Reviewerly/exHarmony huggingface dataset:
The application effect of team resource management in the green channel of emergency ischemic stroke

ObjectiveTo explore the application effect of team resource management in green channel of emergency ischemic stroke.MethodsIn this study, 90 patients with acute ischemic stroke in the hospital were selected as the research objects by retrospective analysis and were divided into control group(not implemented) and observation group(implemented) according to whether they implement team resource management, 45 cases of each group.The emergency residence time, visit to thrombolysis time, onset to thrombolysis time and safety attitude scale score were compared between the two groups.ResultsPatients in the observation group had significantly shorter emergency retention time, visit time to thrombolysis, and onset time to thrombolysis than those in the control group, with statistically significant differences(P<0.05). The scores of the safety attitude scale in the observation group were significantly better than those in the control group, and the differences were statistically significant(P<0.05). The nursing quality of the observation group was significantly higher than that of the control group, and the difference was statistically significant(P<0.05).ConclusionThe implementation of team resource management in the green channel of ischemic stroke has a significant effect, which is beneficial to shorten the emergency visit time of patients, improve the safety attitude and nursing quality of team members, and has significant clinical value, which is worthy of promotion and application.Key words: Team resource management; Green channel; Acute ischemic stroke
A Study on Industry-academia Bidirectional Learning under the Theme of Work Efficiency with OSS

Under the theme of raising the efficiency of white-collar business tasks using software robots, we performed a study of industry-academia bidirectional learning in which project leaders from a university and a company acquire knowledge and gain practical experience in a collaborative manner. An application for automating a certain routine task was successfully developed using Python and related libraries while the project leaders exchanged opinions and information. The end result was a mutually beneficial.
JPEG 2000: guide for digital libraries

Purpose The joint photographic experts group (JPEG) 2000 image compression system is being used for cultural heritage preservation. The authors are aware of over a dozen of big memory institutions worldwide using this format. This paper aims to review and explain choices for end users to help resolve trade-offs that these users are likely to encounter in practice. Design/methodology/approach The JPEG 2000 format is quite complex and therefore sometimes considered as a preservation risk. A lossy compression is governed by a number of parameters that control compression speed and rate-distortion trade-off. Their inappropriate adjustment may fairly easily lead to sub-optimal compression performance. This paper provides general guidelines for selecting the most appropriate parameters for a specific application. Findings This paper serves as a guide for the preservation of digital heritage in cultural heritage institutions, including libraries, archives and museums. Originality/value This paper serves as a guide for the preservation of digital heritage in cultural heritage institutions, including libraries, archives and museums.
Paralanguage (The Cracked Lookingglass of a Servant, or the Uses, Virtues and Value of Liminality)

The term “paralanguage” was coined in the middle of the twentieth century in response to the problem of how to operationalize and investigate vocal signs and signals that have an impact on utterance meaning but which are not formally grammatical (e.g., tone of voice, vocal inflection), and has also been used to characterize textual elements, such as expressive punctuation. For several reasons, “paralanguage” has never been as popular as “nonverbal communication,” and has typically been subsumed within the latter. However, the vital place of “paralinguistic” phenomena in human communication has become increasingly evident with the rise of digitally mediated textual interaction (cf. emoticons, emoji and other graphical interactional tools), the development of increasingly sophisticated and responsive voice-controlled interfaces and digital assistants, and even the gestural character of touchscreen technologies. Historically, the idea of “paralanguage” has been treated with ambivalence, at best, because, in practice, separating language from paralanguage (and verbal from nonverbal) is far more difficult than it might at first seem. However, that very challenge makes the idea of “paralanguage” a powerful tool for revealing taken for granted or unacknowledged theoretical assumptions about the nature of language, communication, interaction, and information, which carry important implications for communication ethics.
Diagnostics of Methodological Competence Development of Preschool Teachers

