Reviewerly/exHarmony huggingface dataset:
A Methodology for Assessing Translation Quality Generated by Sign Language Machine Translators: A Case Study with VLibras

Machine translation tools for sign languages are developed to reduce barriers to access to information for deaf people. However, these technologies have some limitations related to the difficulty of dealing with some specific grammatical aspects of sign languages, which can negatively influence the experience of deaf users. To address this problem, we developed a methodology for assessing the quality of the translation of machine translators from Brazilian Portuguese (PT-BR) to the Brazilian Sign Language (Libras). We apply the evaluation methodology as a study case with Libras, a Brazilian machine translate to Libras. In this experiment, some Brazilian human interpreters evaluated the treatment of some specific grammatical aspects in the application. As a result, we observed significant limitations in the translations performed by this application, indicating the need to improve the treatment of these grammatical aspects. Thus, the proposed methodology can be used by researchers and developers in the field to identify limitations and points of improvement in the process of translating a spoken-to- sign language machine translator.
Computer Vision on Wheelchairs: Detecting Sleeping Behavior of People with Intellectual Disabilities

There have been few products or research efforts on designing for people with intellectual disabilities. The caretaking companies have no enough caretakers to keep an eye on the clients with intellectual disabilities, who are suffering from circadian rhythm disorder. We report on the design of a system to detect the sleeping behavior of people with intellectual disabilities in the daytime. The system utilizes an inexpensive 2D camera with computer vision techniques to track whether a user is falling asleep. The system wakes up the clients gradually in several steps when a long-time sleeping is detected. Our study explores taking eye aspect ratio, head orientation as inputs, and a support vector machine to managing complex situations in real life.
Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract)

Estimating the normalization constants (partition functions) of energy-based probabilistic models (Markov random fields) with a high accuracy is required for measuring performance, monitoring the training progress of adaptive models, and conducting likelihood ratio tests. We devised a unifying theoretical framework for algorithms for estimating the partition function, including Annealed Importance Sampling (AIS) and Bennett's Acceptance Ratio method (BAR). The unification reveals conceptual similarities of and differences between different approaches and suggests new algorithms. The framework is based on a generalized form of Crooks' equality, which links the expectation over a distribution of samples generated by a transition operator to the expectation over the distribution induced by the reversed operator. Different ways of sampling, such as parallel tempering and path sampling, are covered by the framework. We performed experiments in which we estimated the partition function of restricted Boltzmann machines (RBMs) and Ising models. We found that BAR using parallel tempering worked well with a small number of bridging distributions, while path sampling based AIS performed best with many bridging distributions. The normalization constant is measured w.r.t.~a reference distribution, and the choice of this distribution turned out to be very important in our experiments. Overall, BAR gave the best empirical results, outperforming AIS.
A Multi-device Evaluation Approach of Passenger Information Systems in Smart Public Transport

Adaptive passenger information for an enhanced mobility experience may be the next step towards a smart public transport. In our research project, we have developed a multi-device evaluation approach for adaptive passenger information systems of mobile public displays. An adaptive passenger information system needs to be aware of the passenger’s context. In order to fulfill this requirement, we use the passenger’s personal devices like smartphones or smart watches as context sources. In this paper, we describe our approach of a multi-device passenger information system evaluation focusing on privacy aspects. We present three different methods of pseudonyms that were used to visually link the personal information on passenger’s private devices with the displayed information on the public display. In addition, we report on our evaluation results from a user study evaluating the acceptance and the intelligibility of the used visual pseudonyms.
A dual-arm, hydraulically-actuated robot for operations within radiological environments

