Reviewerly/exHarmony huggingface dataset:
As ações do enfermeiro frente ao paciente com infarto agudo do miocárdio na urgência e emergência

The aim was to identify the actions of the nurse in front of the patient with acute myocardial infarction in urgency and emergency. This is an integrative review, using the bases of the Virtual Health Library, BDENF, LILACS, MedLine and SciELO. The research was carried out in May 2021 with a time frame from 2015 to 2020. After reading the articles and adopting the selection criteria, five articles were included and three categories were listed: The importance of risk classification in the care provided to patients with AMI, the difficulties of the nursing professional in the care of the patient with AMI and the favorable aspects in the care of the patient with acute myocardial infarction. It was found that nursing positively perceives the use of risk classification, protocols and guidelines as a way to make care safe and agile. It also identifies administrative difficulties to be overcome. On the other hand, they show that offering comfort measures are positive actions in the quality of care for patients with acute myocardial infarction.
А locally adaptive wavelet filtering algorithm for images

The algorithms based on the decomposition of a noisy image in an orthogonal basis of wavelet functions have been widely used to filter images (especially contrasting ones) over the past four decades. In this case, most wavelet filtering algorithms are of a threshold nature, namely: the decomposition coefficient smaller in an absolute value of a certain threshold value is reset to zero; otherwise the coefficient undergoes some (most often nonlinear) transformation. A certain (and very significant) drawback of threshold algorithms is that all coefficients of a certain decomposition level are processed with one identical threshold value (i.e., a constant value for all de-composition coefficients). This does not allow taking into account the “individual energy” of each decomposition coefficient for its more optimal processing. Therefore, we propose its own filtering factor for each coefficient, built on the basis of the optimal Wiener filtering and where a filtering parameter is introduced to compensate for incomplete a priori information on the value of the processed decomposition coefficients. In order to select a filtering parameter, a statistical approach has been proposed that makes it possible to estimate the optimal value of this parameter with acceptable accuracy. The performed computational experiment has shown the developed algorithm effectiveness for wavelet filtering of images.
Possibilities and Limitations of Basic Academic Skills Support Policy: Focusing on the 1st Comprehensive Plan for Basic Academic Skills Guarantee

이 연구의 목적은 2022년 3월 25일 시행된 기초학력 보장법을 비롯한 기초학력 향상 지원 정책의 가능성과 한계를 분석하는 것이다. 이를 위해 기초학력보장 종합계획 발표에 이르기까지의 정책 추진과정을 주요 시기별로 구분하고, 현행 기초학력 향상 지원 정책을 목표의 합리성과 수단의 적절성을 준거로 평가하였다. 분석 결과, 정책 목표의 합리성 측면에서 기초학력 향상 지원 정책은 지원대상 선정의 자율화와 탄력성을 강조하고, 현실성 있고 현장 수용도가 높은 목표치를 설정했으며, 국민적 요구가 높은 기초학력 보장에의 국가 책무성을 확대하였고, 정책체계의 안정성과 공공가치를 유지한 것으로 나타났다. 수단의 적절성 측면에서는 국가수준의 기초학력 진단 도구를 마련하고, 협력수업을 운영하면서 협력교(강)사의 질적 수준을 보장하고자 하고, 학습종합 클리닉을 전담기구로 운영하고, 시도 기초학력지원센터를 지원조직으로 두는 등 사업 수행 방식을 다각화하였다고 평가하였다. 이러한 정책 분석결과를 통해 얻은 시사점을 기초로 기초학력 향상 지원 정책의 발전방향을 제시하였다.The purpose of this study is to analyze the validity of basic academic skills support policies, including the Basic Academic Skills Guarantee Act, which was enforced on March 25, 2022. This study classified the policy promotion process leading up to the announcement of the comprehensive plan for guaranteeing basic academic ability by major period, and evaluated the current basic academic skills support policy based on the rationality of the policy goal and the appropriateness of the policy method. The basic academic skills support policy emphasizes autonomy and flexibility in selecting support targets. The stability of the policy system and public value were maintained. A tool for diagnosing basic academic ability at the national level was prepared, and the need to ensure the quality level of partner teachers was considered. Based through these policy analysis results, this study identified the rationality of goal and appropriateness of method of the basic academic skills support policy were identified, and suggested the development direction of the policies.
LEVERAGING AI-BASED INTERVENTIONS TO ADDRESS CYBERBULLYING AMONG CHILDREN: A RIGHTS-BASED PERSPECTIVE

