Reviewerly/exHarmony huggingface dataset:
Application of Artificial Intelligence in Clinical Nursing in Information Age

With the rapid development of modern information electronic technology, artificial intelligence information technology has gradually penetrated into all fields of human society. This paper aims to improve the clinical assistant nurses’ correct understanding of medical artificial intelligence, and to provide an important reference for further promoting the wide application and development of clinical artificial machine intelligence in the field of clinical nursing in China. In this paper, through the comparison of intelligent nursing and traditional nursing effect monitoring, as well as the analysis of medical staff and patients’ satisfaction with artificial intelligence treatment time, treatment effect and treatment scheme, and the results were discussed and analyzed. The problems that should be paid attention to in the application of artificial intelligence in clinical nursing were put forward, which provided guarantee for the development of clinical nursing. The research in this paper has important practical significance for the further development of the two.
Formation of the composition of programs for the knowledge–intensive industry development using bacterial optimization algorithms and fuzzy logic methods

Today the knowledge–intensive industry development is carried out by the programs that combine a set of innovation and investment projects aimed at achieving a single goal and implemented in general constraints. The presence of a larger number of project characteristics (in particular, terms, resources, performers, etc.), which must be taken into account when forming the composition of the program, leads to the formulation of the problem of multicriteria optimization. As its solution, it is proposed to use an algorithm of bacterial optimization, supplemented by a procedure for forming initial positions using fuzzy logic methods.
Unsupervised text segmentation predicts eye ﬁxations during reading

Words typically form the basis of psycholinguistic and computational linguistic studies about sentence processing. However, recent evidence shows the basic units during reading, i.e., the items in the mental lexicon, are not always words, but could also be sub-word and supra-word units. To recognize these units, human readers require a cognitive mechanism to learn and detect them. In this paper, we assume eye fixations during reading reveal the locations of the cognitive units, and that the cognitive units are analogous with the text units discovered by unsupervised segmentation models. We predict eye fixations by model-segmented units on both English and Dutch text. The results show the model-segmented units predict eye fixations better than word units. This finding suggests that the predictive performance of model-segmented units indicates their plausibility as cognitive units. The Less-is-Better (LiB) model, which finds the units that minimize both long-term and working memory load, offers advantages both in terms of prediction score and efficiency among alternative models. Our results also suggest that modeling the least-effort principle on the management of long-term and working memory can lead to inferring cognitive units. Overall, the study supports the theory that the mental lexicon stores not only words but also smaller and larger units, suggests that fixation locations during reading depend on these units, and shows that unsupervised segmentation models can discover these units.
PECULIARITIES OF FUTURE PRIMARY SCHOOL TEACHER INDIVIDUAL EDUCATIONAL TRAJECTORY FORMATION IN THE CONDITIONS OF DISTANCE LEARNING

The article provides an analysis of the formative aspects in the individual educational trajectory (IET) of a student in the Program Subject Area “Primary Education” in accordance with the conditions of distance learning. The reasons for the relevance of the study are identified; factors of IET influence on professional and personal development of the future primary school teacher; the advantages of IET in terms of distance learning for teacher training. During the study, it has been provided the interpretation of the concepts of «individual educational trajectory», «individual educational program», «individual educational route» from the standpoint of modern research. The chronology of the introduction of IET in the educational process of free education in Ukraine is presented, in accordance with the changes in the professional training of primary school teachers. The peculiarities of IET formation in the context of professional training of primary school teachers under distance learning are substantiated: the content factor, which is considered in accordance with the Concept of «The New Ukrainian School», «Professional Standards for Primary School Teachers», presented in educational and vocational training program; the position of systematic representation of the block of the selective educational component is formed and the possibilities of introduction of personalized educational programs on the basis of the praxiological approach (integration of formal, non-formal and informal education) are analyzed; procedural and methodological factor due to innovative forms, methods and aims of teaching in the context of informational educational Internet space; the main resource for educational platforms, blogs, social networks, forums, YouTube, etc. have been outlined; the factor of personalization of the educational environment is based on the methodology of the environmental approach and determines its design from the standpoint of management of pedagogical systems and psychological and pedagogical features of student identification as a participant in the educational process; coordinating and monitoring factor of educational activity is aimed at establishing pedagogical interaction in the system of teacher-tutor and student, the formation of his professional reflection on their own educational results; personal factor is aimed at diagnosing the readiness to learn by distance technology, readiness to choose educational content within their own educational needs, the organization of independent work, media literacy.
Localising the Privacy Requirement to Improve the Scalability Issue of Blockchain