Nuclear decommissioning environments are an ideal example of where robotics can be utilised incredibly constructively. Decommissioning generally can be an unpleasant manual task with traditional civil engineering hazards, such as high temperature or extreme noise, alongside the radiological ones. Thus, the use of robotics in such environments is a popular one – even if there are many difficulties which may not be obvious initially. Electrically actuated robots are the most common and easiest robot type to use, but suffer from low payload limits and are vulnerable to high radiological fluence. Another problem is in teleoperation of the robots – a highly skilled operator is required to work for long hours and human error often increases with fatigue. We present here a hydraulically actuated two arm robot, each possessing seven degrees of freedom and a payload of 75 kg. Each of the joints within the arms feature potentiometer based feedback which can be used to inform any software algorithm of the position and orientation of the arms at any time. Further, the end effectors can be equipped with a variety of tools such as saws, grippers or buckets. The two manipulators can be controlled tele-operationally via twin joysticks, although this is often a highly complex operation requiring significant experience. The alternative is semi-autonomous control which is implemented here via three elements. Firstly, a commercially available vision system, the Microsoft Kinect, which has been widely utilised in numerous fields in research. The information from the Kinect is fed into the MATLAB software environment, with user interaction allowing the location and orientation of cut to be determined. This position and required orientation data is fed into National instruments LabVIEW software, where the inverse kinematic mathematics are performed and the required joint angles of the robotic arm are determined. Finally, a Compact Field Point (CFP) controller is used to physically move the joints of the arms into the required positions, thus desired operations can be undertaken. The example task chosen is the cutting of a single plastic pipe at an unknown orientation and location. The intention is that the right arm grips the pipe at the location chosen by the user in the MATLAB program, while the left arm, equipped with a small circular saw, performs the actual cutting operation. Both tele-operational and semi-autonomous control of the system was employed here in order to compare the two systems, with times taken to cut the pipe compared as well as the quality of cut.
Transnational Access to on-site modelling resources and hazard assessment tools: Establishing the pillars of scientific collaboration.

&amp;lt;p&amp;gt;The Agencia Estatal Consejo Superior de Investigaciones Cient&amp;amp;#237;ficas (CSIC) is the largest public multidisciplinary research organization in Spain. The Institute of Earth Sciences Jaume Almera (ICTJA) of Barcelona is one of the main CSIC centres dedicated to Earth Sciences. The Group of Volcanology of Barcelona (GVB), part of Environmental Geology and Geohazards of the ICTJA,&amp;amp;#160; has vast experience in numerical and experimental modelling of volcanic and related processes, as well as in the development of hazard assessment and risk management e-tools and methodologies to be applied in active volcanic regions. Within the framework of the EUROVOLC project, the GVB-ICTJA has offered physical access to on-site modelling resources including initial training, guidelines and technical assistance to simulate with the FEM modelling software COMSOL Multiphysics: (i) thermo-fluid dynamic processes occurring during the phases of magma injection, accumulation and cooling and (ii) local and regional stress field of a volcanic area. The on-site access has been complemented with further remote assistance to the users to help finishing their research work. Additionally, the ICTJA has provided on-site access to VOLCANBOX (http://www.volcanbox.eu), an e-tool that integrates, in a systematic and sequential way, a series of well-tested tools addressing various aspects of the volcanic hazard processes and risk assessment. E-tools-computer or Web-based applications can help users employ probabilistic methods to assess and forecast volcanic eruptions and hazards, as well as their spatial and temporal likelihood of occurrence. In the first Transnational Access Call opened by the EUROVOLC project two accesses were funded, one for each offered installation. Thanks to the activities carried out during both accesses, the pillars for future scientific collaboration between the visiting research groups and the GVB-ICTJA have been successfully&amp;amp;#160; consolidated.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;These activities were funded&amp;amp;#160; by the EUROVOLC project (Horizon 2020 Grant Agreement: 731070).&amp;lt;/p&amp;gt;
Jan Chovanec, The discourse of online sportscasting: Constructing meaning and interaction in live text commentary. Amsterdam: John Benjamins, 2018. Pp. 303. Hb. €100.

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A BI-TECHNICAL ANALYSIS FOR ARABIC STOP-WORDS DETECTION

Stop words are defined as words that frequently appear in texts without carrying any significant information. For the Arabic language, existing works suffer from two main drawbacks (i) the use of only proprietary corpus and (ii) the reliance of only the frequency metric. Our approach for automatic Arabic stop-words detection uses a new metric based on a supervised machine learning process and a vector space representation that can be applied to any corpus, taking into account both domain-independent and domain-dependent stop-words. Conducted experiments to evaluate the proposed approach show a significant improvement reaching 91.85% for the detection rate using the F-measure metric.
The Design and Development of Student Electronic Homework Management System

