Reviewerly/exHarmony huggingface dataset:
PEDAGOGICAL SKILLS OF THE TEACHER AS A MEANS OF FORMING A HEALTHY LIFESTYLE AMONG STUDENTS

The article considers the phenomenon of teacher's personal maturity as a key factor in the effectiveness of pedagogical activity. The purpose of our article is to substantiate the pedagogical skills of the teacher as a means of forming a healthy life. Generalization of various approaches gives the grounds to allocate some bipolar parameters which have great value in a context of pedagogical activity and characterize the level of a personal maturity or, accordingly, immaturity of the teacher. Based on the analysis of psychological and pedagogical approaches to the interpretation of the essence of personal development, we determine the following criteria of the teacher's personal maturity: self-determination, capacity for self-awareness, spontaneity, authenticity, readiness for emotionally close relationships, etc., as well as the adequacy of self-perception, flexibility, tolerance for contradictions, understanding of the relativity of things, positive self-image, inclination for creativity, existence of individual life philosophy and professional position. The humanization of the school and the organization of the educational process on the basis of a personal approach requires the teacher to have a high level of personal maturity, who can present him/herself to the students not as an impersonal functionary, professional, but as an original personality, who has his/her own position, which is open in expression, their feelings, emotions and views. Teaching such teachers requires the realization of a set of pedagogical conditions in the educational environment of higher education institutions, connected with ensuring the subjective position of students, intensifying their reflective processes, dialogue, problematization and personalization of pedagogical communication. The preparation of such teachers requires the realization in the educational space of a higher educational institution of a complex of pedagogical conditions connected with the maintenance of the subject position of students, activation of their reflexive processes, dialogical character, personification and complication of pedagogical interaction, Psychology of Technology and Social Psychology.
Building Connections for a Secure User Experience

The focus on design areas that motivate users, enhance user experience instead of just making it usable has made security with respect to data privacy an important topic. There is also a general lack of easily comprehensible information and awareness when it comes to new regulations like the General Data Protection Regulation (GDPR) [1]. Changes in processes or requirements that involve the use of certain data are avoided without studying the finer details of dependencies and connections. This hinders projects with design ideas that might otherwise enhance user-experience. We introduce a method to enable innovative design for human-machine interfaces in compliance with data protection and security regulation that is based on our extensive experience with industrial projects. The paper will provide examples of design concepts that address the security concerns raised while conforming to the main topics of ISO 9241.
Deciphering German diplomatic and naval attaché messages from 1900-1915

In World War One (WW I), the German diplomatic services and the Imperial Navy employed codebooks as the primary means for encoding confidential communications over telegraph and radio channels. The Entente cryptographic services were able to reconstruct most of those codebooks, to obtain copies of others, and to overcome various enhancements introduced by the Germans.A collection of diplomatic and naval attaché cryptograms from and to the German consulate in Genoa, dating from the late 19th Century to 1915, has been preserved and is held in German archives.11 Politisches Archiv des Auswärtigen Amtes, RAV Genua - Records from the German consulate general in Genoa (PAAA – RAV Genua).In this article, the authors describe the process of identifying the encoding methods, of reconstructing diplomatic codebooks, and of recovering the superencipherment applied to the German Navy’s Verkehrsbuch. The vast majority of the messages can now be read in clear. The authors also provide the historical context for the messages, which shed new light on the impact of the mobilization and war declarations on the Genoa consulate, its role in gathering naval intelligence, and in assisting the Goeben and Breslau warships in their escape to the Dardanelles in August 1914.22 An early version of this paper with preliminary results was presented at HistoCrypt 2018 (Lasry 2018 Lasry, G. 2018. Invited talk-special session on Arne Beurling: Modern codebreaking of T52. In Proceedings of the 1st International Conference on Historical Cryptology HistoCrypt 2018, number 149. Linköping University Electronic Press. [Google Scholar]). The current version includes an in-depth historical analysis, as well as a detailed description of codebook 18102.
Salient Object Detection via Depth and Contrast Networks

Deep salient object detection (SOD) methods usually use the end-to-end network to extract the global or local information of the image such as contrast, spatial distribution and objectness. We find that the depth is one important cue of saliency that is neglected by previous works. For a single image, the depth denotes the relative distance of objects to observer, and the relatively closer object in the image usually attracts more human attention and has a higher saliency. In this paper, we proposed a deep convolution network to extract the depth information of the image to predict the saliency. Our network consists of two streams, depth stream and contrast stream. The first stream can predict the saliency brought by object depth through two deep networks. The second stream can extract the contrast information of image through a multi-scale network. The saliency prediction through the depth stream often has blurred boundaries, while the result of the contrast stream is more accurate in pixel level. So, we obtain the final saliency map through the combination of the two stream results. We compare with the state-of-the-art deep SOD methods on four public datasets. The experimental results show that the combination of the two streams can have more accurate performance.
AI Patents and the Self-Assembling Machine