Singh, Ajay Jani, Preetida VinayakrayBlockchain is one of the most ice breaking technology of this century. To make fast integration of this technology in various domains some prominent issues like scalability, high throughput, processing delay need to be resolved. Blockchain architecture is decentralized with distributed system approach, where maintaining the privacy of every block comes at the cost of scalability of the network. Scalability is the problem associated with transaction rate (throughput) of the system. Therefore to make a blockchain technology embedded within the mainstream it is necessary for it to be secure and scalable at the same time. To deal with the issue of scalability proposed framework attempts to localize the privacy requirement on a block level along with a simple but efficient consensus algorithm. Therefore this paper shows a novel framework that is built around a blockchain network that uses distributed nano node architecture. These nano node assist to verify blocks coupled with an efficient consensus algorithm and maintain the privacy of the blocks.
Target Tracking System for Urban Counter-UAS Using a Camera Network

As interest and investment into unmanned aerial systems (UASs) continue to grow in recent years, security and surveillance of these vehicles in urban environments become increasingly important for both operators and residents. Traditional aerial surveillance methods such as radar systems are less efficient in urban canyons due to high-rise buildings blocking line of sight (LOS). In this paper, we design a stationary tracking node consisting of a GPS, a high-resolution fish-eye camera, an infrared-beacon, and a GPU accelerated edge computing unit. We develop algorithms for calibration of a network of these deployed nodes in a large scale urban environment. We also develop a multiple-sensor data-association and estimation algorithm to track multiple UASs simultaneously. The estimation algorithm leverages a dual measurement mode using blob tracking for distant UASs and convolutional neural network (CNN) based object detection when the vehicle is close to one of camera nodes.
A Heuristic Approach to Extract Knowledge from the Text Considering Explicit and Implicit Features Both

The important thing to extract knowledge from text data (comments, chat, blogs, news articles, etc.) is how to convert unstructured data into structured data sometime called metadata and further how to get implicit features from it. Implicit features are very important for semantic understanding of any sentence. Generally, features are opinionated in terms of adjectives. Researchers find such features easily using natural language processing and the concept of association between adjectives and high frequency nouns, sometime synonyms of nouns and adjectives also play very important role in the acquisition of such features. In this paper, adjectives and their synonyms are considered to have highly relevant features and opinions in terms of pointwise mutual index. This paper presents the introduction, proposed method, framework, result, and finally conclusion.
Morphometric Study of Traces on Bone Retouchers from the Chagyrskaya Cave Using a Profi lometer

Bone retouchers were used by ancient humans in stone tool working. They were made mainly of the bones of prey animals. Retouchers are most characteristic of the Neanderalian bone tool collections, but they are also found in other cultural and chronological contexts at all stages of the Stone Age in Eurasia and beyond. Research on bone retouchers has been carried out for over a century using many different methods. Use-wear signs on bone retouchers are usually studied through a microscope with a magnification of up to x50 and are classified according to morphological characteristics. Most often the size of retouchers and their working zones are measured, but not the size of a single sign. Today, there are several classifications of use-wear traces on bone retouchers identifying from two to four types of marks. This paper presents the results of a morphometric study of the most widespread and recognized by most researchers category of marks on retouchers -short linear impressions with a V-shaped or trapezoidal profile using high-precision three-dimensional modeling methods. A high-precision three-dimensional structured light scanner and a three-dimensional surface profilometer were used to analyze traces on the surface of retouchers at the micro level. We measured the length, width, depth and angles of single, non-overlapping traces on the working areas of retouchers from the Chagyrskaya Cave. As a result, the average size of such traces with various exhaustion rates and their inclination angle in the cross-section view were determined. The dimensions of the marks on retouchers of Chagyrskaya Cave were compared with those on retouchers from other Middle Paleolithic sites previously published by other researchers.
A basic study on the development of tasks for Korean Language Screening for internet-based academic purposes

