Reviewerly/exHarmony huggingface dataset:
UML Consistency Rules: a Case Study with Open-Source UML Models.

UML models are standard artifacts used by software engineers for designing software. As software is designed, different UML diagram types (e.g., class diagrams and sequence diagrams) are produced by software designers. Since the various UML diagram types describe different aspects of a software system, they are not independent but strongly depend on each other, hence they must be consistent. Inconsistencies cause faults in thefi nal software systems. It is, therefore, paramount that they get detected, analyzed, andfi xed. Consistency rules are a useful tool proposed in the literature to detect inconsistencies. They categorize constraints that help in identifying inconsistencies when violated. This case study aims at collecting and analyzing UML models with OCL consistency rules proposed in the literature and at promoting the development of a reference benchmark that can be reused by the (FM-)research community. We collected 33 UML consistency rules and 206 different UML diagrams contained in 34 open-source UML models presented in the literature. We propose an FM-based encoding of the consistency rules in OCL. This encoding allows analyzing whether the consistency rules are satisfied or violated within the 34 UML models. To assess the proposed benchmark, we analyzed how the UML models, consistency rules, diagram types contained in the benchmark help in assessing the consistency of UML models, and the consistency of diagrams across the different software development phases. Our results show that the considered UML models and consistency rules allowed identifying 2731 inconsistencies and that those inconsistencies refer to different software development phases. We concluded that the considered UML models and consistency rules could be considered as an initial benchmark that can be further extended by the research community.
Models for Risk assessment of Mobile applications

Mobile applications are software that extend the functionality of our smartphones by connecting us with friends and a wide range of other services. Android, which is an operating system based on th ...
Security Risk Analysis based on Data Criticality

Nowadays, security risk assessment has become an integral part of network security as everyday life has become interconnected with and dependent on computer networks. There are various types of dat ...
CT Tracing Algorithm Based on Optical Flow Field

Currently, there have already been plenty of visual tracing algorithms that were put forward in succession, but in the field of ship tracking, it has still been faced with challenge. The article has mainly solved problem brought by variation dis-turbance of ship tracking light and contrast in CCTV system. On the basis of compressing tracking frame, the article has put forward a kind of CT ship tracking algorithm based on optical flow field improvement. The article has reduced the alternating sample by above 50% to obtain faster tracking performance by utilizing the CT tracing solving scheme improved by optical flow field. At the same time, the article has improved the robustness and accuracy of tracking algorithm under illumination variation disturbance. The article has conducted verification and analysis on plenty of shipping tracking collection, and the algorithm of this article can realize more accurate tracking to the ship target.
Lip Biometric Authentication Using Viola-Jones and Appearance Based Model (AAM) System

The lip biometric system focuses on the uniqueness of the parameters of the lips as a useful feature to distinguish similar-looking people. Data gathering includes five identical twins, ten similar faces, and ten dissimilar faces of still face-front images of subjects with neutral expressions were used to examine the efficiency and performance of the system. Different lighting conditions measured in flux under various distances have been characterized. The system employs the Viola-Jones algorithm for face detection and the Active Appearance Model (AAM) for lip extraction. An 87.5% accuracy resulted in using lips for human identity.
Adaptive Neural Layer for Globally Filtered Segmentation.

This study is motivated by typical images taken during ultrasonic examinations in the clinic. Their grainy appearance, low resolution, and poor contrast demand an eye of a very qualified expert to discern targets and to spot pathologies. Training a segmentation model on such data is frequently accompanied by excessive pre-processing and image adjustments, with an accumulation of the localization error emerging due to the digital post-filtering artifacts and due to the annotation uncertainty. Each patient case generally requires an individually tuned frequency filter to obtain optimal image contrast and to optimize the segmentation quality. Thus, we aspired to invent an adaptive global frequency-filtering neural layer to learn optimal frequency filter for each image together with the weights of the segmentation network itself. Specifically, our model receives the source image in the spatial domain, automatically selects the necessary frequencies from the frequency domain, and transmits the inverse-transform image to the convolutional neural network for concurrent segmentation. In our experiments, such learnable filters boosted typical U-Net segmentation performance by 10% and made the training of other popular models (DenseNet and ResNet) almost twice faster. In our experiments, this trait holds both for two public datasets with ultrasonic images (breast and nerves), and for natural images (Caltech birds).
Lumina – An Exploration of How Interactive Lights Can Support Mindfulness

This thesis project presents a research through design process that has aimed to explore how we can design interactive technologies that can support mindfulness practices in beginners. This has bee ...
SSHFD: Single Shot Human Fall Detection with Occluded Joints Resilience

