Reviewerly/exHarmony huggingface dataset:
Dense Activation Network for Image Denoising

Although deep convolutional neural networks (CNNs) have received great attention in image denoising, most CNN-based methods do not take full account of the hierarchical features of the original low-quality images, including the spatial feature information within channels, which decreases the representational capacity of the network. To solve this problem, we propose a dense activation network (DAN) with a dense activation block (DAB) consisting of a dense information fusion (DIF) net and a spatial activation (SA) net. Specifically, DIF takes into account both local feature information in the current block and global feature information across blocks to enhance the propagation of feature information, and it adopts dilated convolution to enlarge the receptive field of a network. Furthermore, we focus on the intra-channel spatial relationships and propose a novel SA net that adaptively recalibrates features by considering the spatial relationships within channels. Experiments on benchmark datasets show that our DAN models achieve favorable performance against state-of-the-art methods.
PENGEMBANGAN MEDIA DELIMA (DENAH LINGKUNGAN RUMAH) PADA SUBTEMA BERMAIN DI LINGKUNGAN RUMAH UNTUK SEKOLAH DASAR

The purpose of this study is to develop Delima (Home Plan) media on the Playing Subtema in the home environment for grade II elementary school. This type of research is research and development (Research and Development). The selection of this type of research is due to the authors developing a learning media product, namely Media Pomegranate (Plan of Home Environment) which is valid, practical, and effective. The results of the study showed that Pomegranate media developed were said to be valid because they obtained an average score of 4.8 and were in the good category. Likewise, the RPP, LK, and THB that were developed to support the use of Delima media were also said to be valid, because they obtained average scores in a row of 4.5, 4.1, and 4.3, and all were in the good category. The results of the implementation of the implementation of learning, student activities, and THB are said to be practical because they obtain an average score of 4.7 and 4.8 respectively and are in the good category. While THB students are said to be effective, because they have reached the established indicators.
QUANT - Question Answering Benchmark Curator

Question answering engines have become one of the most popular type of applications driven by Semantic Web technologies. Consequently, the provision of means to quantify the performance of current question answering approaches on current datasets has become ever more important. However, a large percentage of the queries found in popular question answering benchmarks cannot be executed on current versions of their reference dataset. There is a consequently a clear need to curate question answering benchmarks periodically. However, the manual alteration of question answering benchmarks is often error-prone. We alleviate this problem by presenting QUANT, a novel framework for the creation and curation of question answering benchmarks. QUANT supports the curation of benchmarks by generating smart edit suggestions for question-query pair and for the corresponding metadata. In addition, our framework supports the creation of new benchmark entries by providing predefined quality checks for queries. We evaluate QUANT on 653 questions obtained from QALD-1 to QALD-8 with 10 users. Our results show that our framework generates reliable suggestions and can reduce the curation effort for QA benchmarks by up to 91%.
LTA Report IO1 Training

This questionnaire is conducted as part of LiveTextAccess (LTA), a European co-funded project devoted to developing a professional profile and training for real-time intralingual respeakers or velotypists. The questionnaire focuses on how you teach and train in this field. Following some general questions, there will be two separate sections: one related to training as part of university programmes (such as bachelor's, master's or post-graduate) one related to vocational training (such as workshops and other vocational courses that do not form part of formal academic training programmes)
Crowd Counting via Conditional Generative Adversarial Networks

Most of current crowd counting algorithms use Euclidean loss to narrow the gap between density map and ground-truth, which leads to the low quality of density maps. In order to alleviate the above problems, we propose a crowd counting method based on conditional generative adversarial framework, which utilizes the game between generator and discriminator to achieve high quality conversion of crowd images to density maps. Specifically, CSRNet is designed as a generator, which uses the method of dilated convolution to extract the detailed information of images under the condition of adapting the scale variation. PatchGAN is designed as a discriminator to simulate high-frequency structures to further improve the quality of density maps. Benefiting from the joint optimization of adversarial loss and L2 loss, our framework can not only accurately capture the low-frequency informations, but also better model the high-frequency informations. We tested on two challenging public datasets (ShanghaiTech, UCF_CC_50) and achieved better performance, which demonstrates the effectiveness of the proposed method.
A Multi-frame Video Interpolation Neural Network for Large Motion

Video frame interpolation algorithms typically estimate optical flow to guide the synthesis of intermediate frame(s) between two consecutive input frames. However, the estimation of optical flow is easily affected by large motion. To tackle this problem, we combine multi-scale optical flow network PWC-Net and optimized network UNet++ to form our multi-frame interpolation neural network, which can be trained end-to-end. Specifically, we first use PWC-Net to estimate bidirectional optical flows between two input frames and linearly combinate the flows at each time step to obtain the approximate flows for generating the intermediate frames. Next, we use a modified UNet++ to refine the approximate flows and avoid the effects of occlusion. Finally, guided by the accurate flows, two input frames are warped and linearly fused to form each intermediate frame. Experiments show that our network outperforms representative state-of-the-art methods, especially in large motion scenarios.
Hate speech: Community social intervention in social networks from the municipality

