Reviewerly/exHarmony huggingface dataset:
Sign Language Recognizer Using HMMs

In our day to day lives, we come across especially abled people who perform their daily chores with the aid of motivation that they get from self-confidence. There are many with hearing impairment. Sign language is the most expressed and natural way for them to communicate. Some chains of restaurants have, in fact, recruited deaf servers providing them with employment opportunities. Therefore, automatic Sign language recognition has become the crux of vision research. This paper is based on a project that builds a system that can recognize words communicated using the American Sign Language (ASL). Having been provided with a preprocessed dataset of tracked hand and nose positions extracted from the video, the set of Hidden Markov Models are trained. Using a part of this dataset, identification of individual words from test sequences is done. It provides them with the ability to communicate better, opening up a lot of opportunities.
Mask Scrambling Against SCA on Reconfigurable TBOX-Based AES

In the last years Side-Channel Attacks have become a significant threat against security devices. Given this, several countermeasures have been proposed, ranging from reducing the leaked power consumption to masking schemes. However, these solutions imply a cost, typically in terms of resources, performance, and power consumption. This paper focuses on the deployment of masking to the AES computation supported on re-configurable technologies, in this particular case on a SmartFusion 2 SoC and its FPGA fabric and embedded ARM Cortex-M3 processor. This work proposes a novel masking scheme using Auxiliary Random Tables (RBoxes) to further harden the protection against SCA by not only extending the set of used random masks, but also by improving the update frequency of the mask sets. The implementation results suggest that the existing related masking schemes can be deployed at a cost of 645 additional LUTs, 16 μSRAMs, and no additional Large SRAMs, whilst achieving the same operating frequency.
A Focused Crawler for Web Feature Service and Web Map Service Discovering

Due to globalization and the technological advances of the last decades, a large amount of data is created every day, especially on the Web. Web Services are one of the main artifacts created on the Web; they can provide access to sources of data of many sizes and types. In this work, we approach the challenge of designing and evaluating a Web Crawler to find two OGC (Open Geospatial Consortium) web services standards: WFS (Web Feature Service) and WMS (Web Map Service). Commercial search engines, e.g., Google and Bing, are indubitably doing a useful job as general-purpose search engines. However, some applications require domain-specific search engines and Web crawlers to find detailed information on the Web. Therefore, this work presents SpatiHarvest, a Web crawler that focuses on the task of discovering WFSes and WMSes. SpatiHarvest is a combination of some of the most advanced techniques found in the literature. Through experiments, we demonstrate that it is capable of finding more WFSes and WMSes, with less effort, when compared to the state of the art.
Duplicate Instance Identification In Multiview And Multiscale Systems

Visual content understanding has seen significant advancement in recent years, with researchers having easy access to superior computing power and infrastructure to train deep learning models. Organizations are further using multiple cameras to collect additional data for developing robust image content analysis solutions, across domains. However, such initiatives have introduced a lot of duplicate data and redundancy. This poses a challenge when a consolidated decision must be taken at an object level. In this paper, we propose a solution to identify duplicate instances in a multicamera system which captures images of the same instance, at varied viewing angles and scales. The duplicate instances are identified at a pixel level by using a combination of deep learning algorithms and computer vision geometry. We also devise a similarity index to quantify the extent of similarity between a pair of instances. Further, we present our solution customized for duplicate damage instance identification in vehicles, for the auto finance and auto insurance industry.
Navigating the ELT Employment Landscape

Job search strategies are an important and often over looked part of one’s life-long career development. While there are many job search publications available that range from how to write the perfect CV, to interviewing, the vast majority of them fail to address the complex nature of what’s involved in an international ELT job search. This chapter aims to fill a gap in the literature by addressing the topics of preliminary documentation and how to keep abreast of a vast array of required employment information, the changing nature of ELT job search strategies and where to locate ELT job openings, approaches to certifying documentation for the purposes of an international ELT job search, and practical suggestions for how to stay motivated during an extended long-term ELT job search.
A constraint-based modeling of negative polarity items in result clause constructions in Romanian

