Reviewerly/exHarmony huggingface dataset:
Video Super-Resolution Based on Multiple Networks Merging

Video or image super-resolution technology is designed to recovery a high-resolution image from a low-resolution video or image. In recent years, deep neural networks have developed rapidly and have been applied in many digtal image processing tasks. In this paper, we choose an optical flow network to effectively exploit temporal relation within multiple consecutive video frames. In addition, we propose a weight distribution network which gives weight images of different high-resolution images obtained by various super-resolution network methods. This architecture combines advantages of different methods and provides a more accurate high-resolution image. We build a dataset with high-definition video, and use this dataset to train and test our networks. We compare our algorithm with other super-resolution methods and show that it performs a state-of-the-art results.
Counting of Teams in First-Order Team Logics

We study descriptive complexity of counting complexity classes in the range from #P to #*NP. A corollary of Fagin's characterization of NP by existential second-order logic is that #P can be logically described as the class of functions counting satisfying assignments to free relation variables in first-order formulae. In this paper we extend this study to classes beyond #P and extensions of first-order logic with team semantics. These team-based logics are closely related to existential second-order logic and its fragments, hence our results also shed light on the complexity of counting for extensions of first-order logic in Tarski's semantics. Our results show that the class #*NP can be logically characterized by independence logic and existential second-order logic, whereas dependence logic and inclusion logic give rise to subclasses of #*NP and #P, respectively. We also study the function class generated by inclusion logic and relate it to the complexity class TotP, which is a subclass of #P. Our main technical result shows that the problem of counting satisfying assignments for monotone Boolean Sigma_1-formulae is #*NP-complete with respect to Turing reductions as well as complete for the function class generated by dependence logic with respect to first-order reductions.
STEM IN HIGHER EDUCATION: THE USE OF AN ADVANCED COMPUTING ENVIRONMENT TO DEVELOP FUNDAMENTAL SKILLS FOR UNIVERSITY CAREER AND THE WORLD OF WORK

STEM IN HIGHER EDUCATION: THE USE OF AN ADVANCED COMPUTING ENVIRONMENT TO DEVELOP FUNDAMENTAL SKILLS FOR UNIVERSITY CAREER AND THE WORLD OF WORK
OAuth 2.0 Integrity Verification for Authorization Requests (IVAR)

This document describes a mechanism for the integrity protection ofOAuth 2.0 authorization requests.
Doing Digital Scholarship with DLS: The Motivations

Digital Library Services (DLS) is running a monthly series of workshops on how to better manage yourdata and your research process. In doing any form of research nowadays we haveto interact with a multitude of digital spaces. This talk outlines digitalprocesses and tools that can increase efficiencies throughout a researchproject, with particular reference to the data life-cycle, from planning to publishing. We also look at collaborative tools for managing, analysing, mapping and visualizing research data. All thoseinvolved in research and research support are welcome. The vision and mission of Digital Library Services (DLS) at UCT Libraries is toprovide open, online access to primary resources for teaching, learning andresearch at the University of Cape Town (UCT) through digitisation, digitalscholarship, data curation and preservation services. We subscribe to andsupport the practice ofOpen Science.
VISION BASED INTERACTION GAME FOR REVISING THE PERIODIC TABLE

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 9376-9382ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.2326Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
FIT FOR THE FUTURE - MODERNISATION OF MASTER CURRICULUM IN ICT FOR ENHANCING STUDENT EMPLOYABILITY IN BELARUS

FIT FOR THE FUTURE - MODERNISATION OF MASTER CURRICULUM IN ICT FOR ENHANCING STUDENT EMPLOYABILITY IN BELARUS
CREATING TEACHING AIDS AIMED AT DEVELOPING COMPUTATIONAL THINKING

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 1515-1521ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0453Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
IMMERSIVE DIDACTIC APPROACH: TEACHING WITH VIRTUAL REALITY AS INTEGRATED LEARNING ENVIRONMENTS

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 9343-9349ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.2314Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
예비 생물교사의 마이크로티칭에 나타난 발문 유형과 발문-대답 계열

The purpose of this study was to analyze the question types and question-answer series that presented in pre-service biology teachers'' microteaching. The types of questions were divided into questions to confirm information, questions to form understanding, and questions to promote reflection. The question-answer series were divided into independence relation, parallel relation, insertion relation and reconstruction relation. The subjects of this study were 14 pre-service biology teachers. As a result of analyzing the types of questions used by pre-service biology teachers, the questions that provided information were most frequently used. As a result of analyzing question-answer series, independence relation was most utilized. And next, parallel relation, reconstruction relation, insertion relation was utilized. These results showed that pre-service biology teachers are very limited in their ability to use the questions. Therefore, the result of this study showed that it is necessary to develop an educational program that can improve the questioning ability of pre-service biology teachers.
Segmenting Potentially Cancerous Areas in Prostate Biopsies using Semi-Automatically Annotated Data