Abstract With the continuous development of information technology, computers and networks have been deeply integrated into the basic process of teaching and learning. In order to solve the basic problems of the traditional homework management mode, on the basis of demand analysis, this paper designs and develops a student electronic homework management system, which provides teachers and students with a convenient and efficient electronic homework online management platform. The system adopts a three-tier architecture system of B/S mode, with clear navigation, convenient use, high operating efficiency, and strong security. It implements user management, course management, job management, announcement management, link management, communication management, system management, etc. The function has solved the collection, management, review, communication and other problems of students’ electronic homework, and can effectively improve the efficiency of electronic homework management in the teaching and learning process.
The Library Squad: Tweens in the Public Library

Though tween services in libraries are far from new, there is surprisingly very little written about them. Unlike early literacy, which is undoubtedly the most common priority amongst librarians serving youth, tween services might seem like the newest passing trend. Some libraries have dedicated tween librarians who not only offer tween-specific programs but curate tween collections. Other libraries offer combination tween and teen programs. At the downtown Eugene Public Library, tween programs fall under the umbrella of school-age programming for youth ages six to twelve. Trend or not, youth services staff have excitedly begun to delve more deeply into this often forgotten stage.
Use of Big Data at Anatel : A Case Study at National Telecommunications Agency

The growth in the volume of data generated by applications affects both public and private institutions. In the National Telecommunications Agency (Anatel), problems related to the Big Data scenario, such as degradation in the performance of these environments, high costs for maintaining the infrastructure and low performance, are commonly observed. Distributed processing solutions, such as Hadoop, has emerged as a way to circumvent this problem. This study presents research on the issue of textual searching in Anatel, aiming to bring answers to the degradation of the environment, poor performance of queries and increased costs to maintain the current structure used to process the large volume of data. which is the best cost-benefit of the current station of Anatel. The results are presented in this paper.
Enhancement of an Encryption System Performance using MPI

Nowadays with a tremendous speed and continuous development, the world's connection to the Internet has increased to a point that it has become part of their unsteady lives. Thus as technology evolves, encryption has become a priority for our lives to protect sensitive data from hacking and piracy. However, this process takes a long time to transfer, handle and program data by the appropriate electronic means. In this paper we present a new methodology which depends on distributed memory architecture based on message passing Interface( MPI) to enhance the performance of the sequential algorithm. Our results showed that the new model give 2x speed up compared to the previous one.
Gamified tool to mitigate change resistance causes in software process improvement

Software development companies are interested in the implementation of best practices for facilitating their processes improvement with the purpose to increase the quality of their software products. However, software process improvement initiatives are complex because of look for modifying the conditions and behaviors of the professionals in charge of these initiatives. Therefore, exist a constant search of strategies for decreasing change resistance and gamification is one of the most used for helping to influence people's behaviors and contribute to reach the improvement goals. This work presents a web platform called the “Planetary exploration system”, where work team members can explore different worlds through mission accomplishment. Such missions allow winning points, achievements and experiences for ascending in the positions board and obtain virtual and real rewards. The platform can be integrated with software project management systems, incident management systems or support tools for other SPI processes.
URecommender: An API for Recommendation Systems

Recommendation systems are intended to assist users in dealing with information overload by providing a content filtering mechanism. Content filtering is based on the user's preferences and interests. Current recommendation systems suffer from the problem of a lack of initial information about new users. This problem, known as the cold-start problem, is present both in existing systems and in new systems, in which any user is a new user. In addition, web application developers find it difficult to integrate recommendation systems into their applications, having to resort to third-party software or develop the recommendation system from scratch. In this work, URecommender is proposed, an API for web recommendation systems composed of a Middleware and a Framework capable of identifying the textual content of greatest interest to the user and recommending relevant related content. Such identification is done implicitly and based on the user's current behavior, which can solve the cold-start problem. In addition, URecommender gives the developer greater control over the recommendation system that will be integrated into the web application under development. The API was used for the development of a real web application and demonstrated good results in the recommendations generated.
Relationship of federal funding to IDEB results in a state in Brazil: an approach based on Educational Data Mining

