Reviewerly/exHarmony huggingface dataset:
A SAÚDE PÚBLICA E OS DESAFIOS PARA PROFISSIONAIS DE ENFERMAGEM DURANTE A PANDEMIA EM MANAUS

Amid the chaos, Manaus sees the worsening of the health crisis, caused by the new coronavirus pandemic, becoming a scenario of despair in the city's hospitals, due to the lack of oxygen to care for hospitalized patients, or even those who were at home, due to the lack of beds for hospitalization, leaving a trail of pain, fear and death. Nursing professionals, having to take turns every 20 minutes to perform manual ventilation, with an ambu bag or mask valve bag (BMV), which are not recommended, due to the high risk of contamination of the team itself. The Covid-19 pandemic changed the forms of interaction in the most diverse sectors of society, and it was no different with nursing professionals. Even more, in those who, during this process in Manaus, had to choose between life and death, of people who needed life support equipment, as vital as oxygen. Bringing deep marks that will be hard to forget.
Peer to peer (P2P) and cloud computing on infrastructure as a service (IaaS) performance analysis

The resources of information technology and the availability of services on non-cloud network systems are limited. This constitutes problems for companies, especially in the efficient management of information technology. The high investment in infrastructure procurement is an obstacle in building centralized systems, including the adoption of cloud computing through Infrastructure as a Service (IaaS), as an elective solution. This research aims to analyze the performance of cloud servers on IaaS services using the parameters of cloud service availability, resource utilization, and throughput transfer which were implemented in companies engaged in the toll road concession sector. Furthermore, the results are expected to be a reference in supporting company decisions/policies related to cloud system adoption. The methodology involved the Network Development Life Cycle (NDLC), a system constituted by 6 (six) stages of management, namely user, proxy server, database, web service, monitoring service, and Remote Desktop Protocol (RDP). The results of cloud service availability indicate that the cloud system provides service availability (system interface, broad network access, and resource pooling). Furthermore, cloud systems have a significant performance on resource utilization (CPU) and throughput transfer parameters, while non-cloud systems only excel in response time and resource utilization (Memory) parameters. The overall result analysis based on this research scenario showed that the cloud system provides services according to user needs and has a better speed in data transmission, but has shortcomings in response time.
Regular Class vs. Special Class: How Can They Differ in English Achievement and Technology Usage?

Providing educational programs provides specific opportunities for better student progress. MTs Negeri 1 Boyolali offers two kinds of programs that can be chosen according to the wishes, abilities, and goals. The two programs are the regular class program and the special class program. These two programs can highlight their technology usage and English learning achievement, considering they come from different programs. Therefore, this study aims to find out whether there are differences in English learning achievement or not between the two programs. This study uses ,a mixed method; statistically collecting and analyzing the students' final semester tests results, and interviewing the teacher and students to clarify some data. Besides, an additional intervies investigates further technology usage during English learning. The data shows differences in English learning achievement and technology usage between students from regular and special class programs. The research is expected to be limited to find the differences between the two classes and to contribute ideas to all related education implementers. Ultimately, regular class students will have English skills that are not much different from students in special classes.
The Role of Teacher Pedagogic Competence in Strengthening Discipline of Indonesian Language Learning at Elementary School

This article aims to determine the competence of teachers in learning Indonesian in order to strengthen the discipline of third grade students at Elementary School of Islam Nadindra Bekasi City. This study used a descriptive qualitative approach. The data of this research were taken from the third grade teacher of Elementary School Islam Nadindra. The results of this study concluded that the pedagogic competence of the third grade teacher of Elementary School Islam Nadindra was good enough to discipline the third grade students. It can be seen from the activities during teaching and learning in class. The pedagogic competence of teachers in the learning process was also very influential on student discipline when learning online. The teachers who have good pedagogic competence tend to be successful in learning activities, especially learning Indonesian. Meanwhile, teachers who have low pedagogic competence tend did not to succeed in learning activities.&#x0D; Keywords: Pedagogic Competence, Indonesian Language Learning, Strengthening Dicipline
Designing Augmented Reality Book for Improving Practical Skill in Scout Education Course

It is important to look at the element of skill in scout learning. This research aims to produce scout teaching books with the help of augmented reality that can improve students&#x0027; practical skills in scouting education subjects. This research used ADDIE model development research. This research is aimed at elementary school teacher education students in general who take scouting education courses. Based on the results of the analysis obtained the results of expert validation tests of 90.31 &#x0025; which belong to the category is very valid. Therefore, related to these results, this book can be used for scouting education learning by improving the practical skills of elementary school teacher education students
Study on the Properties of Water Molecule at Different Temperatures