Summary The paper discusses the occurrence of emphatic negative polarity items (NPIs) in high degree result clause constructions. We will identify four distributional patterns for Romanian emphatic NPIs. These will range from NPIs that only occur occasionally in result constructions to NPIs that are bound to such constructions and even do not show any truth-conditionally relevant semantic contribution. We reformulate a scalar, pragmatic theory of NPIs in a constraint-based, representational framework, Lexical Resource Semantics . We propose a scalar extension of a standard semantics of result clauses in order to capture the high degree, i.e. intensification readings. The constraint-based, representational perspective of this paper allows for an elegant modeling of the data: (i) We can capture the four distributional patterns as a lexical property of the discussed NPIs. (ii) The semantics and pragmatics of Romanian result clause constructions is accounted for by lexical properties of the result clause complementizers. (iii) A scalar analysis of emphatic NPIs can be applied in embedded clauses and even when the NPI itself does not contribute to the at-issue content of the overall utterance.
Comprehensive Simulation of a Software Project Throughout Several Subjects

Software projects are amongst the most common professional activities of computer engineers. Gaining competences on the design and development of software projects is, however, a complex issue that cannot be tackled within a single subject. In this article, we detail the design and implementation of a teaching methodology that aims at providing a comprehensive simulation of the whole life cycle of software projects throughout the coordination of the practical exercises of subjects of different courses. The proposal consists in developing the same software project in consecutive courses under the perspective of the three main roles involved in the project development: designer, developer and director. In the second course, the students exercise the developer role in teams of 4 people under the supervision of a student of the fourth course, who acts as the director. The director has previously proposed a formal design of the project in the third course (designer role). This methodology has been successfully deployed for 4 years in the Computer Engineering Degree at the Universitat Rovira i Virgili. The results show an improvement of the skills and competences related to the three involved subjects, which include better programming quality, better team coordination and fulfilment of deadlines, as well as a much practical view of the director's role.
Design and Implementation of Virtual Reality Video Incentive and Management Software

Virtual reality (VR) video is a form of media transmission. What is the difference between the visual language and expression methods of VR video and ordinary desktop video? Continuous content creation, viewing feedback are a path of exploration. It is also a potential method to explore the basic VR video language and its aesthetic characteristics through neuroscience. In order to build an electroencephalogram (EEG) signal acquisition platform that meets the needs of VR video language research, VR video incentive and management software was developed to realize the management functions of sequencing, hot loading, playback, scoring, and synchronization of VR videos. The necessity of adding hardware synchronization was verified. Finally, the EEG signal acquisition experiment was successfully completed with the help of video management software.
Social Ills and Higher Education’s Community Service Function: The Strategic Role of Adult and Non-Formal Education Departments in Tertiary Institutions’ Community Engagement Practice

The paper places adult and non-formal education departments at the centre of tertiary institutions’ role in combatting social ills in the country. Introduction provided a background on social vices and the link with higher education. A discussion of the types, causes and effects of social ills formed the next section while the community service function of higher education was highlighted as a reason for active role in addressing societal problems. Adult and non-formal education departments’ pivotal role in tertiary education’s intervention was examined followed by the conclusion and recommendation among which is a call for greater synergy among all faculties and schools in engaging with communities to solve society’s problems with adult and non-formal education departments being the hub for new and innovative programming .
Iterative Recovery for Interfered Scrambling Code Sequence on Factor Graph

To solve the problem of insufficient number of check equation in the reconstruction of high order interfered scrambling code sequence, a reconstruction algorithm is proposed. Firstly, the check relationships based on the scrambling code generator polynomial are used to construct the factor graph, and the factor graph iteration method is used to estimate the scrambling code sequences. Secondly, the check relationship inspection method is used to evaluate the compatibility between the iterative estimation sequences and the generator polynomial, and select the best continuous codeword to restore the scrambler initial state. Finally, the optimal reconstruction sequence is selected from the scrambling code for initial state recovery according to the principle of minimum Hamming distance. Simulation results show that the algorithm can effectively solve the problem of reconstruction by using a limited number of check equations.
Educating Adolescents In Sustainable Travel Urban Behavior Through Mobile Applications Using Motivational Features

Mobile technology can facilitate “anytime and anywhere” learning and has the potential not only to educate people but also to encourage their choices towards greener habits. This paper describes the User-Centered Design process followed within a mobile application aiming to educate pupils/adolescents in adopting a sustainable travel urban behavior using various motivational features. We report the primary outcomes derived from an assessment by a secondary education pupils’ group of six simulated screens of a prospective mobile application named ESTA (Educating pupils/adolescents in Sustainable Travel urban behavior through mobile Applications). We analyze their feedback on the application’s functionality and the possibility for its daily use in order to the adolescents to become more mindful of their environmental impact.
Internet Hate speech – case study of Poland, Romania, India and Bulgaria

