Reviewerly/exHarmony huggingface dataset:
CodeMaster UI design - app inventor

One way to teach computational thinking in K-12 is through the development of mobile applications with App Inventor. Although there exist several courses in this context, there is still a need for support for the evaluation of the applications created by the students. Specifically for the evaluation of the interface design there are still no automated approaches available. Thus, in order to support the evaluation of the visual design of apps based on its compliance with guidelines, we developed CodeMaster UI Design Rubric - App Inventor in the context of computing education in school. In order to facilitate its application in practice, the evaluation of applications created with App Inventor has been automated. The reliability and validity of the rubric were evaluated through an evaluation with 978 projects from the App Inventor Gallery. The results indicate that the CodeMaster UI Design Rubric - App Inventor can be considered reliable (Cronbach's alpha = 0.72). In terms of construct validity, there is evidence of convergent validity. However, we identified the need to revise some criteria due to a lack of correlations with UI design element categories. Based on these results, the rubric is being improved and larger-scale studies are being carried out.
Solving the Individuation and Counting Puzzle with $$\lambda $$ -DRT and MGL

Individuation and counting present an open puzzle for lexical semantics. The key challenge posed by this puzzle is that polysemous words can be counted according to different facets, using different individuation criteria for each. Several solutions have been proposed and challenged in the past, and the complexity of the responses expected makes it an interesting and pertinent test for formal theories and automated systems. We present a simple solution for this puzzle using an integrated chain of analysis from syntax to semantics and discourse, with a partial implementation that uses publicly available tools and frameworks. This clarifies the status of logical, compositional formalisms for lexical semantics regarding their ability to handle quantification and individuation. We also discuss the ability of the same formalisms to handle the resolution of discourse-level anaphora and correctly parse utterances introducing multiple lexical facets that are later referred to in the discourse.
An In-Depth Analysis of Personality Prediction

The complex nature of human mind poses recurrent challenges for predictive modeling of human traits and behavior and current technological trends has real potential for advancing the endeavor. In this paper, we present an in-depth analysis of the suitability and effectiveness of several personality prediction models, that incorporate both, multimodal and linguistic features. By studying the impact of various modeling decisions on the predictivness of each Big Five personality dimension, our findings suggest that some modeling choices might be at odds with one another or the objective of the target application scenario, which highlights the importance of extensive experimentation and unique modeling approaches for various aspects of this multi-faceted phenomenon.
Design and Implementation of An Architecture for Electronic Billing Through Web Services and Mobile Devices

Electronic billing comes in response to both the needs of businesses and legal foundations defined by regulators, with an increasingly vital importance given a society that becomes more digitally based with each passing day. Electronic billing became possible in Ecuador in 2014, and in 2015, telecommunications companies and exporters began using the service, followed by public sector entities. Soon, all taxpayers are expected to apply electronic billing options. Given the incredible growth in these billing services, an application for Android mobile devices was analyzed, designed, and implemented. This application includes an architecture that integrates electronic signature processes, web services for receiving and authorizing electronic documents, with the generation, distribution, and storage of electronic vouchers over modern and user-friendly interfaces. MobileD methodology was applied because of its agility and special focus on the mobile device market, as it applies techniques and processes that are both well-known and consolidated. Using test-driven development, 82 unit tests and 6 integration tests were made to correct errors, and 113 acceptance tests were implemented among 8 users to verify all of the system’s functionalities and ensure that they system conformed to user’s needs.
Report of the ALCTS CaMMS Cataloging &amp; Classification Research Interest Group. American Library Association Midwinter Meeting, Seattle, January 2019

The ALCTS CaMMS Cataloging & Classification Research Interest Group held its program at the ALA Midwinter Meeting in the Washington State Convention Center, Seattle, WA, on Saturday, January 26, 20...
A tutorial on concurrent zero-knowledge

research-article Share on A tutorial on concurrent zero-knowledge Author: Rafael Pass View Profile Authors Info & Claims Providing Sound Foundations for Cryptography: On the Work of Shafi Goldwasser and Silvio MicaliOctober 2019 Pages 623–648https://doi.org/10.1145/3335741.3335765Published:04 October 2019Publication History 0citation54DownloadsMetricsTotal Citations0Total Downloads54Last 12 Months1Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Optimal ranking of factors affecting students’ academic performance based on belief and plausibility measures