Abstract Using computers as tools to perform molecular dynamics simulations from a microscopic point of view to explain macroscopic physical phenomena has become mainstream. This article discussed the properties of water molecules at different temperatures from the perspective of molecular dynamics simulation. In terms of general physical properties, this article investigated the trend of water viscosity and thermal conductivity with temperature by collecting and comparing existing literature data. The conclusion is that the viscosity decreases with increasing temperature, and the thermal conductivity increases with increasing temperature. In terms of special properties, this article took the hydrogen bond of water as the research object, and made a comprehensive analysis from three aspects of hydrogen bond length, hydrogen bond angle, and the hydrogen bond coordination number, which includes data analysis of existing literature and molecular dynamics simulation analysis. The latter used “Moldy” to perform three molecular dynamics simulations on water molecules at different temperatures, and imported the simulation results into “Vmd” for visual analysis. The results were compared with the existing literature data, and the conclusions were almost the same. That is, as the temperature increases, the hydrogen bond length becomes slightly longer, the hydrogen bond angle becomes smaller, and the hydrogen bond coordination number becomes less.
Website-Based Information System on Drug Purchases and Sales at Pharmacy

Pharmacy is a company that engages in the field of drug supply. In general, the system that runs at the pharmacy is still performed manually, starting from recording transactions, stocks checking, drug stocks data processing and recording, transaction calculation process, and the process of making reports. The fact that these processes were done manually makes the process to be not optimal. The purpose of this research is to determine the problems faced by the current system and propose a system design. Then, test the system and finally implement the information system on drug purchases and sales at the pharmacy. The method used a structured development method as well as the Waterfall method as a software development method. The results of this study present a drug purchase information system at a pharmacy to help facilitate the sale and purchase of goods from the pharmacy to the customer and supplier. With a drug purchase information system, pharmacies can minimize transactions that are done manually so that they can be upgraded to be computerized. By implementing the information system on drug purchases and sales at the pharmacy, it is expected to be able to overcome the problems faced by the current system at the pharmacy in order to be able to maximize the transaction process and to increase revenue from the pharmacy
Professional Training of Future Foreign Language Teachers: Socio-Cultural Aspect

The article examines socio-cultural aspect of professional training of future foreign language teachers. The purpose of the article is to substantiate the pedagogical conditions and structural and functional model of the socio-cultural competence formation of future foreign language teachers in the system of the pedagogical college. The main task of the study is to determine the structure, criteria, indicators and levels of socio-cultural competence of future foreign language teachers and to develop a structural and functional model of formation of their socio-cultural competence and its experimental verification. The research hypothesis lies in the assumption that the effectiveness of the socio-cultural competence of future foreign language teachers in the process of professional training in the pedagogical college will increase with the implementation of the following pedagogical conditions: the use of integrated socio-cultural tasks with variable content and innovative teaching methods. The formulated structural and functional model of sociocultural competence formation among future foreign language. The author's contribution to the development of the scientific field lies in the fact, that the use of interactive teaching methods encourages students to feel like subjects of socio-cultural competence and be active participants of this process. And this subjective position contributes to the development of cognitive motivation for socio-cultural competence, which contributes to the effective acquisition of socio-cultural knowledge and the effectiveness of the socio-cultural competence formation in general.
Recognition of Studied Words in Perceptual Disfluent Sans Forgetica Font

The new Sans Forgetica (SF) typeface creates perceptual disfluency by breaking up parts of letters vertically, horizontally, or diagonally, thereby fragmentizing them. While patterns of fragmentization are consistent for each unique letter, they are not uniform across letters. With Gestalt principles such as good continuation and perceptual completion being more difficult to implement in these settings, viewers may need to depend on context clues to identify words. This may be a desirable difficulty and improve memory for those words. Here, we investigate whether SF improves recognition of studied words. In Experiment 1, participants studied words in Arial and SF and completed old-new recognition tests where words retained their study fonts. In Experiment 2, we investigated the potential for context reinstatement-testing studied words in their studied fonts or the other font. Hit rate and discrimination sensitivities (d') were analyzed for both experiments. Participants had significantly better recognition (hit rate) in SF than in Arial (Exp 1) and significantly higher discrimination sensitivities (d') when words were tested in SF than in Arial (Exp 2). However, further examination of these results (e.g., marginally more response bias with SF than with Arial in Exp 1) lead us to hold reservations for the benefit of SF on word memory and conjecture that SF, at best, plays a limited role in improving recognition of studied words.
Experimental study on image stitching of blade-shaped hole

