Reviewerly/exHarmony huggingface dataset:
Blockchain-based smart contracts and conflict rules for business-to-business operations

In recent years, the irruption of blockchain technology has enhanced the impact of smart contracts in the international trade scenario, although not without raising some problems, particularly, in terms of Private International Law.This paper, thus, addresses such problems when it comes to determining the applicable law from a business-to-business perspective leaving aside the particular problems raised by the conflict-of-law rules oriented to protect the weaker party to a contract.The analysis, however, starts with a general approach to the two concepts which are the object of this paper: smart contracts and blockchain technology.RESUMEN: En los últimos años, la irrupción de la tecnología blockchain ha incrementado la proyección de los smart contracts en el escenario del comercio internacional, no sin plantear algunos problemas, en particular, por lo que respecta al Derecho internacional privado.Este artículo, por lo tanto, aborda tales problemas en el ámbito del conflicto de leyes desde una perspectiva business-to-business, dejando de lado los problemas planteados por las normas de conflicto orientadas a proteger a la parte débil del contrato.El análisis, sin embargo, empieza con una aproximación general a los dos conceptos objeto de este artículo: los smart contracts y la tecnología blockchain.
Easy Urls In The Content Management System With Crawlers For Added Security

Websites are becoming busier by the hour, and URL is what differentiates a single one from the rest. Additionally, a record of bootlickers would require metadata of the page to give classification. This study is aimed at describing the role of friendly URLs in the content management system (CMS) and the power of global ranking with added security. Some selected scientific databases to discover a piece of literature about URLs (search engine optimization) in the content management system and global ranking with crawler with added safety was searched in order to achieve the objective of this study,. The finding shows that keywords and the length of URL are the major factor in CMS and the global ranking of the search engines. It was further revealed that a friendly URL is significant by weighing in to give developed probabilities for sycophants to creep over site pages. It also circumvents the probabilities of uncovering the authentic and real URLs where the content resides, thereby decreasing the chances of hacking. Hence, a concise and understandable URL should be chosen during website development.
TOOLS AND SERVICES OF CLOUD-ORIENTED OPEN SCIENCE SYSTEMS FOR LYCEUM TEACHERS PROFESSIONAL DEVELOPMENT

The article is devoted to the urgent problem of using the tools and services of cloud-oriented systems for the professional development teachers of lyceums as a new type of general secondary education institution as well as the effective use of these tools and services to ensure the quality of specialized education. The purpose of the article is to substantiate the choice of tools and services of cloud-oriented open science systems for the professional development of lyceum teachers. The directions of lyceum teacher’s professional development are determined with the help of such research methods as analysis, generalization, systematization of scientific and scientific-methodical sources on the research problem, and analysis of cloud-oriented tools and services. The author proposes to select tools and services by categories that cover the full range of educational activities of teachers and use innovative approaches and technologies such as open science cloud services and computer modeling systems. The teachers' use of the AiiDA cloud-oriented environment provides access to a number of additional services, such as lecture recordings and interviews on specific aspects and results of groundbreaking research; collections of short training courses on selected topics conducted by renowned lecturers from around the world. The author notes that for biology and chemistry teachers, it would be appropriate to familiarize themselves with the 3DBIONOTES-WS web application (online process modeling), designed for adding biochemical and biomedical information to structural models by scientists from around the world. The author focuses the attention of teachers, in particular natural sciences and mathematics teachers, on the use of competency tasks and computer modeling systems in the educational process. The research provides examples of tasks detailing both areas of long-term teacher development and methodological aspects of new technologies application in educational practice.
La distribuzione dei verbi modali in testi legislativi europei e italiani. Uno studio corpus-based sulla variazione intralinguistica di dovere e potere

This study focuses on the distribution of modal verbs (dovere and potere) in EU and Italian legislative texts. The analysis of intralingual variation is led by comparing three legislative corpora belonging to the Eurolect Observatory Multilingual Corpus: Corpus A (EU directives), Corpus B (Italian implementing laws of EU directives) and Corpus C (Italian national laws). Quantitative data are discussed and exemplified in order to provide qualitative considerations related to the expression of obligation or necessity, prohibition and permission. Cross-corpora results show morphological variation between Italian Eurolect (Corpus A), EU-derived legislative Italian (Corpus B) and national legislative Italian (Corpus C) as far as the deontic modality is concerned.
Doc2Bot: Document grounded Bot Framework