As online hate is ubiquitous and spread on the cyberspace, new studies are needed to understand its nature and evolution. We have researched young adults from Poland, India, Romania and Bulgaria to study their hate experiences. We have found out that online hate is an inherent part of their cyberspace activities. This implies a necessity of ongoing education at this field as current skills of participants on dealing with hate speech and possibilities of support as well as legal responsibilities remain relatively low.
Conditional Generation of Adversarial Networks Based on Multiple Generators

Conditional generative adversarial network are widely used in image translation and many other fields. However, traditional conditional generative adversarial networks have the problem of model collapse. To solve this problem, we proposed a conditional generative adversarial network model based on multiple generators. It uses multiple generators to obtain multiple outputs, and adds a distance constraint between multiple generators to output multimodal results. Experiments on Edges2Shoes and Facade datasets show that the diversity distance index LPILS between generated images can be effectively increased with our method. In addition, it also has good results in coloring application scenarios.
Conceptions and awareness of information literacy among professionals and students of Vietnam’s upper secondary schools

This study focuses on investigating the conceptions and awareness of Information Literacy (IL) among professionals and students in Vietnam’s upper secondary schools in order to provide an appropriate suggestion regarding this issue in the implementation of an IL teaching model in the country. The investigation, aimed at achieving the above purpose, was conducted in three upper secondary schools in the country using an open-ended questionnaire and interviews. The questionnaire aims to explore students’ conceptions and their awareness of the IL concept. Meanwhile, the interviews were used for professionals. This study contributes to existing knowledge by providing an understanding of professionals and students’ conceptions and their awareness of IL in Vietnam’s high schools, which is an under-researched context. The findings reveal that there is a real need to work towards enhancing professionals and students’ understanding and their awareness of the role of IL to learning success.
The effects of suggested tags and autocomplete features on social tagging behaviors

Abstract Many websites employ social tagging to allow users to label and classify information. These tagging user interfaces use a variety of features to support efficient and consistent tag creation, including suggested tags and autocomplete for tags. This study uses a custom‐built tagging interface in a controlled experiment to determine how these features affect social tagging behavior. The study finds that suggested tags do not have a significant effect on the number of tags, number of unique tags, number of typos, or time elapsed per tagged provided. However, autocomplete significantly increases the number and consistency of tags provided, significantly decreases the rate of typos, and significantly decreases the elapsed time per tag provided. These findings for the autocomplete feature align with the priorities and constraints of social tagging folksonomies that support retrieval and site navigation and suggest that autocomplete is an important aid for text entry in social tagging user interfaces.
Non-Technological and Technological (SupTech) Innovations in Strengthening the Financial Supervision

The application of non-technological and technological innovations provides support to supervisory institutions in the digitization of reporting and regulatory processes. This chapter deals with international applications of innovations in financial supervision (SupTech). The aim of the chapter is to present the most popular technological and non-technological solutions along with an evaluation of their usefulness in exercising supervision over the financial market. The authors discuss the types of innovations and the reasons for implementing them by supervisory institutions. Furthermore, they describe the most important non-technological supervisory solutions and technologies that supervisors can apply in creating SupTech tools. The study utilizes, among other things, data from reports and elaborations by central banks, supervisory institutions, and consulting companies. The authors' main focus is on the analysis of the solutions utilized by European Union member states.
An Empirical Study of Gender Differences in Competitive High School Debate

Gender differences in competitive environments have been studied extensively; however, the majority of literature concerns activities with an objective winner. In this paper, we examine gender differences in high school Public Forum debate, a two vs. two activity where judges subjectively decide the winner. We constructed a dataset with 44 variables and 125,087 unique debate rounds during the 2014-2015 to 2019-2020 school years. Using logistic modeling, we document a large difference in win rates between teams of different gender compositions, with female-female teams 17.1% less likely and male-female teams 10.0% less likely to win a debate round against male-male teams. However, there is no gender gap in win rates for novice debaters, suggesting that the disparity does not occur from innate entry ability differences but rather appears alongside experience in debate. We also find a large difference in participation rates between female and male students, which begins at the 9th grade level and is exacerbated over time due to female debaters being 30.34% more likely to quit than male debaters. Finally, we find that a higher ratio of female to male debaters from the same school reduces attrition rates of female debaters.
A Robust Feature Based Approach for Bare-Hand Detection under Practical Non-Ideal Conditions