The article is devoted to the problem of methodical competence development of preschool teachers. It requires diagnosis of the real level of this competence development. The relevance of the study is justified by the need to develop and implement a pedagogical model of methodical competence development of preschool teachers. Checking the effectiveness of the pedagogical model of methodical competence development of preschool teachers requires the development of a special diagnostic system to determine the level of methodical competence development of preschool teachers. Objective determination of the level in the context of the implemented diagnostic system can be understood by selecting a set of criteria and their indicators. Thus, the purpose of this article is to develop a diagnostic system for determining the level of methodical competence development of preschool teachers. The article describes the process of experimental diagnostics of methodical competence development of preschool teachers. On the basis of application of universal methods of scientific knowledge (analysis, synthesis, modeling, generalization) theoretical aspects of levels of pedagogical education, criteria and indicators of their definition are studied in the article. By means of theoretical methods (idealization, design) the system of criteria and indicators of methodical competence development of preschool teachers was developed. On the basis of the application of empirical methods (observation, testing, questioning, pedagogical diagnostics, pedagogical experiment) professionally significant qualities of teachers through the use of diagnostic tools are determined. The elements of novelty in the study are presented by the developed diagnostic tools, a system of criteria and indicators for determining the level of methodical competence development of preschool teachers and characteristics of each possible level (creative, productive, basic).
Singularity in CM Sequences

Most existing results about modeling and characterizing Gaussian Markov, reciprocal, and conditionally Markov (CM) processes assume nonsingularity of the processes. This assumption makes the analysis easier, but restricts application of these processes. This paper studies, models, and characterizes the general (singular/nonsingular) Gaussian CM (including reciprocal and Markov) sequence. For example, to our knowledge, there is no dynamic model for the general (singular/nonsingular) Gaussian reciprocal sequence in the literature. We obtain two such models from the CM viewpoint. As a result, the significance of studying reciprocal sequences from the CM viewpoint is demonstrated. The results of this paper unify singular and nonsingular Gaussian CM (including reciprocal and Markov) sequences and provide tools for their application. An application of CM sequences in trajectory modeling with a destination is discussed and illustrative examples are presented.
Computer Graphics: Theory and Practical

“Computer graphics refers to using acomputer to create or manipulate any kind of picture, image, or diagram”. The processand art of combining text and graphics and communicating an effective messagein the design of logos, graphics, brochures, newsletters, posters, signs, andany other types of visual communications. The five elements of lines, shapes,mass, texture, and colour are the building blocks of design for desktoppublishers. Sometimes a designer uses a line alone to divide or unite elementson a page. Lines can denote direction of movement (as in diagonal lines andarrows) or provide an anchor to hold elements on a page (such as lines at thetop, bottom, or sides of a page).
GSU Library Research Guides: Web Savvy -- General Guide: Quiz -- Publisher Evaluation

A multi-page tutorial on evaluating web sites, for beginners and those who think they know. Evaluating UNESCO as a web site publisher
Connectives and Straw Men. Experimental approach on French and English

In this paper, we present experiments designed to assess the role of causal connectives with an attributive meaning (e.g. since and puisque) on the acceptability of straw man fallacies. Our results show that connectives play a role for the detection of straw man fallacies by increasing readers’ awareness to the speaker’s persuasive intent, thus creating a forewarning effect. We also uncover a crucial difference between causal connectives both within and across languages. Taken together, our experiments plead in favor of conducting fine-grained analyses of connectives in different languages in order to deepen our understanding of their role for argumentation.
Multi-view Deep Features for Robust Facial Kinship Verification

Automatic kinship verification from facial images is an emerging research topic in machine learning community. In this paper, we proposed an effective facial features extraction model based on multi-view deep features. Thus, we used four pre-trained deep learning models using eight features layers (FC6 and FC7 layers of each VGG-F, VGG-M, VGG-S and VGG-Face models) to train the proposed Multilinear Side-Information based Discriminant Analysis integrating Within Class Covariance Normalization (MSIDA+WCCN) method. Furthermore, we show that how can metric learning methods based on WCCN method integration improves the Simple Scoring Cosine similarity (SSC) method. We refer that we used the SSC method in RFIW'20 competition using the eight deep features concatenation. Thus, the integration of WCCN in the metric learning methods decreases the intra-class variations effect introduced by the deep features weights. We evaluate our proposed method on two kinship benchmarks namely KinFaceW-I and KinFaceW-II databases using four Parent-Child relations (Father-Son, Father-Daughter, Mother-Son and Mother-Daughter). Thus, the proposed MSIDA+WCCN method improves the SSC method with 12.80% and 14.65% on KinFaceW-I and KinFaceW-II databases, respectively. The results obtained are positively compared with some modern methods, including those that rely on deep learning.
A simple refinement for depth information predicted with DNN

