Reviewerly/exHarmony huggingface dataset:
NDE1.0 &#8211; A new database of earthquake data recordings from buildings for performance based earthquake engineering, vulnerability assessment and seismic structural health monitoring

&amp;lt;p&amp;gt;Over the last two decades, seismic ground motion prediction has been significantly improved thanks to the development of shared, open, worldwide databases (waveform and parametric values). Unlike seismic ground motion, earthquake data recorded in buildings are rarely shared. However, their contribution could be essential for evaluating the performance of structures. Increasing interest in deploying instrumentation in buildings gives hope for new observations, leading to better understanding of behavior. This manuscript presents a flat-file containing information on earthquake responses of instrumented buildings. Herein, we present the structure of the NDE1.0 flat-file containing site and earthquake characteristics (vs30, Magnitude, Distance...), structural response parameters (i.e. drift ratio, peak top values of acceleration, velocity and displacement, pre- and co-seismic fundamental frequencies) computed for several intensity measures characterizing ground motion (peak and spectral values, duration...). The data are from real earthquake recordings collected in buildings over the years. This 1.0 version contains 8,520 strong motion recordings that correspond to 118 buildings and 2,737 events, providing useful information for analyses related to seismic hazard, variability of building responses, structural health monitoring, nonlinear studies, damage prediction, etc. Some specific analysis will be presented concerning seismic structural health monitoring and damage prediction, with a special focus on the engineering demand parameter versus intensity measures variability.&amp;lt;/p&amp;gt;
Automatic Colorization of High-resolution Animation Style Line-art based on Frequency Separation and Two-Stage Generator

In this paper, we use Generative Adversarial Networks (GAN) to address the industrial needs of auto colorization of line arts which takes enormous amount of manual labor. Auto-colorization method used in Image-to-Image conversion based on GAN has received a lot of attention due to its promising results. In this paper, we present a solution to not only colorize the line art but also transform the low resolution out image to match the resolution of the input image through two generators and frequency separation method. A high frequency components are extracted from the line, then two generators are used to colorize the image in low resolution. The high frequency component is merged with low resolution image to produce the high resolution colorized image. The resolution of fi nal output image matches the resolution of original image while preserving the texture of the input image, whereas the other schemes reduce the output image to 512 pixels. We performed visual and qualitative evaluation using FID, PSNR, and SSIM. The FID Score of the proposed method is better than the base model by about 4 (proposed: 47.87 and base model 51.64). PNSR and SSIM of the high-resolution images are also better than the base model. PSNR and SSIM of base model is 13.01 and 0.72 whereas the proposed is 20.77 and 0.86, respectively.
Deliberative and Conceptual Inference in Service Robots

Service robots need to reason to support people in daily life situations. Reasoning is an expensive resource that should be used on demand whenever the expectations of the robot do not match the situation of the world and the execution of the task is broken down; in such scenarios, the robot must perform the common sense daily life inference cycle consisting on diagnosing what happened, deciding what to do about it, and inducing and executing a plan, recurring in such behavior until the service task can be resumed. Here, we examine two strategies to implement this cycle: (1) a pipe-line strategy involving abduction, decision-making, and planning, which we call deliberative inference and (2) the use of the knowledge and preferences stored in the robot’s knowledge-base, which we call conceptual inference. The former involves an explicit definition of a problem-space that is explored through heuristic search, and the latter is based on conceptual knowledge, including the human user preferences, and its representation requires a non-monotonic knowledge-based system. We compare the strengths and limitations of both approaches. We also describe a service robot conceptual model and architecture capable of supporting the daily life inference cycle during the execution of a robotics service task. The model is centered in the declarative specification and interpretation of robot’s communication and task structure. We also show the implementation of this framework in the fully autonomous robot Golem-III. The framework is illustrated with two demonstration scenarios.
Achieving the Effectiveness of Training Using Information and Communication Technologies in Training Designers

The purpose of this article is to analyze the introduction and use of information and communication technologies (ICT) in the special disciplines of higher education, to teach teachers how to improve the effectiveness of teaching and learning through information and communication technologies (ICT). This article discusses the issues of improving the knowledge and skills of students through the use of modern information and communication technologies in the preparation of designers, increasing students' interest in the educational process and the ability to apply their knowledge in practice in the future. The focus is on the need to develop appropriate strategies for a new educational role and, in addition, to enhance the role of learners in integrating information and communication technologies (ICT) into the educational process. The role and perspective of the teachers was very important, highlighting them as key players in the process. The data show that there is a belief that the use of information and communication technologies (ICT) in the educational process will help increase the effectiveness of education and facilitate the organization of the educational process. In particular, it shows that the contribution of information and communication technologies (ICT) to the improvement of the educational process in educational institutions, where information and communication technologies (ICT) is an innovative factor, is high. Achieving this high level means that the educational institution must not only modernize technological means, but also change the models of teaching.
SELECTION OF OUTBOUND LOCATIONS IN GUNUNGKIDUL USING A MULTI-OBJECT OPTIMIZATION METHOD BASED ON REPORTING ANALYSIS

