Reviewerly/exHarmony huggingface dataset:
Annals Graphic Medicine - Attending on the Medicine Wards

Web Exclusives19 May 2020Annals Graphic Medicine - Attending on the Medicine WardsFREEZachary G. Jacobs, MDZachary G. Jacobs, MDOregon Health & Science University, Portland, Oregon (Z.G.J.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/G19-0036 SectionsAboutVisual AbstractPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Download figure Download PowerPoint Comments0 CommentsSign In to Submit A Comment Author, Article, and Disclosure InformationAffiliations: Oregon Health & Science University, Portland, Oregon (Z.G.J.)Disclosures: The author has disclosed no conflicts of interest. The form can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=G19-0036.Author/Illustrator Information: Zachary G. Jacobs, MD, is a hospitalist at Oregon Health & Science University. He uses creative writing, photography, and graphic arts to combine his two passions: healing and storytelling. To see more of his work, visit https://zgjmd.wordpress.com. E-mail: [email protected]edu; Twitter: @ZacharyGJacobs.This article was published at Annals.org on 12 May 2020. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics 19 May 2020Volume 172, Issue 10Page: W132-W133KeywordsConflicts of interestDisclosureHealth careHealth information technologyHospitalistsPhotography ePublished: 12 May 2020 Issue Published: 19 May 2020 Copyright & PermissionsCopyright © 2020 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...
A study of lexical usage differences between human and machine translation in English translations of Korean newspaper editorials.

This study aims to identify stylistic differences between human and machine translation in terms of word usage. For this purpose, a comparable corpus was constructed, which consisted of English translations of 110 Korean newspaper editorials done by a group of human translators and three online machine translation services (Google, Bing and Papago) respectively. Principal component analysis was performed on the corpus to investigate differences in the way 200 most frequent terms are related to the human and machine translators. Additionally, part-of-speech analyses were carried out to further elucidate the differences found in the PCA analysis. The major findings are that machine translators tend to overuse ‘be’ verbs and ‘as’ and ‘if’ subjunctive connectives, while underusing third-person personal pronouns, particularly the female form, ‘she’. Additionally, they were found to rely heavily on high-frequency content words. These characteristics of machine translators are construed as stemming from their scope of lexical options being limited by structural correspondence to original Korean texts.
Comparing the Efficiency of In Situ Visualization Paradigms at Scale.

This work compares the two major paradigms for doing in situ visualization: in-line, where the simulation and visualization share the same resources, and in-transit, where simulation and visualization are given dedicated resources. Our runs vary many parameters, including simulation cycle time, visualization frequency, and dedicated resources, to study how tradeoffs change over configuration. In particular, we consider simulations as large as 1,024 nodes (16,384 cores) and dedicated visualization resources with as many as 512 nodes (8,192 cores). We draw conclusions about when each paradigm is superior, such as in-line being superior when the simulation cycle time is very fast. Surprisingly, we also find that in-transit can minimize the total resources consumed for some configurations, since it can cause the visualization routines to require fewer overall resources when they run at lower concurrency. For example, one of our scenarios finds that allocating 25% more resources for visualization allows the simulation to run 61% faster than its in-line comparator. Finally, we explore various models for quantifying the cost for each paradigm, and consider transition points when one paradigm is superior to the other. Our contributions inform design decisions for simulation scientists when performing in situ visualization.
Intersecting the Quantum Future and the Semiconductor Industry (Conference Presentation)

Quantum computing has been a long-anticipated emerging computational paradigm to complement and compete with conventional CMOS technologies. The last decade has featured reports of the initial development of using CMOS processing techniques for qubits and the atomistic fabrication of single atom transistors. Will the semiconductor industry embrace this new architype, and if so, how? When quantum devices begin to scale as predicted, will our industry be ready to integrate radically different architectures and device structures? Are there known obstacles not yet addressed that would enable the industry to more readily adopt and benefit from today’s achievements in the laboratory? What are the emerging designs and the potential fundamental challenges that are to be overcome? We have assembled a panel of experts that will share their insights on the state-of-the-art in quantum computing as well as intellectual leaders that will share their vision of the eventual merger of these new technologies with our computing capabilities today, even as lithography is approaching the near-atomic domain. Join us as we discuss the impending critical impact of quantum computing on the semiconductor industry.
LibGuides: Library Tutorials: For specific courses