Falling can have fatal consequences for elderly people especially if the fallen person is unable to call for help due to loss of consciousness or any injury. Automatic fall detection systems can assist through prompt fall alarms and by minimizing the fear of falling when living independently at home. Existing vision-based fall detection systems lack generalization to unseen environments due to challenges such as variations in physical appearances, different camera viewpoints, occlusions, and background clutter. In this paper, we explore ways to overcome the above challenges and present Single Shot Human Fall Detector (SSHFD), a deep learning based framework for automatic fall detection from a single image. This is achieved through two key innovations. First, we present a human pose based fall representation which is invariant to appearance characteristics. Second, we present neural network models for 3d pose estimation and fall recognition which are resilient to missing joints due to occluded body parts. Experiments on public fall datasets show that our framework successfully transfers knowledge of 3d pose estimation and fall recognition learnt purely from synthetic data to unseen real-world data, showcasing its generalization capability for accurate fall detection in real-world scenarios.
Characters, Gauss Sums, and the DFT

One of the major problems often encountered in working with finite fields is the transition between their additive and multiplicative structures. We have seen a concrete example of this type of problem when we studied the arithmetics in finite fields in Chap. 8. Depending on the choice of representation, either addition (in some basis representation) or multiplication (using Zech logarithms) is trivial, while the other operation is not at all easy to perform. The same type of problem arises also in theoretical investigations concerning both the additive and multiplicative structure simultaneously, for instance, when proving the existence of primitive normal bases or that of primitive elements with a prescribed value of the trace (into a specified subfield); these two problems will the topic of the final two chapters. Such questions often require the use of tools from Representation Theory which we did not introduce up to now, that is, characters and character sums and, in particular, Gauss sums. These tools will be presented in the current chapter, where we first consider characters of finite abelian groups in general and then specialize to the case of finite fields and introduce the basic properties of Gauss sums. We then give a few interesting applications of the quadratic character; in particular, we shall prove the law of quadratic reciprocity and consider solutions of quadratic equations in several variables over finite fields with odd characteristic. Following this, we shall prove three more advanced identities for Gauss sums; we will also obtain an interesting connection to the eigenvalues of the matrix of the Discrete Fourier Transform defined in Sect. 7.4. Finally, we extend the DFT to abelian groups in general and present some applications to abelian difference sets and periodic sequences.
SAT and Interactions (Dagstuhl Seminar 20061)

This report documents the program and the outcomes of Dagstuhl Seminar 20061 and Interactions. The seminar brought together theoreticians and practitioners from the areas of proof complexity and proof theory, SAT and QBF solving, MaxSAT, and modal logics, who discussed recent developments in their fields and embarked on an interdisciplinary exchange of ideas and techniques between these neighbouring subfields of SAT.
ОРГАНІЗАЦІЯ ПРАКТИЧНОЇ ПІДГОТОВКИ МАЙБУТНІХ УЧИТЕЛІВ ПОЧАТКОВОЇ ШКОЛИ У КОНТЕКСТІ ФОРМУВАННЯ КУЛЬТУРОЛОГІЧНОЇ КОМПЕТЕНТНОСТІ

The author examines the types and duration of pedagogical practices in the UK, characterizes the main objectives of pedagogical practice in the United States in the context of the national objective to train an “effective multicultural teacher”. Based on the analysis of educational and professional programs of higher education institutions of Ukraine, the author characterizes such types of pedagogical practice of future primary school teachers as: the extra-curricular and out-of-school educational practice, the pedagogical practice in children's recreation camps, the educational and nurturing practice in the first grade, the teaching and educational practice.
The Study of Multi-Interactive Teaching Mode in College English Based on Intelligent Terminal

With the mode of teaching and learning in colleges and universities gradually changes to themulti-dimensional model, pluralism, internationalization and modernization have become the inevitabletrends of the future development of Chinese college English teaching. Based on the current situation ofmulticultural education in China, the thesis puts forward some ideas on the construction of college Englishteaching model from three aspects. First, correct culture teaching value is particularly important. Forexample, understanding and innovation of multi culture influence the model construction of college Englishteaching under the background of multi culture. Second, clear teaching goals, teaching channels and Englishclassroom group are good for the diversification of teaching strategies, which is also an important content ofcollege English teaching model. Thirdly, we need to establish a scientific cultural evaluation mechanism,enrich cultural connotation under the perspective of multicultural development, and expand ways for collegeEnglish teaching model. The construction of these three aspects of English teaching in colleges anduniversities is of reference value for Chinese English education.
Operation of semiconductor telecom entangled photon sources over installed fiber networks

We show deployment of a tunable telecom entangled photon source based on semiconductor quantum dots in an installed fiber network. We further report about network integration of a pulsed device operating at GHz clock rates.
Mode Switching from a Security Perspective: First Findings of a Systematic Literature Review.