Decision support system (DSS) is a computer-based system that can help users make decisions. One of the DSS applications is to select outbound locations in Gunungkidul by using the Multi-Object Optimization method on the Base Ratio of Analysis (MOORA). Outbound is an open-air learning method based on direct experience presented in the form of games, discussions and adventures. So that participants will get feedback about the impact of the activities carried out which is useful for self-development in the future. The application of the MOORA method is a method that can determine the weight of each criterion, then proceed with a ranking process that will select the best alternative from a number of available alternatives. In this study an application for outbound location selection in Gunungkidul was made using the MOORA method, an application designed based on a website, this test was carried out using black box testing. The results of this study show that the best location based on the criteria weight and ranking with several alternatives is the location of the Nglanggeran Ancient Volcano with a value of 0.1507, Sri Getuk Waterfall with a result of 0.0909, Kampung Jelok with a result of 0.01497, Goa Pindul with a result of 0.00182, Sundak Beach with a result The result is -0.07192, Wulenpari with the result -0.08854, and the last one is Indrayanti beach with the result -0.13179.
Network Approach for Visualizing the Evolution of the Research of Cross-lingual Semantic Similarity

The paper is devoted to the problem of the bibliometric study of publications on the topic “Cross-lingual Semantic Similarity”, available in the Dimensions database. Visualization of scientific networks showed fragmentation of research, limited interaction of organizations. Leading countries, leading organizations and authors are highlighted. Overlay visualization allowed us to assess the trends in citing authors. The expansion of the geography of research is shown. For international cooperation, the uniformity of semantic approaches to describing the concepts of critical infrastructure, incidents, resources and services related to their maintenance and protection is important. The stated approaches can be applied for visualization and modeling of technological development in the modern digital world. Semantic similarity is a longstanding problem in natural language processing (NLP). The semantic similarity between two words represents the semantic proximity (or semantic distance) between two words or concepts. This is an important problem in natural language processing, as it plays an important role in finding information, extracting information, text mining, web mining and many other applications.
O IHGRGS E OS ACERVOS PESSOAIS: DOCUMENTOS E OBJETOS DE SANDRA PESAVENTO

RESUMO O artigo relata as circunstâncias e condicoes que se encontra o acervo da intelectual, escritora e historiadora Sandra Jatahy Pesavento, cuja trajetoria esta registrada nos itens recolhidos em seu acervo, cuja guarda encontra-se sob responsabilidade do Instituto Historico do Rio Grande do Sul, instituicao que vem prestando relevantes servicos aos processos de historia e memoria no Rio Grande do Sul. Discorre sobre os procedimentos iniciais que estao sendo adotados para dar condicoes de acesso ao acervo, considerando as possibilidades e perspectivas de trabalho desses documentos, de modo especifico, e na sua relacao com os demais acervos do Instituto. Destaca aspectos singulares desse acervo e discute questoes relacionadas aos acervos pessoais e sua dimensao na arquivologia. ABSTRACT The article reports the circumstances and conditions found in the collection of the intellectual, writer and historian Sandra Jatahy Pesavento, whose trajectory is recorded in the items collected in her collection, whose custody is under the responsibility of the Historical Institute of Rio Grande do Sul, an institution which has been providing relevant services to the processes of history and memory in Rio Grande do Sul. It discusses the initial procedures that are being adopted to give conditions of access to the collection, considering the possibilities and perspectives of work of these documents, in a specific way, and in its relationship with the other collections of the Institute. It highlights singular aspects of this collection and discusses issues related to personal collections and their dimension in archivology.
INFLUENCE OF VALUES-BASED ORIENTATIONS OF EDUCATION STUDENTS ON EVOLVEMENT OF THEIR PROFESSIONAL FLEXIBILITY