Due to easy detection of contact based devices, color-markers or 3D cameras, state-of-art gesture models mostly employs them to make the gesture. Yet, their lack of user-friendliness limits their use in practical scenarios. Use of barehand to make a gesture, however, comes naturally to the user. However, computer-vision based bare-hand detection is a challenging task, affected by multiple environmental factors. Feature based object detection techniques are easy and robust solution to detection under various non-ideal conditions. In this study, an extensive comprehensive study is carried between two purely spectral (color) features and fourteen color-texture features. Models are developed and compared for different image sizes. The Classification models are developed using Naive Bayes classifier (Probabilistic view), Euclidean distance and Chebyshev distance models (Proximity view) and Real AdaBoost classifier. Experimental results showed that only 2 out of the 16 proposed features has performance less than 90% for hand detection under noisy conditions.
Learning to Modulate Action of Deterministic Policy for Autonomous Navigation

Unmanned mobile robots are widely used in un-known environments, where the exact overall arrangement of environments may not be available. This paper investigates navigation strategy for mobile robots based on reinforcement learning method to allow mobile robots to navigate in such environments. Deterministic policy gradient algorithm has recently been shown to be effective in complex tasks. However, deterministic policy may not be safe to solve navigation problem in unknown environments due to its determinacy. We propose a learning framework composed of dual policy networks, in which one of the policies acts as a tuner for the other. Multiple simulation results demonstrate that the proposed framework implicitly learns key navigation ability and is more efficient than baseline method.
ICT in School Education in Croatia

This chapter presents the state of the art of ICT in education in Croatia by focusing on six major elements: policy perspectives, infrastructure, educational resources, ICT integration into practices, students’ ICT competence and teachers’ professional development. The authors describe the role of technological innovation and its potential in transforming Croatian educational landscape, ranging from primary to secondary schools and to a lesser extent the universities. Although local and European Union funds are available and ready to be utilized for educational resource procurement, the priorities in choosing adequate national strategies and infrastructure elements are still discussed, as well as the means of resource integration into everyday teaching and learning practices. This is especially relevant in Croatia, as the gap between students’ digital competences and teachers’ professional development in usage and application of digital technologies is widening.
De-anonymizing Social Networks with Edge-Neighborhood Graph Attacks

Social networks have a great influence in business, for which the data of social networks are usually released for research purpose. Since the published data might contain sensitive information of users, the identities of which are removed for anonymity before release. However, adversaries could still utilize some background knowledge to re-identify users. In this paper, we propose a novel attack model named edge-neighborhood graph attack (ENGA) against anonymized social networks, in which adversaries are assumed to have background knowledge about targets and their two-hop neighbors represented by 1-neighborhood graph and $$1^{*}$$ -neighborhood graphs respectively. Based on such model, a de-anonymous approach is proposed to re-identify users in anonymous social networks. Theoretical analysis indicate that ENGA has a higher de-anomymization rate. And experiments conducted on synthetic data sets and real data sets illustrate the effectiveness of ENGA.
Development Strategy for Aviation Industry through Introduction of Domestic Avionics Qualification System

Avionics is a compound word of aviation and electronics that began to be used in the late 1930s. In the components or sub-systems installed to the aircraft, avionics is something that works by electronic technology. In the past, the aircraft mate, the flight engineer, and the radar operators performed the work on board the aircraft but the modern aircraft have replaced these tasks with avionics. the aircraft mechanics who maintain and manage such complex aircraft must have expertise and technics with the development of avionics to maintain aircraft airworthiness. This paper is about the introduction of domestic avionics qualification system and the development of avionics maintenance technology. For this, the SWOT analysis is performed by identifying the internal and external environment. And recommend the strategy and direction of domestic avionics qualification and education system.
Quantum Deterministic Computing

A novel deterministic paradigm for creating quantum computing via photon transactions with the electrons of an atom is described. This paradigm is free of quantum logic. The practically focused evolutionary path of quantum computing starting with the classical approach is shown: Memory-Address-Transaction → Electron-Address-Transaction Electron → Address- Quantaction (EAQ). Qubit-vector models for describing functionalities are proposed that differ from the known truth tables in the compactness of description and technological ability of the algorithm implementation for synthesis and analysis of digital devices and SoC components. For example, we consider a memory-driven algorithm for the simulation of digital devices based on qubit-vector forms for describing functionalities with a significant increase in the performance of computational processes. These processes can be utilized for analysis and synthesis through parallel execution of logic operations. A set of comparative estimates of qubit models and methods for improving the efficiency of the algorithms for simulating digital devices is presented.