Gleason grading specified in ISUP 2014 is the clinical standard in staging prostate cancer and the most important part of the treatment decision. However, the grading is subjective and suffers from high intra and inter-user variability. To improve the consistency and objectivity in the grading, we introduced glandular tissue WithOut Basal cells (WOB) as the ground truth. The presence of basal cells is the most accepted biomarker for benign glandular tissue and the absence of basal cells is a strong indicator of acinar prostatic adenocarcinoma, the most common form of prostate cancer. Glandular tissue can objectively be assessed as WOB or not WOB by using specific immunostaining for glandular tissue (Cytokeratin 8/18) and for basal cells (Cytokeratin 5/6 + p63). Even more, WOB allowed us to develop a semi-automated data generation pipeline to speed up the tremendously time consuming and expensive process of annotating whole slide images by pathologists. We generated 295 prostatectomy images exhaustively annotated with WOB. Then we used our Deep Learning Framework, which achieved the $2^{nd}$ best reported score in Camelyon17 Challenge, to train networks for segmenting WOB in needle biopsies. Evaluation of the model on 63 needle biopsies showed promising results which were improved further by finetuning the model on 118 biopsies annotated with WOB, achieving F1-score of 0.80 and Precision-Recall AUC of 0.89 at the pixel-level. Then we compared the performance of the model against 17 biopsies annotated independently by 3 pathologists using only H\&E staining. The comparison demonstrated that the model performed on a par with the pathologists. Finally, the model detected and accurately outlined existing WOB areas in two biopsies incorrectly annotated as totally WOB-free biopsies by three pathologists and in one biopsy by two pathologists.
Efficient characterization of correlated SPAM errors

State preparation and measurement (SPAM) errors limit the performance of many gate-based quantum computing architecures, but are partly correctable after a calibration step that requires, for an exact implementation on a register of $n$ qubits, $2^n$ additional characterization experiments, as well as classical post-processing. Here we introduce an approximate but efficient method for SPAM error characterization requiring the {\it classical} processing of $2^n \! \times 2^n$ real matrices, but only $O(n^2)$ measurements. The technique assumes that multi-qubit measurement errors are dominated by pair correlations, which are estimated with $n(n-1)k/2$ two-qubit experiments, where $k$ is a parameter related to the accuracy. We demonstrate the technique on the IBM and Rigetti online superconducting quantum computers, allowing comparison of their SPAM errors in both magnitude and degree of correlation. We also study the correlations as a function of the register's geometric layout. We find that the pair-correlation model is fairly accurate on linear arrays of superconducting qubits. However qubits arranged in more closely spaced two-dimensional geometries exhibit significant higher-order (such as 3-qubit) SPAM error correlations.
The Observer Experiment: A View of the Dynamics of Multimodal Interaction

Here we present and also apply the “observer gaze” methodology in order to study the structural organization of multimodal, face-to-face conversations. Tracking the gaze of a third party observer can provide an online and implicit method for investigating the dynamics of interactions and the relevant features that capture the observer’s attention according to the amount of information the observer has available. The way an outsider visually perceives the interactional exchanges may also suggest a better modeling of human-human communication for human-machine communication system. With these goals, ten observers participated in the present study, all being native speakers of Persian. The observers watched a short clip of a dyadic, spontaneous conversation in Persian. Using an eye tracker, the observers’ gaze was recorded in two different watching situations, namely: audio-visual, and visual-only. Afterwards, using ELAN, the observers’ gaze data were temporally aligned with verbal and nonverbal behavior of the interactants (such as head movements, hand gestures, body shift, facial expressions and turn-taking). First, the observers’ visual attention, measured as the amount of fixation time on the speaker and listener, was described across conditions. Second, the observers’ gaze was analyzed in presence of turn-transitions and we showed that they were able to a large extent to anticipate turns and also follow them depending on the conditions. In summary, the observers’ gazing behavior was affected by the conditions.
APPROPRIATE LEARNING APPROACHES AND TECHNOLOGIES FOR DISASTER PREPARATION OF THE POPULATION

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 5123-5128ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.1266Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
The Systems Approach to Change and the Agile Software Development Context.