To ensure transparency and provide ways for analysis and auditing of various public activities and expenditures, the Complementary Law 131, known as the "Transparency Law," requires the Union, States, and Cities to disclose their expenses in real-time through Internet. However, despite the apparent progress in opening data in Brazil, applications do not follow the various recommended models. Since this data is mostly unconnected, a clear view of the underlying contexts of a query becomes impossible. Thus, there is no clear relationship between recorded expenditure data for education, quality indicators, and/or descriptive census data. The following research sought to create relations between data from the Brazilian Federal Government Open Data Portal and the primary education quality indicator, IDEB, in the cities of the state. The methodology used was Data Mining, a research field resulting from the intersection between the areas of Computer Science and statistics, which seeks to discover non-trivial information hidden in large data. Using Correlation and Linear Regression in the collected and formatted data, it was not found linear relationship, indicating that only cities funding data is not sufficient to obtain a causal relationship with the IDEB average for municipalities. The statistical result found, although it does not provide a direct correlation between the variables investigated, represents a relevant scientific finding in the non-causal relationship itself. The more relevant contribution of this research is the process of selection, preprocessing, and transformation of the data scattered in different information sources and different formats of the analyzed data, as well as the originality of the analyzed causality.
Training based on a 3D virtual world as a didactic tool for computer learning processes

Virtual worlds have become everyday, their use ranges from entertainment to simulation of real scientific environments, they have been increasingly incorporated into teaching to complement the classroom. A methodological change is required to allow a method focused on content and the teacher, one focused on e - activities and the student. This article exposes the results and conclusions of a research research process by incorporating a virtual 3D world without immersion as a didactic tool to support the silver activities in the classroom of university students in the computer science academic space. The research is specified under an empirical-analytical method, with an experimental design, based on G1O1 X O2 and G2 O3-O4. The high levels of interaction by the experimental group of students with the virtual 3D world of indicative learning improvements in academic performance compared to the control group, because their self-learning processes are strengthened. In addition, the data detected will analyze with parametric analysis techniques by which the difference of the quantitative results in the academic process between the two groups that are statistically significant is verified, which concludes the success of the experimental treatment.
SSM-Seq2Seq: A Novel Speaking Style Neural Conversation Model

Abstract Open domain personalized dialogue system has attracted more and more attention because of the ability of generating interesting and personalized responses. To incorporate speaking style, the existing methods first train respectively a response generator over a non-personalized conversational dataset and a speaking style extractor over a personalized non-conversational dataset, and then generate personalized responses by the parameter sharing mechanism. However, the training datasets’ speaking styles of the response generator and speaking style extractor is totally different, which makes the performance of the existing methods be not optimal. Intuitively, it will improve the performance by decreasing the gap between two training datasets’ speaking styles. Thus, in this paper, we propose a novel speaking style memory sequence-to-sequence (SSM-Seq2Seq) model, which incorporates the speaking style information from personalized non-conversational dataset into the training dataset of response generator to eliminate the gap. Extensive experiments show that the proposed approach yields great improvement over competitive baselines.
Estimating Model-Based Oral Reading Fluency: A Bayesian Approach.

Oral reading fluency (ORF), used by teachers and school districts across the country to screen and progress monitor at-risk readers, has been documented as a good indicator of reading comprehension...
Changing Internet Language Features Among the Korean Scholarly Group

This study aims at identifying how the Korean scholarly group's internet language features changed during the last 10 years. For this study, 2,450 written texts on the same web-site in which a previous study collected data were analyzed. This comparison study showed the following results: 1)First of all, the scholarly group's internet texts still involved standard language, high-quality vocabulary and long sentences; 2)However, it was very difficult to find Chinese characters and the percentage of the usage of English increased significantly; 3)Presenting objective data and numbering were still frequently seen; 4)Furthermore, typical internet languages such as slang, argot and abbreviations began to appear; 5)Texts showing self-reflection and teaching tone have been decreased. Instead, texts implying psychological pressure and worries about their jobs have increased; 6)The biggest change was that most of communicator's names were written in English (or unidentified words) or commonly used internet names. This study concludes that comparing to the previous study, the scholarly group's internet language features have changed (although some based on occupational variables remained the same), and that these changes might be affected by social changes taking place in the scholarly group.
A visual approach to support Change Impact Analysis in object-oriented source code

Change Impact Analysis aims to identify parts of a system affected by the proposed change implementation. Although one may find in literature techniques to automate the impact identification process, it is still highly dependent on the experience with the analyzed software. Studies in this area do not focus on the analysis of the possible impact identified by the techniques. In this paper, we propose a visual approach to deal with the results generated by applying an impact analysis technique to oriented source code. Coordinating visual mappings makes it possible to identify impacted entities regarding the individual difficulty of maintenance. Also, it is possible to determine how are affected the entities. In this paper, we present the implemented approach (tool VisImpala), the generated views, how to interpret them, and the lessons learned.