Conversational agents, or chatbots, are widely used to provide customer care and other informational support. Currently, the development of chatbots using standard frameworks requires a lot of manual crafting by subject matter experts (SMEs). On the other hand, while learning-based approaches to dialog have made significant advancements, they require training with a large volume of dialog data, which chatbot developers typically do not have access to. To tackle these challenges, we introduce DOC2BOT, a system that supports the automated construction of chatbots by digesting various forms of documents such as business manuals, HowTos, and customer support pages that organizations own. In addition to that, DOC2BOT provides a user-friendly experience to SMEs, and to minimize their effort by supporting intuitive interactions and streamlining their workflow.
The Sparse Vector Technique, Revisited

We revisit one of the most basic and widely applicable techniques in the literature of differential privacy -- the sparse vector technique [Dwork et al., STOC 2009]. This simple algorithm privately tests whether the value of a given query on a database is close to what we expect it to be. It allows to ask an unbounded number of queries as long as the answer is close to what we expect, and halts following the first query for which this is not the case.We suggest an alternative, equally simple, algorithm that can continue testing queries as long as any single individual does not contribute to the answer of too many queries whose answer deviates substantially form what we expect. Our analysis is subtle and some of its ingredients may be more widely applicable.In some cases our new algorithm allows to privately extract much more information from the database than the original.We demonstrate this by applying our algorithm to the shifting-heavy-hitters problem: On every time step, each of n users gets a new input, and the task is to privately identify all the current heavy-hitters. That is, on time step i, the goal is to identify all data elements x such that many of the users have x as their current input. We present an algorithm for this problem with improved error guarantees over what can be obtained using existing techniques. Specifically, the error of our algorithm depends on the maximal number of times that a single user holds a heavy-hitter as input, rather than the total number of times in which a heavy-hitter exists.
Clustering with Euclidean Distance, Manhattan - Distance, Mahalanobis - Euclidean Distance, and Chebyshev Distance with Their Accuracy

There are several algorithms to solve many problems in grouping data. Grouping data is also known as clusterization, clustering takes advantage to solve some problems especially in business. In this note, we will modify the clustering algorithm based on distance principle which background of K-means algorithm (Euclidean distance). Manhattan, Mahalanobis-Euclidean, and Chebyshev distance will be used to modify the K-means algorithm. We compare the clustered result related to their accuracy, we got Mahalanobis - Euclidean distance gives the best accuracy on our experiment data, and some results are also given in this note.
A fusion of aspect and contextual information for rating prediction in recommender system using a latent factor model

Referring to reviews, checking online comments and, visiting different websites before buying any product is a call of the day. Online reviews are an excellent source of information both for users and organisations alike. In this article, a hybrid model, named as aspect and context-based latent factor model (ACMF), is proposed to predict user rating on an item based on star ratings provided by users, feature-opinion information, and context information. ACMF mainly consists of three phases: the first phase extracts spam reviews, the second phase extracts features and opinions from written reviews and calculates the polarity score of opinions. In the last phase, reviews and context information are aggregated to predict the unknown rating of a user for better recommendations. The proposed model is tested on ratings and reviews downloaded from the Amazon website. Experiment results show RMSE of ACMF has been achieved significantly less than other relevant methods.
On Basic Probability Logic Inequalities

We give some simple examples of applying some of the well-known elementary probability theory inequalities and properties in the field of logical argumentation. A probabilistic version of the hypothetical syllogism inference rule is as follows: if propositions A, B, C, A→B, and B→C have probabilities a, b, c, r, and s, respectively, then for probability p of A→C, we have f(a,b,c,r,s)≤p≤g(a,b,c,r,s), for some functions f and g of given parameters. In this paper, after a short overview of known rules related to conjunction and disjunction, we proposed some probabilized forms of the hypothetical syllogism inference rule, with the best possible bounds for the probability of conclusion, covering simultaneously the probabilistic versions of both modus ponens and modus tollens rules, as already considered by Suppes, Hailperin, and Wagner.
On the Accuracy Evaluation of Access Control Policies in a Social Network

Access control policies are mandatory for organizations whose operation involves sharing resources that must be kept private. In this paper, we address the problem of evaluating the accuracy of access control policies distributed in an interaction network modeled from a social network. Such network models granted access to documents owned by a large set of users. Since denied accesses are not included in the input network, we discuss a method based on Network Science to include complementary edges to have an approximate evaluation of ACPs’ accuracy. The synthetic interactions allow the evaluation of ACPs by assessing the explicit and implicit intentions of the owners. We present an evaluation strategy to measure the accuracy of the generated ACPs. The results will be of interest to academics who want to synthesize information for similar phenomena.
The Evolving Collaboration – AMazed! The A-Maze artists investigate immersive technology to create imagination and artifice