Online videos and step-by-step tutorials to use the Library resources and complete research assignments. Tutorials for specific classes or assignments
Klasterisasi Tingkat Kehadiran Dosen Menggunakan Algoritma K-Means Clustering (Studi Kasus Institut Agama Islam Batusangkar)

Non-Civil Servant Lecturers of Batusangkar State Islamic Institute (IAIN) are still manual in recording the presence of non-civil servant lecturers. This study aims to use an application to record the number of meetings conducted during the teaching and learning process by non civil servant lecturers who are able to study courses. The meeting data will be an assessment of the performance of non civil servant lecturers. Higher education quality assurance institutions can classify non-civil servant lecturer meeting data using Knowledge Discovery in Database (KDD). The next stage is to do data mining with the K-Means Clustering Algorithm. The results of this study grouping lecturers into 3 groups: 72 subjects taught by non-civil servant lecturers in the group rarely meet (4,7650%), 69 courses that are taught by non-civil servant lecturers in the group are in meetings (4,5665%), and 1370 subjects taught by lecturers non civil servants in the diligent group meeting (90.6684%). Based on the results of the study it was concluded that the academic year 2017/2018 odd semester and even non-civil servant lecturers supporting certain subjects diligently entered at each meeting with attendance rates of 12-16 times meetings per semester.
Pelatihan Penulisan Artikel Ilmiah bagi Mahasiswa Pendidikan Biologi FPMIPA IKIP Mataram

The objectives of this service activity are: (1) increasing student knowledge about the ins and outs of writing scientific papers and scientific articles , and (2) improving the ability to write scientific articles among students of Biology Education FSTT Undikma Mataram. Community service activities were carried out for 2 days, with 3 stages of activities, namely: (1) Introduction, (2) core activities, and (3) workshops. The partner in this service activity is the Biology Education Study Program of FSTT UNDIKMA Mataram, especially for students who have taken thesis examinations and will compile articles based on their research findings. From the results of the evaluation of the activities, it can be concluded that the purpose of this service activity has been achieved according to expectations, namely increasing student knowledge about the ins and outs of writing scientific papers and scientific articles, the achievement can be seen from the results of student articles that have been presented through the presentation of the results of the preparation of their articles showing that the results are very good and in line with expectations.
Application of Information Technology in Teaching in Vietnam

Information technology is a great achievement of the developing scientific and technological revolution in this day and age. The positive effects that it has on the educational environment. The training of foreign languages supported by information technology has been taking place in almost all universities and colleges nationwide. The paper focuses on analyzing the situation of information technology application in teaching and learning from theory to practice at FPT University, and provides solutions to apply information technology to improve efficiency of teaching foreign languages in schools, creating premises and increasing job opportunities for students after graduation. The paper also discusses the situation of information technology application in foreign language teaching-learning process from the world model to the application situation in Vietnam. The paper analyzes the theoretical application of the introduction of information technology into the classroom, into the teaching process, followed by an analysis of the information technology competencies teachers need to achieve in Vietnam and world. Practical needs and necessity of the application of information technology in the Vietnamese context, accompanied by the current application situation in order to make appropriate recommendations
Attraversando il Sahel: Elena Dak in cammino con i nomadi

The essay intends to examine the most recent reportage written by travel writer Elena Dak, published by Corbaccio in 2016, dedicated to Peulh Wodaabe nomads, better known as Bororo. The experience of nomadism, firmly rejecting a ‘touristic’ idea of visit, is experienced and narrated by a woman’s voice as an exception that can facilitate the contact with the customs and traditions of a migrant culture, featured by ritual traditions, social practices and dances of extraordinary significance.
Articulation Point Based Quasi Identifier Detection for Privacy Preserving in Distributed Environment