Several factors, either numeric or nonnumeric can have varying degrees of influence on academic performance of students. It is believed that ranking of these factors will, hopefully, assist management to initiate corrective action, with a view to improve students' academic performance. In an academic environment, teachers are frequently in close contact with students and therefore their belief about degree of influence of factors on students' academic performance could be of vital significance. The case study reported in this paper analyzes and proposes a possible and practicable ranking strategy of only selected factors via Dempster Shafer theory of evidence and fuzzy relational calculus.
Prediction-Based Reversible Watermarking for Safe Transfer of CT Scan Medical Images

Due to rapid development in the field of computer networks, exchange of medical records over the Internet has become common practice now-a-days. Medical records, which contain patient information and medical images, are exchanged among medical personnel for number of reasons. Discussing diagnostic and therapeutic measures is one of the main reasons of this exchange. Since patients are highly sensitive about their medical information; therefore these images require strict security. To achieve this stringent requirement digital image watermarking provides a good solution. In this paper, we present a prediction-based reversible medical image watermarking (MIW) system, which is comprised of two phases: embedding phase and extraction phase. In embedding phase, the proposed system, first divides the cover image in region of interest (ROI) and region of non-interest (RONI). Later it embeds a fragile watermark (FW) in ROI for achieving integrity control of ROI and a robust watermark (RW) in RONI for achieving security and authenticity of medical image. In extraction phase, the implanted watermarks are extracted first and then are compared with their reference watermarks to verify the integrity, security and confidentiality of the received image. We have used CT scan medical images for simulations. Experimental results show that proposed system provides better security and confidentiality for safe transfer of CT scan medical images. In addition, proposed system also outperforms the other reversible MIW techniques, which are currently reported in literature.
Comparing Results of Natural Language Disambiguation Tools with Reports of Manual Reviews of Safety-Related Standards

Methods and tools for detecting and measuring ambiguity in texts have been proposed for years, yet their efficacy is still under study for improvement, encouraged by results in various application fields (requirements, legal documents, interviews, ...). The paper presents a fresh-started process aimed at validating such methods and tools by applying some of them to a semi-structured data corpus. This corpus represents results of manual reviews, done by international experts, along with their source texts. The purpose is to check how much results of automated analysis are consistent with the reviewers reports. The application domain is that of safety-related system/software Standards in Railway. Thus, if we increase confidence in tools, then we also increase confidence in Standard correctness, which in turn impacts in conforming products. Care is taken in using, for scientific purpose only, sensitive, unpublished source data (the comments, protected by NDAs), that are kept reviewer-anonymous before statistical results are produced, while the Standards are publicly available texts. The results will also be used to improve the tools themselves, even if much elaboration is still to be carried out: the research is still at its beginning, so metrics for tool evaluation is a goal, whose characteristics are just sketched and discussed in the paper.
Information Extraction in Editorial Setting. A Tale of PDFs

In the last decade the Semantic Web initiative has promoted the construction of knowledge resources that are understandable by both humans and machines. Nonetheless considerable scientific and technical content is still locked behind proprietary formats, especially PDF files. While many solutions have been proposed to shift the publishing mechanism to more accessible formats, we believe that is paramount, especially in business scenarios, to be able to tap into this type of content and be able to extract machine readable semantic information from it. In this demo we show how we can process and semantically annotate Medication Package Inserts, publicly available from the pharmaceutical companies in the form of PDF files. Our proposed solution is fully integrated with a standard PDF viewer and does not require the subject matter expert to use any external software.
A note on Bitcoin’s price volatility

Cryptocurrencies such as bitcoin are sometimes referred to as the new gold and the buzz that surrounded bitcoins in the last few years is akin to the old day’s gold rush. Cryptocurrencies are not directly linked to any monetary policy instruments or fundamentals. Therefore, the analysis of common factors between these virtual currencies and other ﬁnancial asset classes is challenging. Towards the end of 2017, Bitcoin’s price shot up to record high figures as cryptocurrency was gaining popularity not only for transactions but also for investments. This motivated us to investigate the relationship bitcoin prices have with Gold and stock index and crude oil. Historical prices were gathered from the start of 2017 to the end of the year, the Pearson’s Correlation analysis was chosen to study the relationship of Bitcoin and 3 other economic indicators namely gold, crude oil, and stock market prices. Then we did a multiple regression. Bitcoin has a correlation coefficient of 0.966 when compared to the stock market index S&amp;P 500 which means that they both share similar properties and characteristics. The t statistic for each variable was also significant. This is paper explores the possible factors that are correlated with the surge in bitcoin prices and offers views on the relevance of bitcoin in today’s world. JEL Classification : F62, G14, G15 DOI: https://doi.org/10.26905/jkdp.v23i3.3103
An item-item similarity approach based on linked open data semantic relationship