There is a need to develop professional flexibility and the values-based attitude to pedagogical activity in future teachers. In recent years, pedagogical activity has been associated with extreme and stressful situations, constantly changing conditions of learning, and general uncertainty. This imposes requirements to the professional flexibility of future teachers. Teachers are required have the stability of their personal qualities, on the one hand, and flexibility, on the other hand. Therefore, this work considers professional stability as a fundamental basis. Professional flexibility of future teachers is understood as a set of emotional, vocational and behavioral flexibilities, which provide a values-based attitude to pedagogical activity, regulation and stability of professional behavior, readiness to respond quickly to changing conditions and challenges of the professional environment by finding original solutions to professional problems. An empirical study of the values-based orientations of 213 first-year students was carried out in the South Ural State Humanitarian Pedagogical University, Chelyabinsk, for four years. It was found that students are orientated towards values that are prioritized in pedagogical activity, and this provides the basis for the successful formation of the values-based orientations to pedagogical activity. In the course of university studies and specially organized work, the existing values-based orientations of future teachers are gradually transformed into a values-based attitude to pedagogical activity, which in turn underlies the evolvement of professional flexibility.
Integrated Data Bank Development as Supporting System of Civil Service Management in Middle Vocational School

The objectives of this study are: 1) Improved Integrated Data Bank services for staffing data and information; 2) Enhanced support system for data and information service server usage; 3) Improving data and information services that are accurate for Staffing Management. The research method used is Research and Development (R&amp;D). Data collection techniques using questionnaires and interviews. Product trials were conducted twice, the first trial involved 15 people, the second trial involved 35 people. The results of the study are 1) Integrated Data Bank services for employee data and information can be used effectively and efficiently. This is based on system reliability with a success rate of 100%. In addition, the efficiency test using GTMetrix gives the results of the PageSpeed Grade B (85%) with a loading rate of the system page 7.4 seconds; 2) the support system for the use of data and information service servers runs according to the Integrated Data Bank application; 3) Personnel management data and information services can be used as an accurate staffing database and show that the Integrated Data Bank staffing management information system can be used as a supporting management system for staff at SMK Muhammadiyah Karangpucung; 4) Integrated Data Bank Products have gone through the process of design validation, instrument validation, and product validation through judgment experts and experts, which produce data in the form of Data Flow Diagrams (DFD), Unified Modeling Language (UML) design, and Entity Relationship Diagram Bank designs Integrated Data. Based on the results of the product design validity test showed that the layout (layout), interface (interface), and content (content) of the system itself obtained a final percentage of 84%. Suggestions in this study include 1) Socialization of the Integrated Data Bank system to employees about the existence of this system can be optimized so that all information can be conveyed properly; 2) Integrated Data Bank systems can be utilized optimally to integrate staffing data; 3) Integrated Data Bank System can be developed into a superior product as a staffing database system in the SMK environment.
Channel Coding Information Hiding Technology Based on Spacecraft Application

Nowadays, information resources have become the most important part of resources in the Internet era, and the problems of information security have become the research hotspot. Channel coding information hiding technology is a new type of information hiding technology, which has been widely studied in the field of communication, but there is little research on the application of spacecraft. Based on this, this paper studies a channel coding information hiding technology based on spacecraft application. In the research, this paper mainly uses the good randomness and security performance of chaotic sequences, applies them to the random coding of encrypted information, and realizes the hiding of encrypted information. In the simulation analysis, it can be found that the channel coding information hiding technology proposed in this paper has good encryption performance, and when the channel bit error rate is set to 5 × 10−3, the recovered information error rate is 0, and the encrypted information can be recovered without error.
The New Stage in the US-China Rivalry: The Quantum Computer

This study was written to investigate the race to own fully equipped quantum computer, which is the new competition sphere in the struggle between The USA and China, and the privilege of owning quantum computers. The subject of the existing study was determined to take into consideration the few numbers of researches in this field. Although the existing study does not fully illuminate both the advantages of quantum computers and the US-China rivalry, it is important bringing more attention in the international relation literature to a quantum computer and the competitions of superpowers to own it. In this sense, in the existing two parted study, while current rivalry between the US and China is investigated in the first chapter, the potential advances of quantum computer and the race to own it is explored in the second part of article.
$$l_{2}$$ Norm Prior-Based Modified Bright Channel for Low-Illumination Images

Riya Gupta, Bhupendra Lamba, Subir SinghLow-illumination image enhancement problem is a very challenging problem in many computer vision applications and, when it comes to nighttime low-illumination images, it becomes more challenging because the depth information of the low-illumination image is not known. Recently, bright channel prior-based methods are used to enhance the overall illumination of the image. The bright channel prior is based on statistical observation on the low-illumination image containing some regions with bright intensity pixels. In this paper, we propose an improved $$l_{2}$$ norm-based prior bright channel to enhance the overall illumination of the image by maintaining the image contrast. This new generated bright channel is free from the block effect, which makes our method more robust than other methods. The experimental results show the effectiveness of the proposed method on the low-illumination images as well as on the nighttime low-illumination images.
Self Actualization and Education Value in The Novel Dendam Si Yatim Piatu by Sintha Rosse