Legal scholarship has begun to consider the implications of algorithmic pattern recognition systems, colloquially dubbed “artificial intelligence” or “AI,” for intellectual property law. This emerging literature includes several analyses that breathlessly proclaim the imminent overthrow of intellectual property systems as we now know them. Indeed, some commentators have prophesied the demise of patentable innovation under the influence of AI research and development tools. Although AI systems pose fundamental challenges to the many areas of law and legal institutions, careful consideration suggests that intellectual property generally, and the patent system particularly, encompasses sufficient flexibilities to address AI innovation. In many cases, previous accommodation of biotechnology within the patent system points the way similar accommodation of AI tools. However, the incorporation of AI innovation into patents reveals a significant gap in patent doctrine regarding issues of causation, which deserves resolution quite apart from the unnecessary furor over the intersection of AI and patent doctrine.
Plain text passwords: A forensic RAM-raid

Despite many academic studies in the last 15 years acknowledging the investigative value of physical memory due to the potential sensitive nature of data it may contain, it arguably remains rarely collected at-scene in most criminal investigations. Whilst this may be due to factors such as first responders lacking the technical skills to do this task, or simply that it is overlooked as an evidence source, this work seeks to emphasise the worth of this task by demonstrating the ability to recover plain-text login credentials from it. Through an examination of logins made to 15 popular online services carried out via the Chrome, Edge and Mozilla Firefox browsers, testing shows that plain-text credentials are present in RAM in every case. Here, a transparent test methodology is defined and the results of test cases are presented along with 'string markers' which allow a practitioner to search their RAM captures for the presence of unknown credential information for these services in future cases.
Usability Testing of a Digital Competence Assessment and Certification System

This research study is based on conducted usability evaluation of the CRISS system, which is a cloud-based system for acquisition, evaluation and certification of digital competence in primary and secondary schools, scalable to other educational levels. The usability evaluation included a combination of tasks completion and questionnaires to collect mostly quantitative, but also qualitative data in order to improve the existing system and give some guidelines for future development of systems with similar scope. In total, 14 teachers and 19 students from primary and secondary schools participated in the evaluation. The results revealed that the effectiveness score of the CRISS system was 97% and 94% on behalf of students and teachers, respectively. One of the efficiency measures showed that in average teachers spent 1.7 min, while students spent 1.5 min per task, but it should be bear in mind that they also had differently assigned tasks. Findings showed no significant differences in score ratings of overall task ease, task time and satisfaction with the system performance.
From Accessible Interfaces to Useful and Adapted Interactions

Ambient intelligence (AmI) is presently considered an important technological development able to support people in all environments (home, office, school, hospital, city). The paper aims to show that: i) the present state of technology already offers the possibility of implementing useful and usable support applications; ii) however its usefulness could be enhanced, increasing impact on all people, with particular reference to people who have some limitations of activities (e.g. older people), if deployed in a carefully planned way; iii) a way off from present limitations may be an artificial intelligence control of the environment itself and of the services made available in it. It is also shown that accessibility is a fundamental prerequisite, but the real problems are the usefulness and usability of available environments and applications. The discussion will be made with reference to an implemented experimental application to support feeding. Its interesting features and remaining limitations are used to support the above statements.
Voice Interaction for Training: Opportunities, Challenges, and Recommendations from HCI Perspective

This paper examines voice interaction requirements in the context of learning and training. The authors reviewed relevant publications, focusing on usability and user experience with conversational interfaces, including speech and chat interfaces. We examined technology trends and limitations, HCI research on speech interfaces, usability evaluations of conversational interfaces in training, including formal evaluation methodologies, and our research projects on voice interaction for military and law enforcement training. Examples of voice technology applications in several domains are provided, along with a set of recommendations for successful design, evaluation and use of voice interaction in training applications.
Incorporating Biterm Correlation Knowledge into Topic Modeling for Short Texts