These days, huge data size requires high-end resources to be stored in IT organizations premises. They depend on cloud for additional resource necessities. Since cloud is a third-party, we cannot guarantee high security for our information as it might be misused. This necessitates the need of privacy in data before sharing to the cloud. Numerous specialists proposed several methods, wherein they attempt to discover explicit identifiers and sensitive data before distributing it. But, quasi-identifiers are attributes which can spill data of explicit identifiers utilizing background knowledge. Analysts proposed strategies to find quasi- identifiers with the goal that these properties can likewise be considered for implementing privacy. But, these techniques suffer from many drawbacks like higher time consumption and extract more quasi identifiers which decreases data utility. The proposed work overcomes this drawback by extracting minimum required quasi attributes with minimum time complexity.
The Application of an Outcome-Representation Learning Model for Characterization of the Decision-Making Strategies Used by Younger and Older People

Characterizing how decision-making changes with age is important for understanding the psychology of older people. The Iowa Gambling Task (IGT) presents a well-established approach for collecting data relevant to this goal. We re-examine the utility of the IGT in this context through harnessing modern neurocomputational models and parameter estimation techniques for the first time.
Studi Kelayakan Aplikasi Kubuku E-Resources Berdasarkan Model Analisis PIECES Pada Perpustakaan Digital APMD Yogyakarta

This research is a feasibility study in the APMD Digital library using the Kubuku E-Resources application based on the PIECES framework analysis model outlined in 6 focus analysis of Performance, Information, Economy, Control, Eficiency and Service. PIECES framework can be used to determine the pros and cons of the application, so that it can serve as a reference in decision making to subscribe to the application in the following year or vice versa. In this study used quantitative descriptive methods. Data is obtained using questionnaires and data analysis using Likert scales. The results showed that the average value of the feasibility level of the APMD library to subscribe to the Kubuku E-Resources application as a Digital library reached 3.73 or with a decent predicate.
WHY are we teaching this way?: A convergence case of early childhood teacher education

본 연구에서는 유아교사양성과정에서의 분절되어 있는 교과 대학교재의 내용과 형식의 유사성 페다고지 수행을 방해하는 이분법적 사고 등에 대한 문제의식을 가진 두 교수자가 두 수업을 합하면서 학습자와 만나고 사이내부 에 몰입하고 경계 지음에 도전하고 다시 수렴되는 순환적인 융합과정 을 탐구하였다. 본 연구는 년 월부터 월까지 교사양성과정의 학부 학년 수업에서 이루어졌으며 그 당시 수업 기록에 담긴 두 교수자와 예비유아교사 명과의 토론 그 기록을 가지고 나누는 대화 그리고 그 순간들을 담은 사진들 수업 전후에 떠오르는 생각들을 담은 교수자 성찰일지와 예비유아교사 저널 등은 자료이자 때로는 이론이 되어 함께 하였다 실험적 수업을 해나가면서 고민하고 겪었던 생생한 이야기를 왜 융합하는가 어떻게 융합하는가 무엇을 융합하는가 라는 세 가지 연구문제 중심으로 풀어나갔으며 이와 같은 수업융합사례가 유사한 문제의식을 갖고 있는 유아교사들과 교육자들의 교육적 삶에 작은 파장을 일으켜 공명되기를 바래본다.This study explored the process of converging to encounter pre-service early childhood teachers immerge in-between them and us, and challenge the boundary by two professors, who have problematized the division of subjects in early childhood teacher education, similarities in content and form of university textbook materials, and dichotomous thinking that interferes with the performance of pedagogy. This study was conducted from September to December 2017 in the undergraduate class. A post-qualitative research leads us to generate our converging journey. Data were collected from the discussions with two professors and 21 preservice early childhood teachers, their conversations with the records, the photographs of the moments, and the professors’ reflective journals and the preservice teachers’ journals. The results showed the vivid stories that two processors experienced during the experimental class, focusing on three research questions: why converge, how to converge, and what to converge. We hope that such a convergence case will resonate with the educational life of teachers and educators with similar problem-consciousness.
Algorithm For Early Threat Detection By Suspicious Behavior Representation