This paper proposes a simple refinement method for improving estimated depth information with deep neural network (DNN) from a single-view RGB image. There have been a lot of effective depth prediction methods using DNN, such as <i>ResNet-UpProj</i>[1]. However, such a learning-based method sometimes estimates unclear or uncertain depth information, especially on the periphery of edges, even if enough learning is done. This paper aims to improve the predicted depth of edge periphery by applying simple image processing based on the position information of edges in an original RGB image to the depth image. Experiments with <i>NYU Depth</i> v2 data-set[2] showed that our simple approach can decrease about 14.3% of the root mean square errors of depth.
Deep Learning in Target Space.

Deep learning uses neural networks which are parameterised by their weights. The neural networks are usually trained by tuning the weights to directly minimise a given loss function. In this paper we propose to reparameterise the weights into targets for the firing strengths of the individual nodes in the network. Given a set of targets, it is possible to calculate the weights which make the firing strengths best meet those targets. It is argued that using targets for training addresses the problem of exploding gradients, by a process which we call cascade untangling, and makes the loss-function surface smoother to traverse, and so leads to easier, faster training, and also potentially better generalisation, of the neural network. It also allows for easier learning of deeper and recurrent network structures. The necessary conversion of targets to weights comes at an extra computational expense, which is in many cases manageable. Learning in target space can be combined with existing neural-network optimisers, for extra gain. Experimental results show the speed of using target space, and examples of improved generalisation, for fully-connected networks and convolutional networks, and the ability to recall and process long time sequences and perform natural-language processing with recurrent networks.
Development of an interface simulating swimming motion for virtual space walk-through

Virtual Reality (VR) contents have been becoming popular. However, VR would certainly cause VR motion sickness. One of the main factors in VR motion sickness might be the discrepancy between the predicted physical experiences and the actual physical experiences. To prevent such discrepancy, an approach is effective that synchronizes the user's physical movements in the virtual space with the user's somatosensory movements. There has been developed a VR system which provides such a somatosensory interface. However, it is too huge, expensive and difficult to operate. In this paper, we propose a simple somatosensory interface for moving virtual space by imitating swimming motions. The users of our system move the virtual space like to swim in the water by the kicks of both foot and the strokes of both arms. We developed a sensory interface that measures user's imitating swimming motions by four gyro sensors. Each gyro sensor is a 9-axis gyro sensor, including a 3-axis angular velocity sensor, a 3-axis acceleration sensor, and a 3-axis geomagnetic sensor. Four gyro sensors measure the movements of the strokes of both arms and kicks of both feet, respectively. Five students evaluated our interface. They use our interface to navigate the specified course. After that, they answered the questionnaires. Experimental results verified that our interface was useful and effective for moving the virtual space without causing VR motion sickness.
System for searching illustrations of anime characters focusing on degrees of character attributes

Keyword searches are generally used when searching for illustrations of anime characters. However, keyword searches require that the illustrations be tagged first. The illustration information that a tag can express is limited, and it is difficult to search for a specific illustration. We focus on character attributes that are difficult to express using tags. We propose a new search method using the vectorization degrees of character attributes. Accordingly, we first created a character illustration dataset limited to the hair length attribute and then trained a convolutional neural network (CNN) to extract the features. We obtained a vector representation of the character attributes using CNN and confirmed that they could be used for new searches.
Forward Selection Component Analysis

The algorithms presented in this chapter are greatly inspired by the paper “Forward Selection Component Analysis: Algorithms and Applications” by Luca Puggini and Sean McLoone, published in IEEE Transactions on Pattern Analysis and Machine Intelligence, December 2017, and widely available for free download on various Internet sites (just search). However, I have made several small modifications that I believe make it somewhat more practical for real-life applications. The code for a subroutine that performs all of these algorithms is in the file FSCA.CPP.
How To Stop Your Phone From Being Tracked