One in three Internet users worldwide are children, and yet children are still insufficiently consulted on Internet governance-related matters as well as with respect to safety design decisions in online environments. Following the adoption of the general comment on the application of UN Convention on the Rights of the Child (UNCRC) in digital environments, this article presents the results of empirical research that solicited children’s input on proposed design of artificial intelligence-based interventions into cyberbullying incidents on popular social media platforms. The article presents the results from interviews and focus groups with 12–17-year-old children from Ireland regarding desirability and effectiveness of proposed interventions; as well as how these affect their rights to safety, privacy and freedom of expression.
LEVERAGING OR EXPLOITING? BREAKING THROUGH DATA COLONIALISM AND ETHNOCENTRISM WHEN BUILDING A DIVERSITY-AWARE SOCIAL PLATFORM.

The extractive logic of data-driven technology and knowledge production has raised serious concerns. While this discourse initially focused on the impact on Western societies, attention is increasingly turning to the consequences for countries and communities in the (Global) Souths. Criticism has mainly focused on the activities of the private sector. In this paper, however, we argue that publicly funded knowledge and technology production projects must also be examined through the lens of this critique. A research project designing and prototyping a diversity-aware social platform with pilot sites in China, Denmark, the United Kingdom, India, Italy, Mexico, Mongolia, and Paraguay is taken as a use case to ask the question: What do we need to do to meet diverse needs and develop innovative knowledge and products that benefit partners from the South and North alike? Our goal is to identify key efforts that are required to break the prevailing cycle of data colonialism and ethnocentric design. We present data from four different pilot sites and reflect on the original concept, as well as progress and results achieved to date. We then compare the experiences and draw five lessons that we believe will help future projects foster more equitable collaboration and achieve outcomes that benefit diverse local communities.
Intervención Educativa: prevención de COVID-19 en una asociación de vivienda, Banda de Shilcayo, San Martín, Perú

Introduction: COVID-19 is an infectious disease caused by the new coronavirus, its peculiarity is to transmit rapidly from person to person, through droplets, which are expelled through the mouth or nose when the person breathes in or out the oxygen in the air, reason for which it is essential to apply the measures of hand washing with soap and water, the use of masks, physical and social distancing in the inhabitants. The lack of knowledge about the prevention of COVID-19 has caused the accelerated increase in cases, causing it to occur, hospitalizations, deaths, in addition to expenses and problems of discrimination against those who are carriers of the disease. Objetive: Determine the influence of the Educational Intervention to prevent COVID-19 in the inhabitants of the "Amplification La Victoria" Housing Association of the district of the Banda de Shilcayo 2021. Materials and methods: It has been made a quasi-experimental study, before-after type without a control group, was carried out through an educational intervention to the inhabitants of the&nbsp; Housing Association of the Banda de Shilcayo district during the period from June to December 2021. The&nbsp; study was made up of the 150 inhabitants of the Housing Association. We worked with 100% of the population Results: It was observed a significant increase in the level of high knowledge was observed after the educational intervention about the disease (54%), healthy lifestyles (96.7%) and prevention measures (100%) Conclusions The educational intervention was effective because a high level of knowledge was achieved in the inhabitants of the Housing Association
A Recurrent Point Clouds Selection Method for 3D Dense Captioning