With increased interoperability of cyber-physical systems (CPSs), security becomes increasingly critical for many of these systems. We know mode switching from domains like aviation and automotive, and we imagine to use this mechanism for the development of resilient systems that continue to function correctly even if under malicious attack. If vulnerabilities are detected or even known, modes can be switched to reduce the attack surface and to minimize attackers’ range of activity. We propose to engineer CPSs with multi-modal software architectures to overcome the interval between the time when zero-day vulnerabilities become known and the time when corresponding updates become available. Thus, affected companies, operators and people will be able to protect themselves and their customers without having to wait for security updates. This paper presents first findings of a systematic literature review (SLR) on mode switching from a security perspective.
Iterative Channel Estimation for Discrete Denoising under Channel Uncertainty

We propose a novel iterative channel estimation (ICE) algorithm that essentially removes the critical known noisy channel assumption for universal discrete denoising problem. Our algorithm is based on Neural DUDE (N-DUDE), a recently proposed neural network-based discrete denoiser, and it estimates the channel transition matrix as well as the neural network parameters in an alternating manner until convergence. While we do not make any probabilistic assumption on the underlying clean data, our ICE resembles Expectation-Maximization (EM) with variational approximation, and it takes advantage of the property of N-DUDE being locally robust around the true channel. With extensive experiments on several radically different types of data, we show that the ICE equipped N-DUDE (dubbed as ICE-N-DUDE) can perform \emph{universally} well regardless of the uncertainties in both the channel and the clean source. Moreover, we show ICE-N-DUDE becomes extremely robust to its hyperparameters and significantly outperforms the strong baseline that can deal with the channel uncertainties for denoising, the widely used Baum-Welch (BW) algorithm for hidden Markov models (HMM).
Semantic Segmentation of Historical Document Images Using Recurrent Neural Networks

Background. This thesis focuses on the task of historical document semantic segmentation with recurrent neural networks. Document semantic segmentation involves the segmentation of a page into diff ...
한국어 어휘 교육 방안 연구의 동향 분석 : 학위논문을 중심으로

The purpose of this study was to research what direction the Korean vocabulary education had to be steered by identifying the trends of research on Korean vocabulary education. Initially, I searched the RISS with the keyword “Korean vocabulary education” and organized the relevant data by year, learner characteristics, and vocabulary type etc. Through the data analysis, I was able to identify several trends. The trend by could be divided into three different time periods depending on the trend of study. Although research on learner proficiency was evenly represented, the studies on the nationality of target learners were mostly represented by Chinese while studies on the types of learners were mostly represented by married foreign immigrant women. Overall, Traditional Chinese (Hanja) contributed the largest proportion of research and I incorporated a variety of research methods such as teaching material analysis, experimental research and surveys in my research. As for the measures for teaching, research on teaching methods were the most popular. Through these results, I propose that more research needs to be done based on the geography of language, proficiency levels, special purposes, and various languages while the measures for teaching be objectively evaluated through this research.
Von Humboldt principles and reality of post-Soviet universities

It has been shown that unsatisfactory state of post-Soviet higher education is largely connected with the fact that the fundamental principles of von Humboldt, which ensured the formation of classical university education at the end of the 19th century, are no longer realized in modern conditions. First of all, due to the fact of widespread higher education, it is only possible to speak formally about interconnection between academic freedom, education and science within the walls of the overwhelming majority of post-Soviet universities. Over the past 150 years, the workload of professors has increased&nbsp;on average from 4 to 30 hours per week, which excludes the realization of academic freedom. This fact reflects systemic crisis in higher education of industrial era and significant difficulties in transition to post-industrial university. It has been shown that to overcome the prevailing negative trends, first of all, it requires the formation of adequate ideas of post-industrial higher education economics as well as systemic counteraction to transitional diseases, which include the flourishing of pseudoscience (especially in areas related to telecommunication technologies), as well as corruption, for which the pseudo-science is working as breeding ground. Key words: Pseudoscience, Humboldt principles, university education, telecommunication technologies, study load, post-industrial high school.
Multi - Terrain Drone with Human Detection System

In any kind of calamity, the search and rescue teams are first to arrive and are a crucial part of disaster management. Currently, a widespread disaster can slow down a rescue team putting more time and resources into the process which costs lives that are affected by the disaster. The proposed project provides a proof of concept that will enable the search and rescue team to better manage their resources and conduct rescue operations effectively. Our drone system is designed to be deployed during search and rescue operations and searches for people that are confined to a location. The drone sent back these locations which can be used to effectively deploy the rescue team. This helps in minimizing the time for actually finding the affected people during the rescue process and directing the rescue team where they are required.
The initial Data Management Plan for PalMod II - FAIR simulation and paleo data from the Last Interglacial to the Anthropocene