This paper examines the construction of an artificial edifice, a navigational architecture, which connects A-Maze Artists' world and development of toolkits for artists to enhance their working practice.The cross-generational, culturally diverse A-Maze artists use a trans-disciplinary approach, mutual interviewing techniques, insights from online meetings, continuous evaluation, iterative design-decisions, critical challenges and questioning.A-Maze artists investigate their working practices, share visual imagery, symbolic language, identifying differences and shared interests.Within these conversations, the artists have been reconsidering, shifting ground, transforming their practice and vision in response to their co-collaborators.A-Maze have reached out to artists from various other regions internationally.Previous research by A-Maze artists explored virtual technologies by artist/practitioners, identifying issues around ideas of 'natural', 'random' and 'uncanny'; access to technologies; ethical frameworks and digital regulation.Today A-Maze includes artists have diverse skill-sets covering areas such as architectural/service user design; 3D character animation; 3D development; cartography; curatorial, public engagement animation and cyber/virtual eco-landscapes.They build on their histories of migration and lockdown, using virtual tools and/or visualisation to realise these interconnected immersive worlds to present: 'Boundless: Worlds in Flux'.Within these worlds, participants visit interconnected immersive multiverses of visual imagery, sound and text.From our age of the Anthropocene, A-Maze imagines Virtual Worlds, transposing ideas from landscape to virtual-scape.Exploring narrative navigation through the use of maze, game, cycle, metaphor and avatars.Embracing cocreation in a meaningful way through imaginative, inventive curation. VR. Navigation. Virtual worlds.
A cryptocompression system with Multi-Factor RSA algorithm and Levenstein code algorithm

Abstract Exchanging digital messages by electronic means has a major security concern. The data being sent can be accessed and read by some unintended parties if there is no security system involved. Cryptography obscures the messages being sent and they can only be read by intended recipients by using the right key. Using asymetric cryptography algorithm such as Multi-Factor RSA may help to obscure a message with high security; however, the ciphertext is usually much larger than the message so it takes much more time to transmit. In order to solve this problem, this research combines the Multi-Factor RSA with the Levenstein Code algorithm in a cryptocompression system to compress the size of the message being sent. This research also compares encrypt-then-compress scheme with compress-then-encrypt scheme. The result shows that encrypt-then-compress scheme has a better compression ratio than the compress-then-encrypt scheme. On the contrary, in terms of actual time performance, the compress-then-encrypt scheme is faster than encrypt-then-compress scheme.
A Quasi Experimental Study on the Influence of Blending Learning on College Students' Information Literacy

To explore the influence of blending learning on College Students' information literacy. Class A and B with similar average level of information literacy were selected as the research objects. Class A (106 students) was the experimental class, and class B (131 students) was the control class. During the research period of one semester (four months), the following measures were implemented for the two classes: The control class studied developmental psychology according to the conventional teaching methods and procedures; The experimental class studied developmental psychology according to the requirements and procedures of blending learning. At the beginning and the end of the course, the two classes were assessed with Network Information Literacy and Competence Scale for College Students (NILCS). At the beginning of the course, the total average NILCS scores of two classes were (2.88 ±0.33) and (2.90 ±0.44) respectively, and the difference was not statistically significant (P > 0.05); At the end of course, the total average NILCS scores of experimental class and control class were (3.38 ±0.29) and (2. 97±0.42) respectively, and the difference was statistically significant (P < 0.001). Blending learning can improve the information literacy of college students to a certain extent.
Detect Text Topics by Semantics Graphs

It is beneficial for document topic analysis to build a bridge between word embedding process and graph capacity to connect the dots and represent complex correlations between entities. In this study we examine processes of building a semantic graph model, finding document topics and validating topic discovery. We introduce a novel Word2Vec2Graph model that is built on top of Word2Vec word embedding model. We demonstrate how this model can be used to analyze long documents and uncover document topics as graph clusters. To validate topic discovery method we transfer words to vectors and vectors to images and use deep learning image classification.
Qualitatively Analyzing PR Rejection Reasons from Conversations in Open-Source Projects

