Reviewerly/exHarmony huggingface dataset:
Capacitação interprofissional sobre insulinoterapia para agentes comunitários de saúde: relato de experiência

Diabetes Mellitus is a chronic-degenerative disease, which consists of an increase in serum glucose concentration or a deficit of insulin for systemic glycemic control. The Community Health Agents are part of the Family Health Strategy, the gateway to Primary Health Care, where they have a very important role in guiding and educating the health of these patients, being the main link between the health team and the community. The present work is an experience report about the training on insulin therapy for CHA of regional II, in the city of Fortaleza, Ceara, carried out between the months of September to October 2019, with the participation of 139 CHA. We use as a theoretical framework for training, the problem solving method of Arco de Maguerez, which has teaching-learning strategies for the development of problematization. There were four stages in each meeting that consisted of the active participation of the CHA for a close look at reality. We observed gaps in the knowledge of the CHA about the care for people using insulin, for example: notions about preventive care for diabetic foot and its complications; differences between types of insulin; the importance of proper handling and storage. There was a collective construction of knowledge during the course of the meetings, contributing to greater training of CHWs in relation to the theme and an understanding by students and professionals who conducted the training on information that is part of the popular culture of patients. This experience provided the CHA with the construction of new knowledge about caring for people with DM in insulin therapy to transform reality, based on a methodology that enabled didactic, dynamic and reflective training.
조선전기(朝鮮前期)에 간행(刊行)된 중국고전문헌(中國古典文獻) 고찰 ― 『고사촬요(攷事撮要)』를 중심으로

According to 『攷事撮要 kǎo-shi-cuō-yao』, the total number of Chinese Classical Books confirmed at early days of the Joseon Dynasty are about 640 copies. Among them, there are 211 copies of domestic books, 319 copies of Chinese books, and 110 copies unidentified. In addition, Chinese books are divided into 『經史子集 jīng shǐ zǐ ji』. It turned out to have 78 copies of 經部 (jīng bu), 34 copies of 史部 (shǐ bu), 137 copies of 子部 (zǐ bu), and 70 copies of 集部 (ji bu). Furthermore, some of the Chinese books were re-selected to Chinese classical literature, classifiedinto poetry, prose, fiction, and etc by genre for consideration.Although, some of the woodblocks catalog at 『攷事撮要 kǎo-shi-cuō-yao』 are lost or omitted during the early days in Joseon Dynasty. Nevertheless, it made a huge influences and literary value of the Joseon Dynasty are believed to have been significant. It is noteworthy that Chinese books were published as editions by Joseon woodblocks. There are considerable significance of Korea and China publication cultural exchange, because some of the materials in Korea are rare and precede current Chinese materials.
Celebrity Endorsements – The Interplay between Intellectual Property Law and The Consumer Protection Act, 2019

The ambit of Copyright law has expanded over time, leading to development of newer concepts such as, Personality Rights‘. These rights are vested in individuals who have acquired an identifiable persona‘ in the eyes of the public. There are two important facets to personality rights- Right to Publicity &Right to Privacy. When such identifiable identities use their acquired celebrity status to promote goods and services of a company to attract more consumers, it can be understood as ‗Celebrity Endorsements‘. This is the most common source of marketing used by major companies to increase sales and garner goodwill and reputation. However, this source of communicating necessary information to the public becomes dangerous when celebrities promote false or misleading advertisements. To counter such issues, the Consumer Protection Act, 2019 introduced provisions to hold celebrities endorsing such products or services to be liable for injury suffered by consumers. The Law mandates that in order to ensure that such misleading advertisements aren‘t promoted, the celebrities must conduct ‗due diligence‘ of the products before endorsing them. However, the question remains that to what extent can celebrities, who are not directly involved in production or manufacturing, be held liable for exploiting their personality rights? This paper aims at addressing the newly created legal interlink between personality rights via celebrity endorsements and protection of consumer interests.
국제인권법의 지평에서 본 우리 소년사법의 과제

Many international standards, including the Convention on the Rights of the Child, specify that children should be guaranteed the right to freedom and participation in the juvenile justice process. The justification for special treatment of children is derived not from the fact that children's crimes should be treated simply generously, but from the unique characteristics and rights that children have. In other words, the protection of children assumed by international standards, such as the Convention on the Rights of the Child, means that the disposition should be made individually considering their personality and environmental characteristics while fair procedures are guaranteed. International standards also stress that children's human rights should not be unfairly violated in the process.Since Korea has joined the Convention on the Rights of the Child, it should comply with international standards on human rights in the operation of juvenile justice and in the legislation of relevant laws. From this point of view, it is necessary to unify juvenile protection procedures and criminal procedures, and to operate a permanent consultative body consisting of several agencies. It should also expand opportunities for children to be assisted by counsel and ensure that children and guardians have the right to participate in juvenile justice procedures. At the same time, child detention should be minimized and children should not be detained in the same facility with adults.
Multi-Faces Recognition in Crowd Using Support Vector Machine on Histogram of Gradient