3D dense captioning provides descriptions for corresponding objects in 3D scenes represented as RGB-D scans and point clouds. However, when generating a description, existing methods select points randomly from a point cloud regardless of importance, which degrades the quality of the description by removing important points or including low-value points. To solve the above problem, we propose a recurrent point clouds selection (RPCS) method to mitigate descriptive deficiencies in 3D dense captioning by iteratively checking the caption results of the different point clouds. Our method is divided into two steps. On step 1, this work randomly selects cloud points and uses objectness score to evaluate the generated description. The objectness score indicates whether the proposed object is close to the ground truth; the higher the score, the closer the proposed object is to the ground truth in the positive value. On step 2, if the objectness score is lower than the threshold, step 1 is processed to generate another group of cloud points and evaluate the results. This loop stops when the objectness score is no longer reduced. The loop termination conditions are configurable according to the requirement of accuracy and processing time. As a result, our work can decrease the deficient descriptions and outperforms previous state-of-the-art methods by a large margin (6.58%~35.70% CiDEr, BLUE-4, METEOR, ROUGE improvement).
Convolutional Neural Network Based Hand Gesture Recognition in Sophisticated Background for Humanoid Robot Control

Hand gesture recognition is a preferred way for human-robot interactions. Conventional approaches are generally based on image processing and recognition of hand poses with simple backgrounds. In this paper, we propose deep learning models, and humanoid robot integration for offline and online (real-time) recognition and control using hand gestures. One thousand and two hundred of hand images belonging to four participants are collected to construct the hand gesture database. Five class (forward, backward, right, left and stop) images in six sophisticated backgrounds with different illumination levels are obtained for four participants, and then one participant's images are kept as testing data. A lightweight Convolutional Neural Network (CNN), and transfer learning techniques using VGG16, and Mobilenetv2 are performed on this database to evaluate user independent performance of the hand gesture system. After offline training, real-time implementation is designed using a mobile phone (Wi-Fi and camera), Wi-Fi router, computer with embedded deep learning algorithms, and NAO humanoid robot. Streamed video by the mobile phone is processed and recognized using the proposed deep algorithm in the computer, and then command is transferred to robot via TCP/IP protocol. Thus, the NAO humanoid robot control using hand gesture in RGB and HSV color spaces is evaluated in sophisticated background, and the implementation of the system is presented. In our simulations, 95% and 100% accuracy rates are yielded for the lightweight CNN, and transfer learning, respectively.
Perancangan Sistem Informasi Penjualan Air Galon Isi Ulang Di Kota Palangka Raya Berbasis Web

This system was built with the aim of being a medium of sales information for refilling gallon water depots and providing information for people who want to buy refill gallon water. With this system, it is expected to be useful as a medium for expanding information about refill gallon water depots, helping consumers to purchase gallons of refill water easily, and the purchase of refill gallon water can be done without the need for the charging depot location. The methodology used in the manufacture of "Refill Gallons of Water Sales Information Systems Design in the City of Palangka Raya Based on Web" is Waterfall According to Ian Sommerville, the Requirement Analysis and Definition, System and Software Design, Implementation and Unit Testing, Integration and System Testing, and Operation and maintenance. This methodology was chosen because every step of structured development was visualized, and clearly documented. At the analysis stage, data collection and needs analysis were made. At the design stage, Data Flow Diagram (DFD) and Entity Relationship Diagram (ERD) are made. At the implementation stage, the system is made using PHP and Javascript as a programming language, and MySQL as a database server. The test method used is the Blackbox Testing method. Test results using this Blackbox method from the analysis process until the implementation is obtained that the system can carry out data processing such as adding/saving, deleting, changing, and searching. Users can enter data and data can be processed and produce location, product, transaction, and report information. "Refill Gallon Water Sales Information Systems Design in the City of Palangka Raya Based on Web" is able to provide information needed by customers and visitors. In the system there are several features that can be used by the admin, operators, customers and visitors though. So that the functionality of this website is appropriate in accordance with the initial purpose of making the system, "Refill Gallon Water Sales Information Systems Design in the City of Palangka Raya Based on Web " can still be developed again.
CIS Society Officers