Abstract The prevalence of short texts on the Web has made mining the latent topic structures of short texts a critical and fundamental task for many applications. However, due to the lack of word co-occurrence information induced by the content sparsity of short texts, it is challenging for traditional topic models like latent Dirichlet allocation (LDA) to extract coherent topic structures on short texts. Incorporating external semantic knowledge into the topic modeling process is an effective strategy to improve the coherence of inferred topics. In this paper, we develop a novel topic model—called biterm correlation knowledge-based topic model (BCK-TM)—to infer latent topics from short texts. Specifically, the proposed model mines biterm correlation knowledge automatically based on recent progress in word embedding, which can represent semantic information of words in a continuous vector space. To incorporate external knowledge, a knowledge incorporation mechanism is designed over the latent topic layer to regularize the topic assignment of each biterm during the topic sampling process. Experimental results on three public benchmark datasets illustrate the superior performance of the proposed approach over several state-of-the-art baseline models.
Heterogeneous Spatial Quality for Omnidirectional Video

Heterogeneous spatial quality in 360-degree videos is characterized by regions of high and low quality appearing in the same video chunk. Encoding quality-varying omnidirectional videos enables bandwidth waste optimization without compromising the quality inside the client's viewport. Heterogeneous spatial quality has been implemented using either the concept of tiling or Facebook's offset projection. In this paper, we study the preparation of heterogeneous 360-degree videos with three main contributions. We propose two novel approaches that prepare heterogeneous quality versions of a 360-degree video based on two video decomposition techniques: the Gaussian pyramid and the Laplace pyramid. We also introduce a spherical filter for omnidirectional videos which allows to further reduce the video bit-rate by exploring the spherical properties of the 360-degree videos. We compare the performance of the proposed three methods to tiling and the offset projection in representative scenarios of heterogeneous spatial quality in 360-degree videos and highlight the key trade-off between bit-rate and video quality to consider when implementing these approaches.
Imitation-Resistant Passive Authentication Interface for Stroke-Based Touch Screen Devices

Today’s widespread use of stroke-based touchscreen devices creates numerous associated security concerns and requires efficient security measures in response. We propose an imitation-resistant passive authentication interface for stroke-based touch screen devices employing classifiers for each individual stroke, which is evaluated with respect to 26 features. For experimental validation, we collect stroke-based touchscreen data from 23 participants containing target and imitation stroke patterns using a photo-matching game in the form of an iOS application. The equal error rate (EER), depicting the rate at which false rejection and false acceptance of target and imitator strokes are equal, is assumed as an indicator of the classification accuracy. Leave-one-out cross-validation was employed to evaluate the datasets based on the mean EER. For each cross-validation, one out of the two target datasets, an imitator dataset, and the remaining 20 imitator datasets were selected as genuine data, imitator test data, and imitator training data, respectively. Our results confirm stroke imitation as a serious threat. Among the 26 stroke features evaluated in terms of their imitation tolerance, the stroke velocity was identified as the most difficult to imitate. Dividing classifiers based on the stroke direction was found to further contribute to classification accuracy.
TYPES OF DIDACTIC MODELS OF THE LEARNING PROCESS

The article substantiates the possibility of increasing the effectiveness of the process of teaching any subject by means of its preliminary modeling. It has been proved that any didactic model consists of three blocks: organizational, which represents the stages of teaching; informative, which includes such links as: teaching objectives, elements of the major subject and components of the major subject content; procedural, which includes such links as: teaching methods, teaching aids, control of teaching outcomes. The form of interconnection of the named links shows that each previous link assumes the next one, and each subsequent link is based on the previous one. Their consistent implementation determines the dynamics of the teaching process. Such model has the properties of a system: INTEGRITY, manifested in the fact that a change in a link or their sequence will violate not only the logic of the teaching process, but will also suspend its implementation; HIERARCHY, manifested in the fact that the presented educational integrity is a structure of a higher level than its components; EMERGENCY, manifested in the fact that a simple sum of links will not lead to the dynamics of the teaching process; it is possible only with the fixed form of their relationship; FUNCTIONALITY, manifested in the fact that each link performs its own function, which proceeds from the function of the previous link, that, in its turn, determines the function of the next link; SYNERGY, manifested in the fact that none of the links can be a subject to bifurcation; otherwise, its destruction will lead to the destruction of the entire teaching process as a whole.
FaceForward – An AI-Based Interactive System for Exploring the Personal Potential