Face recognition plays massive role in the biometric identification. On behalf of its usability, face recognition is developed more advanced in term of the accuracy. The use of face recognition as biometric identification varies from security surveillance to business purposes. However, the existing methods for face recognition are mostly for close distance and single face purpose only, meanwhile the demand for face recognition has come into recognizing multi faces in a certain crowdy place. Thus, it is required to select the most suitable approach in order to face this challenge. This study proposes Support Vector Machine (SVM) as the classification method and Histogram of Gradient (HoG) as the feature extraction of the image. This study is expected to give the best recommendation for developing multi face recognition in crowd considering the accuracy given by the proposed method. The result of efficiency and performance is shown by the simulation and analysis.
Efficient parameter-free adaptive penalty method with balancing the objective function value and the constraint violation

Real world problems are often formularised as constrained optimisation problems (COPs). Constraint handling techniques are important for efficient search, and various approaches such as penalty methods or feasibility rule have been studied. The penalty methods deal with a single fitness function by combining an objective function value and a constraint violation with a penalty factor. Moreover, the penalty factor can be flexibly adapted by feeding back information on search process in adaptive penalty methods. However, setting parameters properly and keeping the good balance between the objective function value and the constraint violation are difficult. In this paper, we propose a new parameter-free adaptive penalty method with balancing the objective function value and the constraint violation. L-SHADE is adopted as a base search algorithm, and the optimisation results of 28 benchmark functions provided by the CEC2017 and CEC2018 competitions on constrained single-objective numerical optimisations are compared with other methods.
Crossing the threshold: Digital cataloguing practices, some thoughts

Digital cataloguing practices carried out by libraries, particularly public libraries, present a number of critical issues, that the Covid-19 contingency has greatly emphasised. Criteria adopted to identify and to describe digital reproductions of analogue publications, as well as native digital editions, appear to be inconsistent and misleading. So far cataloguers have acted on the assumption that digital reproductions have the same features of xeroxes, microfilms or microfiches. New software tools, combined with the greater flexibility of digital files, imply that differences existing between the two media should require a different treatment in terms of cataloguing. Characteristics specific to digital objects deserve to be described with the same care as those of analogue publications in the first place because they have an impact on the way readers can make use of them, and secondly because they could be used as search keys, especially as query facets. Another area of concern is the development of descriptive standards aimed at bringing into the catalogue resources of a different nature from bibliographic items. The reason for doing so is the idea of turning the catalogue into part of the semantic infrastructure of the web. Having given insufficient consideration to cataloguing principles and to catalogue functions, in favour of a more pragmatic approach, is threatening to strip the catalogue of its substance, encouraging at the same time the replacement of library services with those offered by subjects not sharing the same cultural and social goals. © 2020 Associazione Italiana Biblioteche. All rights reserved.
Multi-hop Attention based Graph Neural Network

Self-attention mechanism in graph neural networks (GNNs) led to state-of-the-art performance on many graph representation learning tasks. Currently, at every layer, attention is computed between connected pairs of nodes and depends solely on the representation of the two nodes. However, such attention mechanism does not account for nodes that are not directly connected but provide important network context. Here we propose Multi-hop Attention Graph Neural Network (MAGNA), a principled way to incorporate multi-hop context information into every layer of attention computation. MAGNA diffuses the attention scores across the network, which increases the receptive field for every layer of the GNN. Unlike previous approaches, MAGNA uses a diffusion prior on attention values, to efficiently account for all paths between the pair of disconnected nodes. We demonstrate in theory and experiments that MAGNA captures large-scale structural information in every layer, and has a low-pass effect that eliminates noisy high-frequency information from graph data. Experimental results on node classification as well as the knowledge graph completion benchmarks show that MAGNA achieves state-of-the-art results: MAGNA achieves up to 5.7 percent relative error reduction over the previous state-of-the-art on Cora, Citeseer, and Pubmed. MAGNA also obtains the best performance on a large-scale Open Graph Benchmark dataset. On knowledge graph completion MAGNA advances state-of-the-art on WN18RR and FB15k-237 across four different performance metrics.
A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep Learning.