i all, As this issue is published, 2023 is well underway.I don't have a set theme for this message -I will just ramble along for a while writing about accomplishments, on-going activities, and plans for the Computational Intelligence Society.Not so original, eh? IEEE CIS has grown over the years in membership, structure, activities, and dreams, but we have operated with only one (albeit very talented) full time staff support for over 15 years.In the last few years, we were fortunate to add another talented part-time staffer, focused primarily on our electronic outreach: web, social media, email.Last year the AdCom let me stand up an AdHoc Committee to study our staff needs relative to both operational and strategic issues.After a careful and detailed analysis that included input from all of the CIS Vice Presidents, AdCom approved a motion to search for an Executive Director for the Society.
Research on SGX-based network adversarial host log highly trusted collection method

With the increasingly fierce offensive and defensive confrontation in cyberspace, security threats have spread to the field of network terminal equipment data monitoring and collection, and the problems of network terminal equipment data collection being damaged and tampered with under the offensive and defensive environment are prominent. To this end, this paper proposes an SGX-based network countermeasure host log highly trusted collection method, adopts SGX hardware-level protection technology as the security reinforcement means, and conducts research on log collection methods, transmission methods, and storage methods. In this paper, the SGX-based network countermeasure host log highly trusted collection system is designed with full consideration of the collection strategy for host logs of multi-operating system platforms. At the same time, not only the physical host collection scenario is considered in the scheme design, but also the host log collection task for virtual machines in the cloud platform with the continuous development of cloud computing, which greatly broadens the application scenario of this method and satisfies most of the network scenarios in reality.
Integration of Deep Direction Distribution Feature Extraction and Optimized Attention Based Double Hidden Layer GRNN Models for Robust Cursive Handwriting Recognition

Cursive handwriting recognition (CHWR) is an interesting area of research as it has a wide range of applications but lacks an accurate approach to provide better results due to its character shapes, the non-uniform spacing between words and within a word, diverse placements of dots, and diacritics, and very low inter-class variation among individual classes. A novel CHWR model is proposed to enhance the recognition accuracy with high global stability. The proposed model introduces three major phases: pre-processing, feature extraction and classification. In the pre-processing stage, the noise removal and binarization are adapted with the intrusion of improved adaptive wiener filtering (IAWF) and structural symmetric pixels. A hybrid deep direction distribution feature extraction (HDDDFE) approach is proposed to extract directional Local gradient histogram (LGH), column gradient histogram (CGH) features and a wavelet convolutional neural network with Block Attention Module (WCNN-BAM) is proposed to extract deep global features (GF), profile features (PF) and dynamic features (DF). A novel double hidden layer gated recurrent neural network with a feature attention mechanism (ODHL-GRNN-FAM) is proposed to offer handwritten classification results. The developed model is evaluated with the IAM database and attains an overall recognition accuracy of 98%, precision of 97%, f-measure of 97.99%, character error rate (CER) of 1.23%, word error rate (WER) of 4.8%, respectively.
Stability Analysis of Mathematical Model of Spread of Covid19 SEIRS Type with Constant Birth Rate

The Covid19 case dated 11 November 2021 recorded that the human population died from Covid19 (143,595 people) with confirmed cases (4,249,323 cases) and active cases (9,537 cases). Based on these data, it can be concluded that COVID-19 is an acute and deadly disease. In addition to deaths, due to Covid-19, namely the increase in divorce cases, decreased income in the economy and tourism. In this study, the author made a mathematical modeling of Covid19 type as an effort to prevent the spread of Covid19. In the modeling there are human populations susceptible to Covid19 , human populations have been vaccinated , human populations have not been vaccinated , human populations are exposed , human populations are infected with Covid19 , and human populations recovered from Covid19 . The research objectives are 1) to build a mathematical model of Covid19, 2) to determine the fixed point and basic reproduction numbers, and 3) to analyze the stability of the fixed point. This type of research includes applied science research. The research procedure is 1) observing real phenomena, 2) searching literature, 3) determining variables, parameters, and assumptions in mathematical modeling, 4) building a mathematical model of Covid19, 5) analyzing the Covid19 mathematical model in the form of fixed points, basic reproduction numbers, and fixed point stability. The results of the analysis 1) the mathematical model type has a fixed point without disease and an endemic fixed point, 2) a fixed point without disease is stable for the condition , and the endemic fixed point is stable for the condition .
Research on sign language gesture division and gesture extraction in complex background