Software developers have largely relied on pull requests as a mechanism of collaboration in their projects. Researchers have collected and analyzed pull request data in different ways for different reasons. In particular, we have qualitatively analyzed pull request conversation data to understand the main reasons for pull request rejection from a developer's perspective. In this paper, we report results from ongoing research on identifying and categorizing pull request rejection factors. Two software developers, co-authors of this paper, manually analyzed 605 rejected PRs from Hexo and ESLint. We found that the most frequent reasons for PR rejection may vary depending on the project size and popularity. Still, some common rejection factors include implementing unnecessary functionality, conflicting PRs, agreement to make PR reattempts, and inactivity. Code quality issues are not among the most frequent reasons.
Technology for developing the professional competence of physical education teachers in architecture and construction university

The objective of this paper is to investigate the possibility of forming the professional competence of physical education teachers in a university of architecture and engineering. At the beginning of the experiment the baseline level of teachers' professional competence was determined in order to form the control and experimental groups among them. In the control group the formation of competence of teachers was carried out by taking professional development courses according to the «standard» program, according to which the participants were given lectures, seminars on various modules of the program, having to complete a course with a final qualifying paper on a selected topic. Teachers in the experimental group were trained according to the professional development programme, taking into account the developed model of competence formation. At the end of the training the previously studied indicators were tested in both groups and the data obtained was then compared. As a result, it was found that the professional competence level of teachers in the experimental group increased significantly compared to this in the control group. Thus, it showed that to be able to form teachers' professional competence «standard» professional development programmes currently implemented by Kazan State University of Architecture and Engineering are not enough. For effective formation of competence it is necessary to have a special technology of teachers' training, which is implemented in the developed pedagogical model of formation of teachers' professional competence.
Saliency-Based Brain Abnormality Identification in Magnetic Resonance Images

Due to the great development in the field of digital image processing, it has become an integral and important part of computer-aided diagnosis systems.Magnetic resonance image (MRI) processing is one of the hot fields that attracted researchers due to its role in improving and speeding up diagnosis.This work presents a new method for identifying abnormal regions in brain MR images using saliency recognition techniques.This is because tumour regions or abnormal regions share with saliency the fact that these regions differ from the rest of the image in terms of size, luminance, and texture.In this paper, we use a saliency extraction method that uses the irregularity of the regions in its definition, as this method depends on the basis that the salient areas in the image are rare and different from the rest of the image, which is what we need to determine the tumour area.The proposed algorithm is applied to a standard dataset and the obtained result showed a high level of accuracy, where the precision, recall, F-measure, and accuracy averages reached 91.8%, 96.2%, 84.5%, and 96% respectively.The results were discussed thoroughly, and the limitations were identified and discussed as well.
Digital Teaching and Learning: Perspectives for English Language Education

The ongoing digitalization of social environments and personal lifeworlds has made it crucial to pinpoint the possibilities of digital teaching and learning also in the context of English language education. This book offers university students, trainee teachers, in-service teachers and teacher educators an in-depth exploration of the intricate relationship between English language education and digital teaching and learning. Located at the intersection of research, theory and teaching practice, it thoroughly legitimizes the use of digital media in English language education and provides concrete scenarios for their competence-oriented and task-based classroom use.
The using Up-Date requirements in classroom during online teaching

This article is devoted to teacher motivation through the use of high technologies. Video is one of the resources that provide audio-visual input to children, interact them in active learning and motivates teachers to use technology in the classroom for effective teaching. The theme of this research is chosen because of the interest of teachers.
Model for measuring concentration ratio distribution of a dish concentrator using moonlight as a precursor for solar tower flux mapping

<abstract> Measuring solar flux distribution (also called flux mapping) of a large receiver is quite challenging. Lunar flux mapping measures the illuminance distribution on the receiver aperture and the direct normal lunar illuminance during moonlight concentration experiments to determine the concentration ratio distribution (CRD). This paper presents a new lunar flux mapping model to extend the applicability to parts of the lunar cycle where the moon is not full. A dish concentrator with a similar concentration ratio to a tower concentrator was built in Beijing and used for lunar flux mapping experiments. A general method of backward ray tracing with effective sun/moon shapes for simulation of CRD is developed. The moonshape image and the normalized error image are convolved in two dimensions using the Fast Fourier Transform to give the effective moon shape image. Several optical simulations and moonlight concentration measurements on the concentrator show good similarity in the effects of changes in light source shape between solar and lunar CRD images. This model recognizes the potential of a solar concentrator to enhance the similarity between the solar CRD and a lunar CRD and that the residual differences can be compensated to some extent by using the smoothing filtering of the lunar CRD image to approximate the expected solar CRD image. The cosine similarity between lunar and solar CRDs is a function of the cosine similarity between the corresponding light source shapes, which can be derived from the dish concentrator and shows promise for application to a large solar tower system. </abstract>