To ensure the privacy of sensitive data used in the training of deep learning models, a number of privacy-preserving methods have been designed by the research community. However, existing schemes are generally designed to work with textual data, or are not efficient when a large number of images is used for training. Hence, in this paper we propose a lightweight and efficient approach to preserve image privacy while maintaining the availability of the training set. Specifically, we design the pixel block mixing algorithm for image classification privacy preservation in deep learning. To evaluate its utility, we use the mixed training set to train the ResNet50, VGG16, InceptionV3 and DenseNet121 models on the WIKI dataset and the CNBC face dataset. Experimental findings on the testing set show that our scheme preserves image privacy while maintaining the availability of the training set in the deep learning models. Additionally, the experimental results demonstrate that we achieve good performance for the VGG16 model on the WIKI dataset and both ResNet50 and DenseNet121 on the CNBC dataset. The pixel block algorithm achieves fairly high efficiency in the mixing of the images, and it is computationally challenging for the attackers to restore the mixed training set to the original training set. Moreover, data augmentation can be applied to the mixed training set to improve the training's effectiveness.
The INVESTIGATION OF GRAMMATICAL ERROR IN STUDENT’S ENGLISH WRITING AT UIN RADEN INTAN LAMPUNG AS BASIS FOR LEARNING MATERIAL DEVELOPEMENT

This research aims to investigate students's grammatical errors (morphological and syntactical) on phrase and clause level in English essay of UIN Raden Intan Lampung students’ as the basis for future learning material developement. Qualitative approach is used in this research. Research method which is used is descriptive qualitative with content analysis technique. Research data are words and sentences with morphological and syntactical error. In this research, interactive data analysis is used. The steps of the data analysis are data reduction, data display, and conclusion as well as verification. Validity of the data is done by using source triangulation. Based on the analysis and discussion result, there are several findings. The first is 3 types of morphological errors. They are noun, verb, and adjactive errors. The second is 5 syntactical errors. They are noun phrases (NP), verb phrases (VP), adverbial phrase (AvP, noun clause, and adjective clause errors. The third is the most dominant error (verb use error). There were 56 verb errors out of 107 total errors. Keywords: Grammatical error, morphology, syntax, qualitative research
Analisis Kesalahan Morfologis pada Karangan Narasi Ekspositoriik Siswa MTs N 2 Palu

In using language, both spoken and written, an underlying theory is needed. The scope of language errors includes errors in phonology, morphology, the field of syntax, and the field of EYD. However, the purpose of this study only focused on the field of morphology in describing misuse of use: prepositions, affixes, and dotted words in narrative essays of class IXA students at MTs Negeri Palu Barat. This research was a qualitative research which aims to understand the phenomenon of what the research subjects experience holistically and by means of descriptions in the form of words and language, in a special natural context and by utilizing various scientific methods. Data collection techniques used in this study were observation, interviews, and documentation of the implementation of activities. The subjects of this study were 29 students of class XI A MTs N 2 Palu. The results of the research on the analysis of morphological errors in the expository narrative essay of MTs Negeri 2 Palu students were: (1) the form of misuse of prepositions which are sequenced from the words that follow them, such as the word dipalu , the use of the prepositions should be separated from the words that follow as in the word di Palu ; (2) the form of the misuse of the affixation which is separated from the word that follows it as in the word di pilih , the use of the affixation should be linked to the word that follows it like the word dipilih ; and (3) the form of misuse of the word berklitik which is separated from the word that follows it, as in the word ku menangkan , the use of the word that follows it should rely on the word that follows it as in the word kumenangkan .
EFL High School Students’ Ability in Comprehending Short Stories

The objective of this research was to describe tenth graders’ ability in comprehending short stories text in SMA Negeri 1 Lage. This research was qualitative in nature. The data were collected from observation and documents. The result of this research shows that students increased their scores of comprehending narrative short stories after three meetings. Some suggestions are proposed in this article for future inquiry. Keywords: reading comprehension, narrative text, short stories
Parameters optimisation of support vector machine using modified grasshopper optimisation algorithm-based Lèvy-flight method

Grasshopper optimisation algorithm (GOA) is one of the most recent meta-heuristic optimisation algorithms. It was first developed by Saremi et al. in 2017. Although, GOA has shown good performance, it still has demerits with respect to low precision, slow convergence and easily stuck at local minima. This paper presents a modified version of GOA based on Levy-flight method, called as (LevyGOA). The proposed LevyGOA is proved to provide a better trade-off between exploitation and exploration, which makes LevyGOA faster and more robust than GOA. LevyGOA is further compared with other meta-heuristic optimisation algorithms and the basic GOA for solving two optimisation problems. These problems are global optimisation problem and parameters optimisation of SVM, where CEC 2005 and CEC 2017 global benchmark functions and six well-known benchmark datasets are used. The experimental results show that LevyGOA can significantly improve the performance of GOA. The results demonstrate that LevyGOA outperforms the other algorithms on a majority of the benchmark functions and benchmark datasets.
A Secure Cloud Authentication and Access Control System for Cloud Infrastructure