There is a diversity of models explaining organizational culture and how these complex aspects can be addressed in connection to organizational change efforts. This workshop paper claims that models already exist for dealing with the cultural change that an agile transition is in the software engineering context. Instead of realizing this again through agile success stories, and thus reinventing the wheel, it is argued that the research in the software engineering field should build on these models instead and investigate how/if they differ. Practitioners already work as the change agents described in other fields and they should get recognition through the presence and integration of these models in the software engineering process research.
$$\mathtt{SpectralLeader}$$ : Online Spectral Learning for Single Topic Models

We study the problem of learning a latent variable model online from a stream of data. Latent variable models are popular because they can explain observed data through unobserved concepts. These models have traditionally been studied in the offline setting. In the online setting, online expectation maximization (EM) is arguably the most popular approach for learning latent variable models. Although online EM is computationally efficient, it typically converges to a local optimum. In this work, we develop a new online learning algorithm for latent variable models, which we call $$\mathtt{SpectralLeader}$$ . $$\mathtt{SpectralLeader}$$ converges to the global optimum, and we derive a sublinear upper bound on its n-step regret in a single topic model. In both synthetic and real-world experiments, we show that $$\mathtt{SpectralLeader}$$ performs similarly to or better than online EM with tuned hyper-parameters.
Brenda Starr at SemEval-2019 Task 4: Hyperpartisan News Detection

In the effort to tackle the challenge of Hyperpartisan News Detection, i.e., the task of deciding whether a news article is biased towards one party, faction, cause, or person, we experimented with two systems: i) a standard supervised learning approach using superficial text and bag-of-words features from the article title and body, and ii) a deep learning system comprising a four-layer convolutional neural network and max-pooling layers after the embedding layer, feeding the consolidated features to a bi-directional recurrent neural network. We achieved an F-score of 0.712 with our best approach, which corresponds to the mid-range of performance levels in the leaderboard.
Simulating Universal Gaussian Circuits with Linear Optics

We develop a universal procedure for simulating sampling from arbitrary non-linear photonic Gaussian circuit with passive linear optics only, provided two-mode squeezed vacuum states are available as a prior resource.
Intelligent Tag Prediction Algorithms for Acupuncture Experts

How to further improve clinical efficacy of acupuncture, extend its application range is a key issue in the research and promotion of acupuncture. Famous acupuncturists represent the highest academic level and treatment ability, and have an important influence on development of acupuncture and rehabilitation of patients. Therefore, how to accurately find the acupuncturist is a difficult problem for both patients and peer doctors. At the same time, Internet is also full of a large number of false information, how to accurately analyze the real acupuncturist from these information is the key issue. We can automatically acquire these tags by using information collection technology, and select acupuncture experts from them by combining artificial intelligence. However, tags of social network users is sparse, only a small number of users have tags, and the number of tags is limited. Most users only publish articles and pay attention to other interested users and blogs. They do not tag themselves. There are problems of no tags or less tags, which make it more difficult to find acupuncturists. For untagged users, we can consider predicting tags from their social relationships. In this paper, we design an intelligent tag prediction algorithms for acupuncture experts, which first predicts intimate users of users, and then predicts the users' tags through intimate users' tags. Firstly, possible close users are selected as candidates through cosine similarity. If the user doesn't have an object of interest, then replace it with his fans. Subsequently, user tags are predicted according to the tags of the target audience or fans. Finally, the effectiveness of ITPAE is verified by simulation experiments.
Investigating the General Medical Students' Attitudes and Way of Using Smartphones to Learn Their Professional and Educational Issues

Introduction: Due to the popularity of smartphones and given the fact that smartphone-based learning methods are not widely used in the official curriculum of universities, this study was conducted with the aim of evaluating the general medical students' attitudes and way of using smartphones to learn the educational and professional issues.Materials and Methods: The population of this descriptive study included all of the general medical students. Sampling was performed by simple random sample. A total of 100 students completed these questionnaires. The research tool was a researcher-made questionnaire, which its validity and reliability have been confirmed in two studies among Australian and Iranian dentistry students. For the analysis of the data of the present study, frequency, mean, percentage, Mann-Whitney test and correlation coefficient Spearman in SPSS 22 software were used.Results: 57% of the students were female and 43% were male. The results of this study showed that medical students used their smartphone facilities for their educational and professional purposes. In this regard, the search of web pages related to the content of the curriculum ranked first (90%), followed by installation of medical-related applications on smartphones (89%). In addition, residential homes, different points of the faculty, and on the route such as in the bus, respectively, were the most commonly used places for students to use smartphones. The results also showed that as students use their phone for more general purposes, the student's desire to learn with the smartphone increases significantly (0.107). Additionally, as the age of people increases, their ability and desire to use it for general and educational purposes through smartphones is reduced significantly (-0.141).Discussion and Conclusion: Based on the results of this research, it seems necessary to use the capabilities of smartphones to learn medical and professional issues and to improve the medical profession, especially in educational and healthcare settings. It is also necessary to use the smartphones in official university curriculum. However, its disadvantages and threats should not be ignored.
Decohering power of thermal fluctuating electromagnetic field with a boundary