Would you like to learn how to prevent your phone from being tracked? If you answered yes to that question you should know that there are some simple ...
Computer Vision Based Sign Language Recognition System

Sign language is a language that uses body movements, gestures, and facial expressions to conveymessages or information. Sign languages are commonly used among hearing-impaired as well asmutism community. However, static gesture recognition system is not capable of recognizingtemporal content of gesture that contains movement. The main objective of this project is todevelop a vision based American Sign Language (ASL) recognition system that has the capabilityto recognize the ASL that contains temporal feature. American Sign Language Lexicon VideoDataset (ASLLVD) is used in this project. Out of 3300 signs in the dataset, only 5 gestures inused during the neural network and Support Vector Machine (SVM) video sequence trainingprocess. Various image processing techniques such as GrabCut background subtraction,grayscaling, and image resizing operation are performed on the video dataset. In order to mitigatethe temporal and spatial complexity, mean structural similarity index (MMSI) technique is usedto reduce the temporal length of the video dataset while reserving the video portion that has themost information. Feature extraction of this dataset is done using multiple Convolutional NeuralNetwork (CNN) models for instance InceptionResnetV2, VGG19, DenseNet201 andMobiliNetV2. Among these CNN models, the best validation accuracy of 15.24% is obtained byInceptionResnetV2 model. In summary, the model is too overfit due to small dataset size. Tosolve the overfitting issue, SVM is also used alongside Histogram of Oriented Gradient (HOG)descriptor. The best accuracy obtained from SVM method is 39.12%.
Encrypted real-time communication web (WEBRTC) using the principle of virtual DOM rendering cycles

Abstract Website is a collection of formatted pages that display text, image, audio or video content to provide information. Various fields in industry, science, government, non-profit agencies use the website as a medium for presenting information to public or stakeholders. Generally, websites present data synchronously so that it requires an effort to request data until it is displayed on a web page. Industries in the investment, stock and even weather reports require to present information with real-time results. This study aims: (1) Create and design architecture Web Real-time Communication using Virtual DOM Rendering Cycles principles. (2) Present encrypted data to real-time decryption process to render into web page. This research purpose is to provide the solution of real-time rendering encrypted data through process rendering with virtual DOM manipulation. Data encrypted collection have real-time decryption process; its results can be rendered in less interval time of request, with the whole process running on asynchronous process. Technical and non-technical testing steps were conducted, namely (1) White-box, (2) Black-box testing, and (3) Performance consistency testing.
On the Assessment of Compliance with the Requirements of Regulatory Documents to Ensure Information Security

Examples of different types of assessments are all around us, providing our assurance that the goods we use won’t harm us, that the system components will work correctly, that services are being delivered consistently, that manufacturers are effectively managing the impact of their activities on health, safety, and the environment, etc. One of the essential forms of assessment is a compliance assessment designed to check how the requirements of regulatory documents to ensure information security (IS) are fulfilled or not on the assessment object, for example, a product, process, system, or service. This short paper discusses work-in-progress results as a part of research aimed at determining the ways of possible improvement, unification and greater formalization of an objective assessment of compliance with the mandatory requirements of regulatory documents on ensuring IS for the selected assessment objects based on the development of recommendations for applying a risk-based approach.
Developing a Model of Cloud Computing Protection System for the Internet of Things

This article proposes the use of a multi-agent approach when building a model of the cloud computing protection system of the Internet of things based on the reference architecture of cloud computing. It is proposed to build a system for monitoring user behavior in a cloud computing system using an automated model. The selection of a security agent is necessary on the one hand in connection with the increase in the number of commercial enterprises switching to the cloud computing platform, and on the other hand, with the need to protect data and resources on the Internet of things. The article also presents some scenarios for the interaction of actors based on a dedicated security agent. In this case, the security agent performs a controlling and connecting role between all the actors of the model, monitoring and recognizing unauthorized actions both by cloud users of the Internet of things networks and by actors of the cloud computing system of the Internet of things.
LGA Cyber Security Stocktake: National-Level Report

A cybersecurity stocktake of all 353 councils in England examined IT security, leadership, governance, partnerships, technology arrangements and training, offering recommendations on areas for improvement.