So as to shield the cloud condition from malicious users, we proposed a novel trust based access control model. This model approves the client dependent on client trust esteem, before accessing the cloud resources. The client must be trusted before accessing the resources and the resources must be trusted before offering the support to the client. In the event that the trust estimation of both client and cloud resource are more than their trust edge esteem, at that point they are viewed as trusted. Likewise, we convey the idea of Token Granting system that permits the users to confirm the accuracy of re-appropriated data without the recovery of the particular files. The tokens are gotten from the metadata containing file area that helps during the time spent storage accuracy check and ad libs the storage proficiency. Simulation results show that proposed model performs superior to comparable models as far as accuracy of result.
SecoArc: A Framework for Architecting Healthy Software Ecosystems.

In recent years, prominent software companies have succeeded to grow by creating ecosystems of third-party providers and users around their software platforms. The overall well-functioning of such ecosystems is referred to as ecosystem health that is the result of a complex and variable range of architectural design decisions at business and technical levels. Despite a body of work considering the architecture of software ecosystems, there is still a lack of solid methods with a precise foundation to facilitate architectural decision-making by providing automated techniques and tools. To fill this gap, we present SecoArc, which is a pattern-centric ecosystem modeling framework for architecting healthy software ecosystems. SecoArc makes the architectural knowledge of well-established ecosystems available. In this paper, we focus on the SecoArc modeling language, analysis technique, and a ready-to-use tool. SecoArc enables platform providers to design architectural variabilities, assess the architecture concerning the quality attributes of ecosystem health, and deeply compare several competing architectures. We show the application of the SecoArc framework in a case study.
LibGuides: COMM-105 Speech Sources: Citing Sources in MLA

This guide serves as a jumping off point for COMM-105 students who are researching and preparing to give an Informative Meeting Speech or a Speech to Actuate. For more help, contact your friendly neighborhood librarian!
DrishtiGyan - Proposed Design on Gaze based Content Evaluation

Real-time digitalisation helps digital marketers improve reader experience of the article. The need for realtime digital text content is increasing at a faster rate. The writer and the reader of the text articles play a major role in content digitalisation. In order to improve the quality of text being generated it is important that the writer gets genuine feedback of his creation. The proposed model uses gaze tracking and emotion detection of the reader to understand how appealing the writing of the article is. The text article is rated based on the reader’s experience and the overall result is given back to the writer as feedback.
Segmenting Messy Text: Detecting Boundaries in Text Derived from Historical Newspaper Images

Text segmentation, the task of dividing a document into sections, is often a prerequisite for performing additional natural language processing tasks. Existing text segmentation methods have typically been developed and tested using clean, narrative-style text with segments containing distinct topics. Here we consider a challenging text segmentation task: dividing newspaper marriage announcement lists into units of one announcement each. In many cases the information is not structured into sentences, and adjacent segments are not topically distinct from each other. In addition, the text of the announcements, which is derived from images of historical newspapers via optical character recognition, contains many typographical errors. As a result, these announcements are not amenable to segmentation with existing techniques. We present a novel deep learning-based model for segmenting such text and show that it significantly outperforms an existing state-of-the-art method on our task.
Blockchain-Based Financial Services and Virtual Currencies: United States

In this article, we analyze how the United States responds to blockchain technology, especially in blockchain-based financial services and virtual currencies. At the federal level, four different agencies have produced at least four different classifications of digital assorts—commodity, security, currency, and property. At the state level, only a handful of laws have been enacted, and numerous bills have been proposed. In addition, several court decisions have addressed the status of blockchain technology and smart contracts. Congress has provided some broad recommendations relating to blockchain and its applications. Overall, blockchain is seen as an exciting new technology, but virtual currencies have drawn skeptics worried about their speculative nature, volatility, and potential for consumer abuse.
AI & ML Based Approaches for Developing Shortest Efficient Motion Path Planning Algorithms for Autonomous Robots to Move from Source to Destination

In this paper  we develop some of the efficient motion path planning algorithms for autonomous robots to move from source to destination using AI & ML approaches using software-based tools such as python, c/c++, java, etc… Several training algorithms are going to be developed so that any type of obstacle could be avoided by the robot in its workspace. The purpose of the global path planning algorithm is to find the shortest path from the current position to a target position while avoiding obstacles given a known map.