This paper explores the idea of the human body as an interface between self- and outside perception as well as verbal and nonverbal communication. Based on this perspective, the visual appearance can be viewed as a display of personality which indicates certain traits or even hidden potentials to a significant point. It allows the individual as well as other individuals to develop a deeper understanding, acceptance, and even tolerance for each other, if those individual traits and potentials are recognized. The concept behind this is an integrated approach, FaceForward, which is based on an analog face reading system. It is combined with as well as supported by the possibilities of AI within an interactive prototype. It intertwines the historical, but still applied integrated knowledge of human nature by face/body reading with a combination of algorithms and AI-based learning. The main goal is to analyze face and body based on their expression, structures, and, most of all, geometric shapes. Portraits of individuals are selected and pass through two different pipelines. One operates as a pre-processing module. The other for training the AI based on the principles of the face reading system. In the end, the results achieved with the AI approach shall be compared to a survey outcome of self- and outside perception based on psychologic concepts.
A PYNQ Evaluation Platform for FPGA Architectures of the Line Hough Transform

The Line Hough Transform (LHT) is an effective line detection algorithm for digital images. To meet real-time requirements, Field Programmable Gate Arrays (FPGAs) are often chosen to accelerate the LHT. However, many LHT architectures select different design parameters and discretisation steps for the Hough Parameter Space (HPS). The work presented in this paper describes a novel evaluation platform for FPGA architectures of the LHT. Our system is named the Hough Evaluation Platform (HEP) and can be used to visualise and inspect the HPS produced from LHT architectures that use different design parameters. Architectures are compared by evaluating the HPS using a unique measurement named the Peak to Mean Vote Ratio (PMVR). Our system employs the PYNQ framework on a Xilinx Zynq MPSoC device for the visualisation of the HPS and also determines the processing time of a given LHT architecture. The HEP has been implemented on a XCZU7EV-2e device and can operate up to a target frequency of 250 MHz.
Construction of English spoken language system based on machine learning algorithm and natural language recognition

English speech recognition system is affected by a variety of interference factors. Associating the algorithm with the support of modern computer technology can increase the model effect of speech recognition system. Based on the study of the current mainstream controlled natural language thesaurus, this paper proposes a controlled natural language vocabulary classification type. Moreover, this paper defines the domain thesaurus according to the WordNet knowledge description framework, and uses WordNet’s synonym, antisense, upper and lower, etc. In this way, the controlled natural language system can use the semantic relationship of WordNet to identify the words of the non-domain thesaurus input by the user and map the non-domain definition words to the words in the domain thesaurus, thereby improving the ease of use of controlled natural language systems. In addition, this paper designed a controlled experiment to analyze the performance of this system. The research results show that the model constructed in this paper has certain significant effects.
Sustainable Interactive Design of Cross-cultural Online Maker Space

Under the background of knowledge society, Innovation 2.0 mode is formed. As a new innovation mode, mass innovation expands the concept of maker space. With the development of globalization, the concept of community of shared future of human beings appears on the world stage. Based on the theoretical support of cultural commonality and civilization integration, this paper proposes the cross-cultural online maker space, through cultural diversity to stimulate innovation, to achieve a virtuous circle of maker space and social civilization. This paper systematically designs cross-cultural online maker space, and studies the design strategy of cross-cultural system, adopting the method of sustainable interaction design. In addition, this paper explores the impact of 5G, blockchain and other new technologies on the development of maker space, so as to ensure its feasibility and sustainability.
Investigation on the Fusion of Multi-modal and Multi-person Features in RNNs for Detecting the Functional Roles of Group Discussion Participants

More and more companies are putting emphasis on communication skill in the recruitment of their employees and adopt group discussion as part of their recruitment interview. In our ongoing project, we aim to develop a training system that can provide advices to its users in improving the perception of their communication skill during group discussion. In order to realize this goal, a conceptual unit of communicational behaviors and a template of communication style are required. We propose the use of functional roles of the participants in group discussions as this unit. In order to incorporate the use of functional roles for improving the perception of participants' communication skill, the first task is automatic detection of the participants' functional roles in real-time. We previously proposed a SVM based model for this task but the results were only moderate. We expect including temporal characteristics, frame-wise interaction of modalities, and inter-person interaction can improve the classification accuracy and explored the use of RNN based networks to see the effectiveness of these factors.
Competency Development Through Experiential Training: Mapping Scenarios with Assessments

A training ecosystem leverages multiple complementary instructional resources to target competency and skill development. In this paper, we introduce work that is integrating assessment functions in the Generalized Intelligent Framework for Tutoring (GIFT) with core components in the Total Learning Architecture (TLA) to support persistent performance tracking and reporting in dynamic simulation-based environments. This capability creates a data strategy to translate multi-modal raw data into contextualized statements of performance for use in a long-term readiness monitoring strategy. In this paper we discuss the integration activities, what this new extended architecture supports, and provide a high-level use case associated with infantry squad level competency sets.