Sign language plays an important role in information transmission and emotional communication between deaf-mute people and the outside world. With the development of artificial intelligence technology, the recognition, translation and generation of sign language based on digital image processing have attracted worldwide attention. In the field of sign language recognition, effective hand division and gesture extraction are the first and key steps, which directly affect the accuracy of sign language recognition. In this paper, a hand information extraction method based on depth image processing is proposed to solve the problem of sign language gesture extraction in complex background. For sign language speakers,hands are at the front of their bodies, so the depth images of sign language speakers can be collected by depth camera, and the complex background can be removed and hand information can be extracted by segmenting different color objects in the depth images. In this paper, the D435i camera of Inter is used to capture the depth image of the sign language speaker, and the HSV color space model based on the digital image is used for threshold processing of the fusion of hue components and brightness components to achieve the division of the hand position; through median filtering and mathematical morphology of digital image, division noise is removed and interference is reduced. Through skeleton extraction algorithm, the gesture gesture can be obtained. Experiments show that the proposed acquisition scheme and algorithm flow in this paper can effectively realize hand position division and gesture extraction in complex background conditions, and provide a good foundation for subsequent gesture recognition and expression.
Sedimentology and Mineralogy of Sedimentary Sequences in Nanim Field in the Niger Delta basin, Nigeria.

A total of nineteen ditch cuttings from the sedimentary sequence of Nanim Field, were subjected to both sedimentological and mineralogical analysis with the aim of investigating the mineralogical composition of the studied section (1810 m - 2650m) in the study area. The shale samples were grinded, pulverized and sieved with less than 75μm and analyzed using X-ray diffraction techniques (XRD) for mineralogical composition. Results of the sedimentological analysis, suggests four lithofacies made up of sandstone, shaly sand, shale and sandy shale in he studied section. The studied section has been interpreted as a shallow marine environment &nbsp;divided into two broad lithofacies sequences made up of beach sand (1810 m - 2290 m.) and upper shoreface (2300 m – 2650m) respectively. The beach sand sequences comprises thick sands, brownish, grey to black, fine to coarse grained, whereas the upper shoreface sequence is essentially a heterogeneous sequence of alternating sand medium to very fine grained sand and shale - grey. Results from the XRD analysis shows that the mineralogical composition of the basal part (upper shoreface) of the studied section is characterized by kaolinite a dominant in sediments of fluviatile environments and is known to concentrate in many near-shore sediments (shallow marine) with a decrease in abundance from the shoreline as other clay minerals increase basinward.
Augmented Reality Based on Discovery Learning: The Human Circulatory System to Improve Biological Literacy

To produce Augmented reality learning media products based on Discovery learning on circulatory system material, assessing the feasibility and effectiveness of Discovery learning based Augmented reality learning media products on circulatory system material in the learning process of class XI students at SMA Plus Sedayu Nusantara. This research is a Research and Development (R &amp; D) development research with the ADDIE development model. Subjects included 2 material experts, 2 media experts, 3 students in the individual test, 9 students in the small group test, and 30 students in the limited field test. The results showed that: Augmented Reality learning media based on Discovery Learning on the circulatory system is very suitable to be used as a learning resource in learning material for the Circulatory System Class XI SMA; Discovery Learning-based Augmented Reality learning media on the circulatory system is very effective in use, testing the effectiveness of Discovery Learning-based Augmented Reality learning media products on the circulatory system fulfills the criteria of being effectively used which is shown from the results of product effectiveness testing using the t-test on different independent test tests. The average result of the assessment in the experimental class was that the average score of the learning outcomes test was higher than the average result of the control class students who did not use learning media.