This basic study investigated the development of screening test tasks to check whether the language skills for academic purposes of Korean learners entering Korean universities or graduate schools are problematic in academic performance or require follow-up language support. In the absence of language diagnostic assessment conducted upon admission to Korean universities, the overall issue was discussed to develop a simple internet-based screening tool. To this end, first, diagnostic assessment and screening tools which are being conducted in foreign countries were investigated, and tasks were analyzed to assess whether questions could be implemented in Korean situations. Accordingly, an appropriate task was explored and developed for this inspection, a draft test was prepared, and an expert review was conducted. Additionally, it was intended to obtain significant implications through the preliminary tests of five students. The screening test consisted of four parts: background questions, vocabulary tasks, text completion tasks, and academic skills-related tasks. This study presented a meaningful discussion using the Yes/No format that is helpful for screening tools. Although it is not adequately used in Korean language evaluation, and it is meaningful in checking the TLU(Target Language Use), it newly included academic skills-related tasks that were not included in overseas screening tests. If a screening test can be developed and implemented based on this study, it is expected that it can develop into a realistic alternative in the field of Korean language education for academic purposes.
Visual Teaching and Simulation Experiments of High Voltage Technology in the Post-modern Curriculum View

The high voltage technology course is rich in content and abstract content, many course knowledge points, involving high voltage levels and limited daily teaching equipment.Build a virtual simulation experiment teaching project for high voltage technology.By building a platform such as DC withstand voltage virtual simulation experiment, we explore the digital online intelligent teaching method under the view of post-modern curriculum.Strengthen students' understanding of theoretical knowledge through practical application and realize independent, inquiry and cooperative learning ability.
Native Hawaiian Library Services Grant (IMLS)

Federal Grants & ContractsVolume 45, Issue 9 p. 1-2 Grants alerts Native Hawaiian Library Services Grant (IMLS) First published: 07 April 2021 https://doi.org/10.1002/fgc.31641Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume45, Issue98 April 2021Pages 1-2 RelatedInformation
Algorithmic Study on Position and Movement Method of Badminton Doubles

The algorithms used by schedulers depend on the complexity of the schedule and constraints for each problem. The position and movement of badminton players in badminton doubles competition is one of the key factors to improve the athletes’ transition efficiency of offense and defense and the rate of winning matches and to save energy consumption. From the perspective of basic theory, the author conducts research on the position and movement of badminton doubles. Based on the numerical analysis method, the optimal model of standing position and direction composed of 7 nonlinear equations is established. In addition, the final of 10 matches of the super series of the world badminton federation in 2019 was selected as the sample of speed parameters. With the help of MATLAB mathematical analysis software, the numerical model established by the least square method was adopted to optimize the specific standing position and walking model. Ultimately, the optimal solution has been obtained, which can be represented on a plane graph. The optimal position of the attack station should be the blocking area (saddle-shaped area) and the hanging area (circular arc area in the middle). The optimal defensive positioning should be left defensive positioning area (left front triangle area) and right defensive positioning area (right front triangle area), which is consistent with our current experience and research results. The research results use mathematical tools to calculate the accurate optimal position in doubles matches, which has guiding significance to the choice of athletes’ position and walking position in actual combat and can also be used as a reference for training, providing a certain theoretical basis for the standing and walking of badminton doubles confrontation. The data collection and operation methods in this study can provide better calculation materials for artificial intelligence optimization and fuzzy operation of motion displacement, which is of great significance in the field of motion, simulation, and the call of parametric functions.
Social and Academic Impacts of COVID-19 - Related Emergency Remote Teaching on Japanese University Students

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A Mimic Cloud Ruling Method for Defending Against Time-Delayed Covert Channel Attacks

The mimic cloud system can effectively defend against security threats such as vulnerabilities and backdoors in the cloud environment, and has been widely used in important fields such as finance, military affairs and cyber space. However, its unique adjudication mechanism provides a potential way to implement time-delayed covert channel attacks. In response to this potential security threat, a mimic cloud ruling method to defend against time-delayed covert channel attacks is proposed. First of all, from the perspective of information theory, the attacker uses the response delay sample mean and variance as the feature statistics to deduce the detection rate formula. Furthermore, in order to defend against time-delayed covert channel attacks, basic countermeasures and first-come-first-rule strategies are proposed to reduce attackers' use of response time-delay difference characteristics to transmit information. Finally, a prototype system based on Nginx was developed and extensively tested to verify the harm of the time-delayed covert channel attack and the effectiveness and feasibility of the proposed defense strategy.
Distributed Multi-source Information Fusion System for the Management of Training Base