Internet Galaxy makes up the virtual public space where hate speech is disseminated. The trolls are achieving, with remarkable results, a social control through the contamination of social networks, with ambiguous speeches that create confusion, misinformation, massive distraction, multiple discriminations, incitement to violence and disaffection with the European democratic heritage. The paradigmatic premises of Bauman, Sartori, Arendt, Horkheimer; Adorno, Twenge and Emcke, among others, are the instruments that enable us to dissect hate speech, understand its effectiveness in social networks, identify it as a social tendency and political representation, as well as formulating a proposal for local digital community intervention inspired by the fusion of the aforementioned theoretical premises and recent European experiences. The municipal response requires an organizational and functional framework of digital governance that promotes new social majorities against haters, who are pretending to subvert the democratic order.
Controlled unclassified information assessment

In December 2016, NIST issued SP 800-171 in support of the E.O. 13556 originally issued in November 2010. This Executive Order is designed to provide guidance and direction to all organizations on how to maintain the confidentiality of governmental data on their organizational systems. It deals with specific types of unclassified data, primarily in the Critical Infrastructure areas. Initially it was focused only on governmental agencies wherein the Executive Agent, NARA, established a program for managing all unclassified information in the executive branch that requires safeguarding or dissemination controls pursuant to and consistent with applicable law, regulations, and government-wide policies. This area was somewhat modified when the E.O. 13636 for the Critical Infrastructure was issued in 2013. This E.O. led to the creation of the Cybersecurity Framework. NARA then issued a set of regulations for CUI management and control in September 2016. This chapter discusses the assessment of CUI in different areas and assessment criteria.
Annotating Narrative Levels: Review of Guideline No. 2

In this brief review, I will assess the theoretical soundness of the categories as explained in the “SANTA 2 Annotation Guidelines” as well as the practical implementation of the theory through exemplary annotation choices.
Bidirectional LSTM Recurrent Neural Network Plus Hidden Markov Model for Wearable Sensor Based Dynamic State Estimation

Abstract Publisher’s Note: This paper was selected for publication in ASME Letters in Dynamic Systems and Control. https://www.asmedigitalcollection.asme.org/lettersdynsys/article/doi/10.1115/1.4046685/1081846/Bidirectional-LSTM-Recurrent-Neural-Network-Plus
LibGuides: Classroom Management: Background Information

This guide is for the subject of Classroom Management. It contains resources available in the NCU Library.
Research Guides: Identity Theft: Locating articles

Guide for resources on Identity Theft which will provide an overview of Stetson library resources on the topic.
Prototype of a Security Model for the Armed Forces of Ecuador

The security problems in the Armed Forces of Ecuador were analyzed, the security parameters were checked to protect the military information of the Armed Forces of Ecuador database, using the security of the information. The objective of this work is to develop a prototype of a security model for Armed Forces of Ecuador, to define the organizational structure and security levels that allow developing or adopting security algorithms and protocols. To analyze security articles, cryptography and networks, the deductive method was used in exploratory research to verify current trends in security models and protect the information available to the military institution. The prototype of a security model for the Armed Forces of Ecuador was determined.
LibGuides: Media and Humanities: Using Media & Humanities databases

A collection of information resources and guidance for Journalism, Media and Humanities students
Faster Biclique Mining in Near-Bipartite Graphs

Identifying dense bipartite subgraphs is a common graph data mining task. Many applications focus on the enumeration of all maximal bicliques (MBs), though sometimes the stricter variant of maximal induced bicliques (MIBs) is of interest. Recent work of Kloster et al. introduced a MIB-enumeration approach designed for “near-bipartite” graphs, where the runtime is parameterized by the size k of an odd cycle transversal (OCT), a vertex set whose deletion results in a bipartite graph. Their algorithm was shown to outperform the previously best known algorithm even when k was logarithmic in |V|. In this paper, we introduce two new algorithms optimized for near-bipartite graphs - one which enumerates MIBs in time $$O(M_I |V| |E| k)$$, and another based on the approach of Alexe et al. which enumerates MBs in time $$O(M_B |V| |E| k)$$, where $$M_I$$ and $$M_B$$ denote the number of MIBs and MBs in the graph, respectively. We implement all of our algorithms in open-source C++ code and experimentally verify that the OCT-based approaches are faster in practice than the previously existing algorithms on graphs with a wide variety of sizes, densities, and OCT decompositions.
Fault detection in non-reporting Vehicle Tracking Units