Nowadays, persons produce more data than they can process, leading to an overload of information. Due to this fact, we need to improve the systems of information processing and retrieval. Moreover, recommendation systems are important tools for leading to such an improvement. Recommendation systems based on collaborative filtering may have degraded performance due to the problem known as cold start. In an attempt to solve this problem, we should recommend items based on their content. The content-based recommendation systems exploit external data sources, such as web documents or the Linked Open Data, to compare item contents. However, a few proposals make use of the semantic relationship among the items. In this work, we exploit the semantic relationship provided by Linked Open Data (LOD) to search out automatically relevant item features and propose an approach for measuring the similarity between items. This similarity measure leads to a ranked list of similar items. To evaluate our approach, we performed experiments on two domains: museums and movies. Our approach produced competitive results compared to those approaches that manually define the relevant features.
Research on Coding Compression and Image Segmentation of Graphic Images

with the rapid development of information technology, the computer processing of information is also changing. Therefore, graphic image processing technology has become a hot topic in recent years. Researchers hope that the computer's "eyes" will no longer have no thoughts, but can process the data seen like a person and then send it to the brain (CPU), which is the formal graphic image processing technology. Graphic image processing technology will be widely used in the future with more diversified computer capabilities, such as image processing detection, computer animation design, image processing and so on. Coding compression technology and image segmentation technology are the key points in graphic image processing, which is also the research direction of this paper.
How to design the faultless bribery and coercion prevention electronic voting scheme

Bribery and coercion usually represents two serious problems in conventional voting systems. However, these problems become acute in electronic voting (e-voting) scheme due to its mobility. Recently, Wu et al. first classified the methods used to perform bribery and coercion into five levels. They proposed a level-four secure scheme which can prevent bribery and coercion even when a voter's voting processes are monitored by a briber or coercer. However, their scheme still cannot achieve the highest level -- level-five secure e-voting scheme. That is, even the major secret used for voting is revealed, a voter still can cast his/her vote without violate his/her volition. By introducing an extra setup phase and a slightly modification on the off-line disputation phase on Wu et al.'s scheme, we propose a level-five secure e-voting scheme. The proposed scheme inherits most of the advantages of Wu et al.'s scheme in the security requirement.
Bottom-Up Strategy for Data Retrieval and Data Entry over Front-End Application Software

A few people implement “pattern” and “best practices” without analyzing its efficiency on their projects. Consequently, the goal in this article is to persuade software developers that it is worth to make an earnest effort to evaluate the use of best practices and software patterns. For such motive, in this study we took a concrete case system for geographical locations inputs through user interfaces. Then, we performed a comparative study on a conventional method with our approach, named “reverse logistic” to recover results about, by measuring the time that a user spends performing activities when entering data information into a system framework. Shockingly, we had a diminished of 59% within the sum of time went through in comparison to the time went through on the conventional strategy. This result lays a establish for feeding data from the typical final step and search based on string matching algorithms, speeding up the interaction between people and computer response.
Harmful Impacts of Cell Phones on Environment and Humans

There is an increasing demand of cell phones in this modern era of information technology. Cell phones are being used by about 61% population all around the globe for the purpose of fulfillment of their personal and professional needs. Cell phones have gone from novelties and have undeniably become the most crucial objects in human lives. They connect people by enabling business, helping to behave more intelligently and giving people a voice where phones are the only source to disseminate information. A large section of society remains oblivious to the the harmful aspects of cell phones on animals, birds, human beings, and overall environment. This short communication explain the ways by which cell phones can harm the environment and humans.
The lands platform: lan.guages and d.omain s.yntax

Lan.d.s is a new solution for language design. From general purpose languages like Lise (short for (list (embedding)) to Domain-Specific Languages using the MOODs framework, and everything else in between. Lan.d.s is build around the formalism of Multi-Ordered Grammars, which are a possible alternative to CFGs and PEGs in wider use today. Multi- ordered grammars (or simply MOGs) aim for a better explo- ration of ambiguity, recursion, ordering and associativity during language design. They can be parsed using the Gray algorithm. After parsing in order to ease the production of executable code Lan.d.s introduces the Abstract Syntax Language (ASL), which is an OO solution for compile-time meta-programming. Finally in order to promote language ex- tension and re-use Lan.d.s employs GrammarTraits, as units of composition for both MOG rules and ASL actions.
Mathematical Models of Images and Video and Its Application