With the continuous development of information technology, more and more parents attach importance to information education. The traditional training base management can no longer satisfy the current higher vocational college education, in order to solve the problem of seeking talents for enterprises and training professional talent bases, this article offers a way to make use of a multi-source information fusion system to solve current needs. Combining with the characteristics of the training database, this method adopts the improved radial basis function network and the improved Dempster Schaffer theory, and a set of multi-source information fusion is designed. The training base management system, which has the functions of network sharing, intelligent optimization of class scheduling, teacher-student interaction, situation monitoring, and data storage. These results can further improve the recommendation system and promote the sustainable development of training base management.
Blockchain-Based Authentication Scheme to Secure Supermarket Transactions—A Survey

Internet of things (IoT) takes an important part in authorizing in converting physical assets to smart establishments through the existing network infrastructures. IoT is aimed at preparing a multiplex information system along with sensor data acquisition, efficient data exchange through networking, artificial intelligence, big data, machine learning, clouds, etc. A system of storing information in a form that it can be protected from hacker system is blockchain technology. This technology stores the data in form of blocks and each block is connected to other block in a linear order. Sensor devices generate a huge amount of data which contains the private information such as transaction details and personal details. The collected information is stored in cloud, and it is essential to safeguard and secure this information. This paper gives a survey on various hashing algorithms and techniques used to provide security to data generated from an IoT device.
Telegram Bot as a Data Collection Tool for Progress Reports in Area Mapping Progress Monitoring System

In the Area Mapping Project (Preparation for the 2020 Population Census), there is monitoring and collecting data process on the progress of activities in the field. There are weaknesses in data collection on the progress of activities in the field; The manual recapitulation of progress reporting makes the progress data not displayed in real-time, the SMS Gateway is often interrupted, and progress data collection through the monitoring website is less effective if reported directly by field officers. Telegram Bot is used as a data collection tool for field progress reports on Area Mapping activities to overcome these weaknesses. This study aims to prove that Telegram Bot can be used as a real-time data collection tool, has good performance, and is acceptable to users. Telegram Bot is integrated with Monitoring Website into one system and database in this research. This system uses PHP, Yii2, and MySQL, and communication between the web server and Telegram Server uses the webhook method. Based on the Black Box test results, all functions in this system run as expected. The average bot response time was 7.72 seconds for images and 2.25 seconds for text data in the performance test. In the usability test, Telegram Bot obtained a SUS Score of 66 and an NPS of 12.195. These results show that Telegram Bot can be used as a real-time data collection tool, has good performance, and is well accepted by users.
End-to-End Motion Planning based on Multi-Task Learning for Mobile Robots

In order for mobile robots to move autonomously, collision avoidance is an essential capability. Thus far, end-to-end motion planners based on Deep Neural Network and Convolutional Neural Network have been proposed. However, robots based on these planners through imitation learning sometimes fail to avoid obstacles in unknown environments. This is due to generalization performance of the planners. In order to improve the generalization performance, we propose a novel motion planner based on DNN and CNN using multi-task learning. Through the experiments, we show the effectiveness of the proposed motion planner for collision avoidance by comparing the generalization performance of DNN and CNN.
Hubungan Antara Penggunaan Google Classroom Pada Pembelajaran Daring Terhadap Hasil Belajar Matematika Siswa Kelas IV-B SDN Kembangan Utara 012 Petang

This study aims to see the relationship between the use of Google Classroom on learning outcomes in mathematics at SDN Kembangan Utara 012 Petang. This research is a quantitative research using survey method. The population in this study were students of class IV-B SDN Kembangan Utara 012 Evening, totaling 30 students. The data collection technique used in this research is in the form of a questionnaire by distributing it through Google Form. This questionnaire was conducted to identify the relationship between Google Classroom and mathematics learning outcomes. The results of the research calculations with the partial test obtained tcount = 3.649 &gt; ttable 2.042 with a significance of 0.000 &lt;0.05, the result is that H1 is accepted and H0 is rejected, which means that there is a significant relationship between the use of Google Classroom on the mathematics learning outcomes of grade IV-B students at SDN Kembangan Utara 012 evening with a coefficient of determination of 67.8% while the remaining 32.2% is connected by other variables outside the study.