Starting an experiment about image stitching of blade-shape hole. Firstly, Focusing on algorithms of feature point detection. Harris, SIFT, and SURF are the main feature point detection algorithms. All of them are used to detect feature points on the same image, and analyze the precision of it and time-consuming. Then compare algorithm of the points match (brute force and KNN, brute force and crosscheck, K-D tree and KNN) by SSIM and line profile. Image fusion is determined based on pixel weighting, and transformation matrix is gained by RANSAC. Last, the system uses the Harris algorithm to detect feature points, and uses brute force and the KNN algorithm to match them. Verify the algorithm of blade-shaped hole image stitching is effective, and lay foundation for the next work of this project.
An adaptive nonlinear filter with missing measurements compensation for manoeuvring target tracking

To solve the problem of missing measurements in highly manoeuvring target tracking, an expected-mode-augmentation-based unscented Kalman filter with missing measurements compensation (EMA-MMCUKF) is designed based on the variable-structure multiple model method. In the proposed EMA-MMCUKF, the random missing measurements are described by the Bernoulli distribution, and the one-step prediction is used as the compensation. Based on the proposed EMA-MMCUKF, a Bayesian estimation-based expected-mode-augmentation unscented Kalman filter with missing measurements compensation (BE-EMA-MMCUKF) is proposed for adaptive estimation of the sensor measurement reception rate, where the unknown measurement reception rate can be estimated by fully utilising prior information. Simulation results demonstrate that the proposed EMA-MMCUKF can effectively track the manoeuvring target at different measurement reception rates. Moreover, when the sensor prior information differs significantly from the true measurement reception rate, the proposed BE-EMA-MMCUKF can effectively estimate the unknown sensor measurement reception rate and improve the accuracy of manoeuvring target tracking compared with non-estimation of the sensor measurement reception rate.
An Improved Hybrid DCT-DWT Blind Watermarking Technique for Securing Multimedia Images

Abstract People are capable of manipulating and copying digital images. Protection and security must be given to the right property from piracy and illegal copies. To safeguard the intellectual property of digital images digital watermarking is used as a solution. Watermarking technique is prevalent due to an effective copyright protection method i.e., only the rightful owner can identify the signature that is embedded in a digital document. In this paper, a blind watermarking scheme is used which is dependent on the image content of certain specific DWT-DCT coefficients. The use of generalized Gaussian distributions helps in modelling the DCT-DWT coefficients of the Source image. The suggested system attained optimal PSNR, MSE and SSIM values and numerous attacks are resisted by an embedded watermark in the image watermarked as per the results of the experiment. Furthermore, the suggested system depicts far more robustness against numerous image processing attacks for example, scaling to 0.25 &amp; 0.50, Cropping, and various types of noise attacks. Experimental results and numerical values of parameters confirms that the hybrid DCT-DWT blind watermarking technique is relatively efficient and also justifies the theoretical analysis.
Novel approach for pedestrian unusual activity detection in academic environment

&lt;span&gt;In this paper, we propose an efficient method for the detection of student unusual activity in the academic environment. The proposed method extracts motion features that accurately describe the motion characteristics of the pedestrian's movement, velocity, and direction, as well as their intercommunication within a frame. We also use these motion features to detect both global and local anomalous behaviors within the frame. The proposed approach is validated on a newly built proposed student behavior database and three additional publicly available benchmark datasets. When compared to state-of-the-art techniques, the experimental results reveal a considerable performance improvement in anomalous activity recognition. Finally, we summarize and discuss future research directions.&lt;/span&gt;
CPGCN: Collaborative Property-aware Graph Convolutional Networks for Service Recommendation

Collaborative filtering (CF) recommendation methods usually suffer from data sparsity and the cold start problem. An effective way to deal with these problems is to add side information such as knowledge graph (KG). However, the existing knowledge-aware recommendation methods cannot separately and accurately model users' interest preferences and services' property characteristics, uniformly termed as property features in this paper. They also rely too much on semantic information of KG and ignores the collaborative information between users and services which plays an important role in CF-based methods. To address these issues, we propose an end-to-end model called Collaborative Property-aware Graph Convolutional Networks (CPGCN) to learn the fine-grained property features. Firstly, the user-service collaborative information is fused with the semantic information of KG to construct Collaborative Property-aware Graphs (CPG). Then property features are learned by one kind of effective variant of graph convolutional neural network (GCN) in recommendation scenario. In order to reflect the differences among users and services, a relevance-attention network is proposed to aggregate these property features. Through extensive experiments on real-world service scenarios, we have confirmed the superiority of CPGCN compared with other state-of-the-art models. Each module in CPGCN is also confirmed to play an indispensable role in recommendation.
IMPLEMENTASI TENSOR FLOW LITE PADA TEACHABLE UNTUK IDENTIFIKASI TANAMAN AGLONEMA BERBASIS ANDROID