In this paper, we propose mathematical models of images and video. The models are based on the approximation of images and video by multidimensional discrete Markov random processes with any number of states. To validate both models, the real and artificial images with the same the transition probability matrices are given. To investigate the adequacy of the models, the estimation of the transition probability matrices was evaluated. According to the experimental results, the presented models are adequate to real images and video, and have high computational efficiency. As an application, the method of the restoration of partially distorted image is then provided. Experimental results show the effectiveness of our proposal.
Computability logic: Giving Caesar what belongs to Caesar

The present article is a brief informal survey o$\textit {computability logic}$ (CoL). This relatively young and still evolving nonclassical logic can be characterized as a formal theory of computability in the same sense as classical logic is a formal theory of truth. In a broader sense, being conceived semantically rather than proof-theoretically, CoL is not just a particular theory but an ambitious and challenging long-term project for redeveloping logic. &#x0D; &#x0D; In CoL, logical operators stand for operations on computational problems, formulas represent such problems, and their "truth" is seen as algorithmic solvability. In turn, computational problems – understood in their most general, interactive sense – are defined as games played by a machine against its environment, with "algorithmic solvability" meaning existence of a machine which wins the game against any possible behavior of the environment. With this semantics, CoL provides a systematic answer to the question "What can be computed?", just like classical logic is a systematic tool for telling what is true. Furthermore, as it happens, in positive cases "What can be computed" always allows itself to be replaced by "How can be computed", which makes CoL a problem-solving tool. &#x0D; &#x0D; CoL is a conservative extension of classical first order logic but is otherwise much more expressive than the latter, opening a wide range of new application areas. It relates to intuitionistic and linear logics in a similar fashion, which allows us to say that CoL reconciles and unifies the three traditions of logical thought (and beyond) on the basis of its natural and "universal" game semantics. &#x0D;
Detecting Spam Tweets in Trending Topics Using Graph-Based Approach

In recent years, social media has changed the way people communicate and share information. For example, when some important and noteworthy event occurs, many people like to “tweet” (Twitter) or post information, resulting in the event trending and becoming more popular. Unfortunately, spammers can exploit trending topics to spread spam more quickly and to a wider audience. Recently, researchers have applied various machine learning techniques on accounts and messages to detect spam on Twitter. However, the features of typical tweets can be easily fabricated by the spammers. In this work, we propose a graph-based approach that leverages the relationship between the named entities present in the content of the tweet and the document referenced by the URL mentioned in the tweet for detecting possible spam. It is our hypothesis that by combining multiple, heterogeneous information together into a single graph representation, we can discover unusual patterns in the data that reveal spammer activities - structural features that are difficult for spammers to fabricate. We will demonstrate the usefulness of this approach by collecting tweets and documents referenced by the URL in the tweet related to Twitter trending topics, and running graph-based anomaly detection algorithms on a graph representation of the data, in order to effectively detect anomalies on trending tweets.
Transfer Learning Using Bi-Lstm With Attention Mechanism On Stack Exchange Data

Stack Exchange is a collection of diversity of topics from different fields which needs the most dominant methods for tags prediction. In our work, we have opted to improve the accuracy by using transfer learning. The Transfer learning reports the problem of how to use amply of categorized data in the source to crack related but diverse problems in a target domain, even though the problems to be trained and tested have distinct features. We trained about 87K instances of data using Bi-LSTM with attention mechanism. We used about 81K of unknown data from physics background for predicting the tags through the knowledge gained by our model. Previous implementation works could hardly achieve an accuracy of 66.89%. Our work has greatly improved the result by achieving an accuracy of 86.54%.
Tactical Pathfinding on a NavMesh

Traditional pathfinding has been focused on finding the shortest route from A to B. However, as gamers demand more realism, this is no longer sufficient. A node that is visible or exposed to the enemy should have a higher cost, while a node that is concealed from the enemy should have a lower cost. Navigation meshes are a popular, efficient method of representing navigable regions of a virtual environment; however, it is not as straightforward to perform tactical pathfinding on these navigation representations. There has been a lot of work on creating an optimal NavMesh representation of a virtual environment, though this is not necessarily required for the purposes of tactical pathfinding. The NavMesh can be more finely tessellated to provide increased detail in areas of different movement properties or tactical significance. Cover spots in game levels can be represented as discrete points. This is often the case with waypoint graph navigation representations.