Vehicle tracking units (VTUs) have become popular in the last decade due to the pervasiveness of their applications, such as fleet management, usage-based insurance and road side assistance. In all such applications it is crucial that the VTUs are continuously working, in order to avoid disruption of the service to the end users. Whenever a VTU stops reporting for a long period of time, e.g. a week, it is thus of extreme importance to be able to understand whether the unit is healthy or in a faulty condition.The present paper proposes a method that automatically detects VTUs that stop reporting under anomalous conditions, for instance due to low data signal coverage, connection loss, power loss, wiring issues or hardware faults; the method separates the aforementioned cases from healthy units that are in a deep sleep mode after the vehicle has been turned off. Our method exploits patterns extracted from the messages sent on the days before the last message, from historical information about the vehicle activity and from contextual information.The discrimination method is a Random Forest classifier, trained on historical VTU message data that include examples of both healthy shut-downs and anomalies, collected by Verizon Connect. A large set of features is built base on such data and a feature importance analysis is then exploited to select the most effective subset of features for the classification model.
Perseverance Reflected In Safe Haven By Nicholas Sparks (2010) : A Feminist Approach

This research focuses to find out the issue of the efforts made by the main character in the novel Safe Haven (2010) by Nicholas Sparks. The theory used in this study is Feminist in general. This type of research used in this research is descriptive qualitative. This research uses data collection methods using descriptive techniques. This study uses two data, primary data and secondary data. The novel Safe Haven by Nicholas Sparks as primary data. Online journals, theses and theses related to perseverance and escape as secondary data. The purpose of this research is to find out what kind of efforts were made by the main character in the Safe Haven novel, and to find out what impact these characters suffered after the violence they experienced. The results of this study include (1) there are 16 attempts made by the main character to escape the violence, (2) of the 3 impacts that the authors refer to, the author only found 2 of them the impact of physical injury, and the psychological impact experienced figure.
Turkish Named Entity Discovery Based on Termsets

Named Entity Recognition (NER) is a subtask of the information extraction process and aims to discover named entities in unstructured texts. Previous studies on NER mostly use statistical machine learning models instead of using classifiers since solving this problem as a classification task requires to deal with quite high dimensional and sparse vector spaces. In this paper, we take NER as a classical text classification problem and extract nominal features from each token in the unstructured text sequence. We convert each token to a document transaction and then, we use frequent termset mining to extract termset features and apply termset weighting to classify named entities. Therefore we deal with lower dimensional feature spaces. Our experimental results obtained on a large Turkish dataset show that frequent termsets and their weighting scheme can be used in NER task.
Image completion via texture direction analysis

Image completion is an approach to repair a damaged region (a hole) in an image. In this study, a novel image completion algorithm is proposed using texture direction to guide the completion process. We first analyse and detect the dominant texture direction using a gray-level co-occurrence matrix (GLCM). Based on the detected direction, we then generate a direction map that serves as a soft constraint during the completion process. Further, we propose an objective function that can balance the global texture structure and local coherency in order to maintain the structure consistency. Experimental results show that the proposed method has potential performance in maintaining the structure continuity and texture smoothness.
УПОРЯДКУВАННЯ РОБОТИ АСПІРАНТІВ В ПОЧАТКОВИЙ ПЕРІОД ДИСЕРТАЦІЙНИХ ДОСЛІДЖЕНЬ

Drawing up the work of graduate students in the initial period of dissertation research is one of the urgent scientific and practical problems. Special attention in solving these problems is paid to the issues of the scientific development of a graduate student while studying in graduate school.In the future scientists of the initial period there are difficulties with the formation and implementation of research directions. The publication aims to formalize the process of specific recommendations to substantiate the topic and purpose of scientific research, the formulation of a scientific problem, the tasks of the objective function of the work and the performance indicator, the formulation of research results as a model, method or methodology. This allows you to concentrate efforts on solving practical problems during the dissertation research.The article formulates the presentation of the obtained scientific results in the form of a structure for solving a scientific research problem, it is advisable to use when describing new models, methods or methods. Particular attention is paid to the justification of the objective function and the indicator of the effectiveness of scientific research, the definition of unmanaged and controlled variables.The results presented are of practical interest also for cadets and students of higher educational institutions studying at the second (master) level of higher education.The recommendations given in the article make it possible to streamline the activities of graduate students at the initial stages of scientific work, to concentrate their efforts on solving actual problems, the effect of the implementation of which is further confirmed by acts of introducing scientific results.
The Moderating Effect of Income on the Relationship between the Participation Motives of the Elderly in Lifelong Education and the Career Barriers