Aglonema or sri fortune has various types with various shapes, patterns and colors. Various types and more and more due to the many crossing processes carried out by owners and lovers of aglonema plants. For ordinary people who do not have insight into aglonema, it will be difficult to distinguish aglonema plants because the shapes, patterns and colors have similarities. It takes a Teachable Machine system with a complex but more sophisticated method that is able to recognize plants with a higher level of accuracy. The machine learning process is carried out on a computer to identify image data into classification results in the form of predictions. Tensorflow lite is a machine learning library specially designed for object recognition. Therefore, researchers are encouraged to create an Android-based mobile application that is able to recognize aglonema plants quickly, easily and accurately.
ENHANCING THE LEARNING OUTCOMES IN ENGLISH COURSE MATERIAL WITH PASSIVE VOICE THROUGH THE APPLICATION OF THE WINDOW-SHOPPING LEARNING MODEL

This research aims to improve the learning outcomes of English Subject Subjects with Passive Voice by applying the Window-shopping learning model to class IX E students of SMP Negeri 5 Banjarmasin Odd Semesters in the 2021/2022 Academic Year. It was in two cycles: planning and implementing the action, observing (observation), and reflection. Data were collected through observation, tests, and documentation and then analyzed descriptively by percentage. The results showed an increase in English learning outcomes for passive voice in Class IXE students at SMP Negeri 5 Banjarmasin through the window-shopping learning model. It can be seen from the increase in student learning outcomes from the pre-cycle, first, and second cycles. Its average value in the pre-cycle was 63.4, increased to 68.3 in the first cycle, and increased again in the second cycle to 74.
Explainable Artificial Intelligence (XAI): A reason to believe?

Artificial intelligence is an alluring technology which companies and governments hope to benefit from. In many circumstances a condition of its use is that humans can understand an explanation of why the action of an AI system took place. This has encouraged the development of a field of “explainable artificial intelligence”, or XAI. Much of the work in this field has been encouraged by the US Defense Advanced Research Projects Agency (DARPA), through its XAI program initiated in 2016. This paper argues that an underacknowledged challenge of XAI is that unlike most traditional technology, many AI systems contain inherent uncertainty. These systems are widely described as “black boxes”, and can be described only through their behavior, a technique described in the literature as post-hoc, rather than through an understanding of their functioning. Explaining such systems is akin to explaining the functioning of the natural world, rather than explaining the functioning of a known technology. While extensive work has been undertaken to explain the behavior of black box AI systems, there are limitations to the certainty that a post-hoc method can bring. Recognizing this is an important part of understanding the limitations of post-hoc reasoning in the use of advanced AI systems. Far simpler technologies have been seen to cause significant social damage: the UK Post Office Horizon system, and the Australian federal government Robodebt program. Coming to advanced AI system examples, two recent prestigious reports on AI systems and law display an unreasoned enthusiasm for AI explainability. AI researchers should be acknowledging that many advanced AI systems remain black boxes, that post-hoc explanations of these are inferences describing how the AI system may function, not how it does function, and the application of these technologies should be managed accordingly. Otherwise, the search for explanations may simply become a reason to believe.
Implementation of Enterprise Architecture in Cloud Computing Companies

In the current era of digitalization, the cloud computing industry market is increasingly shining along with the birth of a number of renewable technologies in this industry. A good and well-planned architectural design for the cloud industry is a major factor in the success of cloud computing companies in competing in a market that has a very broad market share. By conducting research on enterprise architecture, a cloud computing company is expected to provide a different approach to exploring and planning a cloud computing company according to market needs so that it can help or provide different methods and designs that allow us to enter the business world. and business. cloud industry competition. in this digital age. Architectural design planning for companies engaged in the cloud computing industry can use several approaches and tools available in the field so as to simplify, save time and encourage new ideas and initiatives. To be able to achieve the expected goals, it is necessary to conduct several studies and research that is quite intensive so that it can provide significant results and impacts. This research is expected to be one of the means to present a cloud computing architecture that is able to compete in the market and as a whole becomes the concern of all users or researchers. This study aims to discuss Enterprise Architecture related to Cloud Computing companies as providers of modern technology services. Provide information that the technology used is effective and cost-effective for industrial cloud service users. This study uses the TOGAF ADM method in conducting Enterprise Architecture.