This study aims to analyze self-actualization and educational values contained in Sintha Rosse's Dendam si Yatim Piatu novel based on Abraham Maslow's humanistic psychology. The research method used was descriptive qualitative method and content analysis technique. The results showed: 1) Self-actualization was found to be more dominant in this novel as much as 65.08% while the value of education was 34.91%. The 14 characters who show self-actualization are found all in this novel. The most dominant self-actualization is focusing on achievement targets (13.52%), the second most is social awareness (13.09%), independence (9.23%), spontaneity, simplicity, and fairness (9.01%). rewards that are always new (8.80%), interpersonal relationships (8.80%), creativity (6.87%), democratic (6.01%), self-acceptance (5.79%), independence (5.58 %), peak experience (4.29%), observing reality efficiently (3.43%), a meaningful sense of humor (3.00%), and the need for privacy (2.58%). 2) The dominant educational value is the value of moral education (37.20%), followed by the value of social education (29.60%), the value of divine education (24.40%), the value of cultural education (5.60%), and the value of aesthetic education (3.20%). Through this novel, the author provides an example through self-actualization of the main character, maximizing all efforts, developing talents, potential, never giving up in achieving goals and achieving the desired success so that life becomes more meaningful. In addition, the author also conveys good values so that readers can wisely take lessons from them which are expected to be applied in everyday life.
How to Utilize The Best Robo-Advisor For Your Investment Portfolio

The robo-advisors computerize your investment management by utilizing PC algorithms to construct a portfolio for you and administer your assets depending on your objectives and
A Single Iterative Step for Anytime Causal Discovery

We present a sound and complete algorithm for recovering causal graphs from observed, non-interventional data, in the possible presence of latent confounders and selection bias. We rely on the causal Markov and faithfulness assumptions and recover the equivalence class of the underlying causal graph by performing a series of conditional independence (CI) tests between observed variables. We propose a single step that is applied iteratively, such that the independence and causal relations entailed from the resulting graph, after any iteration, is correct and becomes more informative with successive iteration. Essentially, we tie the size of the CI condition set to its distance from the tested nodes on the resulting graph. Each iteration refines the skeleton and orientation by performing CI tests having condition sets that are larger than in the preceding iteration. In an iteration, condition sets of CI tests are constructed from nodes that are within a specified search distance, and the sizes of these condition sets is equal to this search distance. The algorithm then iteratively increases the search distance along with the condition set sizes. Thus, each iteration refines a graph, that was recovered by previous iterations having smaller condition sets -- having a higher statistical power. We demonstrate that our algorithm requires significantly fewer CI tests and smaller condition sets compared to the FCI algorithm. This is evident for both recovering the true underlying graph using a perfect CI oracle, and accurately estimating the graph using limited observed data.
Diffeomorphic unsupervised deep learning model for mono- and multi-modality registration

Different from image segmentation, developing a deep learning network for image registration is less straightforward because training data cannot be prepared or supervised by humans unless they are trivial (e.g. pre-designed affine transforms). One approach for an unsupervised deep leaning model is to self-train the deformation fields by a network based on a loss function with an image similarity metric and a regularisation term, just with traditional variational methods. Such a function consists in a smoothing constraint on the derivatives and a constraint on the determinant of the transformation in order to obtain a spatially smooth and plausible solution. Although any variational model may be used to work with a deep learning algorithm, the challenge lies in achieving robustness. The proposed algorithm is first trained based on a new and robust variational model and tested on synthetic and real mono-modal images. The results show how it deals with large deformation registration problems and leads to a real time solution with no folding. It is then generalised to multi-modal images. Experiments and comparisons with learning and non-learning models demonstrate that this approach can deliver good performances and simultaneously generate an accurate diffeomorphic transformation.
Volatility Modelling and VaR: The Case of Bitcoin, Ether and Ripple

Abstract Since Bitcoin introduction in 2008, the cryptocurrency market has grown into hundreds-of-billion-dollar market. The cryptocurrency market is well known as very volatile, mainly for the fact that the cryptocurrencies have not the price to fall back upon and that anybody can join the trading (no license or approval is required). Since empirical literature suggests that GARCH-type models dominate as VaR estimators the overall objective of this paper is to perform comprehensive volatility and VaR estimation for three major digital assets and conclude which method gives the best results in terms of risk management. The methods we used are parametric (GARCH and EWMA model), non-parametric (historical VaR) and Monte Carlo simulation (given by Geometric Brownian Motion). We conclude that the best method for value-at-risk estimation for cryptocurrencies is the Monte Carlo simulation due to the heavy diffusion (stochastic) process and robustness of the results.