본 연구는 노인의 평생교육 참여동기가 진로장벽에 미치는 영향을 파악하고, 이 영향에 대한 소득의 조절효과를 실증적으로 분석하는 것을 목적으로 수행되었다. 이러한 목적을 달성하기 위해 본 연구에서 확인한 구체적인 연구문제는 다음과 같다. 첫째, 노인의 평생교육 참여동기 가 진로장벽에 미치는 효과는 어떠한가? 둘째, 노인의 소득이 진로장벽에 미치는 영향은 어떠한가? 셋째, 노인의 평생교육 참여동기와 진로장벽 의 관계에서 소득의 조절효과는 어떠한가? 이를 위해 D시에서 평생교육프로그램에 참여하고 있는 65세 이상의 노인 187명을 대상으로 연구를 진행하였다. 연구의 결과를 위해 주요변수의 상관관계를 확인하였으며, 조절효과를 분석하기 위해 중다회귀분석을 실시하였다. 자료를 분석한 결과는 다음과 같다. 첫째, 노인의 평생교육 참여동기는 진로장벽에 부적인 영향이 있음을 확인했다. 평생교육에 참여하거나 참여한 노인은 능력을 발전시키고, 인정받음으로써 진로장벽이 감소됨을 알 수 있었다. 둘째, 노인의 소득은 진로장벽에 유의한 부적인 영향을 미치는 것으로 분석되었다. 소득이 많을수록 진로장벽의 부적 관계가 강화됨을 확인했다. 셋째, 노인의 평생교육 참여동기와 진로장벽의 관계에서 소득은 조절효과를 갖는 것으로 나타났다. 이와 같은 연구결과를 토대로 논의와 시사점을 제시하였다.The purpose of this study was to investigate the effect of the elderly s motivation for participation in lifelong education on career barriers and to analyze empirically the effect of income adjustment on this effect. For this purpose, 187 elderly people aged 65 or older participating in lifelong education programs in D city were studied. The correlation of major variables was confirmed and multiple regression analysis was conducted to analyze the moderating effect. To that end, the city conducted a study on 187 senior citizens aged 65 or older who were participating in a lifelong education program. The correlation of the main variables was checked and the middle and multiple return analysis was performed to analyze the adjustment effects. The purpose of this study was to investigate the effect of the elderly s motivation to participate in lifelong education on career barriers and empirically analyze the effect of income adjustment on this effect. For this purpose, 187 elderly people aged 65 or older participating in lifelong education programs in D city were studied. The results of the analysis are as follows. First, it was confirmed that elderly s motivation to participate in lifelong education had negative effects on career barriers. The elderly who participated or participated in lifelong education developed their abilities and recognized that their career barriers were reduced by their recognition. Second, income of the elderly was negatively influenced on career barriers. The higher the income, the more the negative relation of the career barrier is strengthened. Third, income has a moderating effect on the relationship between elderly motivation to participate in lifelong education and career barriers. Based on the results of this study, the discussion and implications are presented.
Towards a Federation of Metadata Repositories: Addressing Technical Interoperability.

The utilisation of metadata repositories increasingly promotes secondary use of routinely collected data. However, this has not yet solved the problem of data exchange across organisational boundaries. The local description of a metadata set must also be exchangeable for flawless data exchange. In previous work, a metadata exchange language QL4MDR was developed. This work aimed to examine the applicability of this exchange language. For this purpose, existing MDR implementations were identified and systematically inspected and roughly divided into two categories to distinguish between data integration and query integration. It has been shown that all the implementations can be adapted to QL4MDR. The integration of metadata is an important first step; it enables the exchange of information, which is so urgently needed for the further processing of instance data, from the metadata mappings to the transformation rules.
Generalized Net Model of Cyber-Control of the Firm’s Dumpers and Crushers

A generalized net model of a system for tracking and monitoring the movement and actions of a firm’s dumpers and crushers is proposed. The presented model permits analysis regarding possible cyber manipulation of data, and highlights the crucial vulnerabilities of such systems.
Observer‐based controller for a class of Takagi‐Sugeno fuzzy models with uncertainty

Abstract Assuming all states are unavailable in a class of Takagi‐Sugeno (T‐S) fuzzy models with uncertainty, this article consists of designs of observers and controllers. Unlike the traditional state observer that is usually designed for the whole state once and for all, this article partitions the whole state into two parts: one is independent of the input and the uncertainty, and the other is not. Following some unique matrix transformations, an observer of the former part is first developed, based on which observers of the latter part and the uncertainty are derived. Using the observers, a controller that guarantees an asymptotically stable closed‐loop control system is proposed. Moreover, in order to determine the relevant design parameters more simply, it makes clear that the separate property is held in this case. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley &amp; Sons, Inc.