In this paper, we analyze the decohering power behaviors for an atom immersed in a thermal bath of fluctuating electromagnetic field in the presence of a perfectly reflecting plane boundary. Firstly, we analytically solve the master equation that governs the system evolution. Then, we discuss the behaviors of decohering power for an atom affected by thermal fluctuating electromagnetic field. It is found that the behaviors of decohering power are dependent on the field temperature, atomic position and polarization. Decohering power fluctuates to relatively stable values with the increasing atom’s distance from the boundary, which suggests a possible way of detecting the vacuum fluctuating and boundary effect. Additional conditions on the electromagnetic field give one more freedom to manipulate the variations of decohering power. Decohering power variations can efficiently reflect the behaviors of quantum coherence affected by electromagnetic vacuum fluctuation, and it is shown that quantum coherence can be effectively enhanced with the presence of a reflecting boundary.
The Diagnosis and Design of Cultivation Education in the Writing Area : Focusing on Chosun University

The skills to guarantee status and rights of human beings to enjoy as human beings in relationships are the most desperately needed ones for college students who are about to enter society. The era of the fourth industrial revolution is rather signaling a break in human relations. Active communication education that transcends alienation and exclusion is an alternative education that overcomes the breakage of human relations. Therefore, it is time to diagnose and design writing education as communication education at this point.BR The Korea Institute of Curriculum and Training classifies writing education as a basic education area for cultural education. However, almost all universities offer writing education without distinction between basic and liberal education. The same is true of Chosun University
EDUCATIONAL SOFTWARE FOR THE INTERACTIVE STUDY OF DYNAMIC ABSORBERS

A. Craifaleanu1, C. Dragomirescu1, I.G. Craifaleanu2 1University "Politehnica" of Bucharest (ROMANIA) 2Technical University of Civil Engineering Bucharest and National R&D Institute URBAN-INCERC (ROMANIA)
Browsing Health: Information Extraction to Support New Interfaces for Accessing Medical Evidence

Standard paradigms for search do not work well in the medical context. Typical information needs, such as retrieving a full list of medical interventions for a given condition, or finding the reported efficacy of a particular treatment with respect to a specific outcome of interest cannot be straightforwardly posed in typical text-box search. Instead, we propose faceted-search in which a user specifies a condition and then can browse treatments and outcomes that have been evaluated. Choosing from these, they can access randomized control trials (RCTs) describing individual studies. Realizing such a view of the medical evidence requires information extraction techniques to identify the population, interventions, and outcome measures in an RCT. Patients, health practitioners, and biomedical librarians all stand to benefit from such innovation in search of medical evidence. We present an initial prototype of such an interface applied to pre-registered clinical studies. We also discuss pilot studies into the applicability of information extraction methods to allow for similar access to all published trial results.
Every metric space is separable in function realizability

We first show that in the function realizability topos every metric space isseparable, and every object with decidable equality is countable. Moregenerally, working with synthetic topology, every $T_0$-space is separable andevery discrete space is countable. It follows that intuitionistic logic doesnot show the existence of a non-separable metric space, or an uncountable setwith decidable equality, even if we assume principles that are validated byfunction realizability, such as Dependent and Function choice, Markov'sprinciple, and Brouwer's continuity and fan principles.
Identifying causal relations in legal documents with dependency syntactic analysis

This article describes a method for enriching a dependency-based parser with causal connectors. Our specific objective is to identify causal relationships between elementary discourse units in Spanish legal texts. For this purpose, the approach we follow is to search for specific discourse connectives which are taken as causal dependencies relating an effect event (head) with a verbal or nominal cause (dependent). As a result, we turn a specific syntactic parser into a discourse parser aimed at recognizing causal structures.
Quick Response Encoding of Human Facial Images for Identity Fraud Detection

Advancements in printing and scanning technology enable fraudsters to tamper with identity documents such as identity cards, drivers’ licenses, admit cards, examination hall tickets and academic transcripts. Several security features are incorporated in important identity documents to counter forgeries and verify genuineness, but these features are often lost in printed versions of the documents. At this time, a satisfactory method is not available for authenticating a person’s facial image (photograph) in a printed version of a document. Typically, an official is required to check the person’s image against an image stored in an online verification database, which renders the problem even more challenging. This chapter presents an automated, low-cost and efficient method for addressing the problem. The method employs printed quick response codes corresponding to low-resolution facial images to authenticate the original and printed versions of identity documents.