&amp;lt;p&amp;gt;The project PalMod II is the second phase of Germany&amp;amp;#8217;s national paleoclimate modelling initiative (www.palmod.de) whose aim is to model the transient climate evolution from the last interglacial to the anthropocene with state of the art earth system models. The second phase more precisely wants to perform simulations for the last glacial inception, the marine isotope stage 3, and the last deglaciation. It further plans to compile paleo-observational proxy data over the full glacial cycle from about 130,000 years before present until today. Models of differing complexity (fully-coupled earth system models and models of intermediate complexity) will be used to assess the scientific questions posed in PalMod II. Model output will be combined with the compiled paleo-proxy data for validation purposes. The sheer data amount in excess of several petabytes and different data handling practices of the participating communities require dedicated management of the data workflow both in- and outside of the immediate PalMod community.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The PalMod II data management takes place in close collaboration between data management specialists and the scientists. The objectives include the standardisation of each simulation and proxy dataset, the facilitation of data sharing and data reuse between work packages, the access channels for external collaborators, and the long-term preservation of the data. The data management follows the concept of the &amp;quot;Active Data Management Plan&amp;quot;, which foresees a continuous development of the data management plan (DMP), starting with an initial basic version. The DMP covers the entire life cycle of the research data generated in the project, from generation and analysis to data publication and archiving. This includes aspects such as data formats, metadata standards and data usage licenses. Ownership and responsibilities for simulation and paleo data sets as well as the input data during and after the end of the project will also be considered.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This contribution will present the initial DMP for PalMod II. It will describe the amount of data produced in the project, highlight how the above mentioned aspects will be dealt with, and present how the project aims to ensure the Findability, Accessibility, Interoperability, and Reusability, i.e. the FAIR data principles, of simulation output, post-processed model data, and paleo-proxy data from PalMod II.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;* This contribution presents results of the full PalMod II initiative, the authors present them on behalf of the initiative.&amp;lt;/p&amp;gt;
Architecture for Augmented Reality Guidance Applications Using DICOM-RTV

The recently published DICOM-Real Time Video (DICOM-RTV) standard allows real-time synchronization of transported video and medical metadata flows. In order to demonstrate the advantages of this synchronization by design, a demonstration of a DICOM-RTV Augmented Reality (AR) based solution is proposed. This solution consists in facilitating the surgeon's gesture by monitoring the positioning of the biopsy needle under ultrasound guidance and constructing virtual and augmented reality views of the needle's trajectory. In this paper, the platform architecture and the obtained results are presented. Furthermore, a comparison between our proposed solution and a setup that do not use DICOM-RTV is provided in order to show the difference in term of precision, synchronization and delay. The obtained results validate the contribution of real-time synchronization to improve the accuracy of surgical gesture aid applications such as AR.
Argumentative paragraphs identification with markers categories

The argumentation in theses is necessary to develop the ideas and convince the reader of the presented statements. However, among university students, there is a deficiency in their ability to argue, which is attended by teachers through the review process. In this article, we present a model for argumentative paragraph detection in sections such as the problem statement, justification, and conclusions. The classification task is performed using machine learning algorithms using five categories of argumentative markers. We present the sets of word patterns for each of the following categories: justification, explanation, deduction, refutation and conditional. Experiments were carried out to evaluate the argumentative paragraph identification reaching encouraging results.
Fast physical random bit generation based on an optoelectronic delay loop pumped by a semiconductor laser under a modulated optical feedback

In this work, we propose and experimentally demonstrate a scheme for generating fast physical random bits (PRBs). For such a scheme, the chaotic signal output from an optoelectronic delay loop (OEDL) pumped by a semiconductor laser (SL) under modulated optical feedback is utilized as the chaotic entropy resource, and the m least significant bits (m-LSBs) extraction and local XOR operation are selected as the post-processing methods. Firstly, through analyzing the influences of some typical parameters on the properties of the chaotic signal, the optimized parameter regions for achieving high quality chaotic signals with weak time-delay signatures and broad bandwidths are determined. Secondly, a high quality chaotic signal under optimized parameters is selected as a chaotic entropy resource, which is sampled and transferred to an original digital bit sequence by an 8-bit analog-to-digital converter (ADC) at a rate of 80 GS/s. Finally, through adopting the m least significant bits (m-LSBs) extraction and logical exclusive OR (XOR) operation to process the original digital bit sequence, a PRB at a rate up to 400 Gbits/s can be generated, which has passed all the NIST tests.