The proposed early detection algorithm is justified because the probability of success to control a criminal activity increases when the response time for generating a warning alarm is reduced. In this paper, a video-based representation model to describe suspicious behavior from elementary actions is proposed. Such behaviors allow detecting potential threats before suspects achieve physical contact with their potential victims. In the algorithm, a novel method to adjust the balance between the anticipation level to threats and the generation of false alerts is introduced. The experimental results obtained from two validation datasets, with attacks to pedestrians and threats against a parked truck, demonstrated the effectiveness of the proposed approach for early threat detection, with performance measures above 90%.
Physical Cue based Depth-Sensing by Color Coding with Deaberration Network.

Color-coded aperture (CCA) methods can physically measure the depth of a scene given by physical cues from a single-shot image of a monocular camera. However, they are vulnerable to actual lens aberrations in real scenes because they assume an ideal lens for simplifying algorithms. In this paper, we propose physical cue-based deep learning for CCA photography. To address actual lens aberrations, we developed a deep deaberration network (DDN) that is additionally equipped with a self-attention mechanism of position and color channels to efficiently learn the lens aberration. Furthermore, a new Bayes L1 loss function based on Bayesian deep learning enables to handle the uncertainty of depth estimation more accurately. Quantitative and qualitative comparisons demonstrate that our method is superior to conventional methods including real outdoor scenes. Furthermore, compared to a long-baseline stereo camera, the proposed method provides an error-free depth map at close range, as there is no blind spot between the left and right cameras.
A Multi-scale Optimization Learning Framework for Diffeomorphic Deformable Registration

Conventional deformable registration methods aim at solving a specifically designed optimization model on image pairs and offer a rigorous theoretical treatment. However, their computational costs are exceptionally high. In contrast, recent learning-based approaches can provide fast deformation estimation. These heuristic network architectures are fully data-driven and thus lack explicitly domain knowledge or geometric constraints, such as topology-preserving, which is indispensable to generate plausible deformations. To integrate the advantages and avoid the limitations of these two categories of approaches, we design a new learning-based framework to optimize a diffeomorphic model via multi-scale propagations. Specifically, we first introduce a generic optimization model to formulate diffeomorphic registration with both velocity and deformation fields. Then we propose a schematic optimization scheme with a nested splitting technique. Finally, a series of learnable architectures are utilized to obtain the final propagative updating in the coarse-to-fine feature spaces. We conduct two groups of image registration experiments on 3D adult and child brain MR volume datasets including image-to-atlas and image-to-image registrations. Extensive results demonstrate that the proposed method achieves state-of-the-art performance with diffeomorphic guarantee and extreme efficiency.
A Study on the Practice of Coach-Type Teacher Reform Classroom Teaching in the Colleges and Universities

In this paper, from the perspective of coach-type teachers, by comparing the traditional teaching concepts and methods, the author discusses how to realize the role of university teachers in the new era, how to use coach technology to integrate advanced teaching concepts, innovate teaching structure and teaching mode, and apply them to the practice and exploration of classroom teaching reform.
Access structures determined by uniform polymatroids

Abstract In this article, all multipartite access structures obtained from uniform integer polymatroids were investigated using the method developed by Farràs, Martí-Farré, and Padró. They are matroid ports, i.e., they satisfy the necessary condition to be ideal. Moreover, each uniform integer polymatroid defines some ideal access structures. Some objects in this family can be useful for the applications of secret sharing. The method presented in this article is universal and can be continued with other classes of polymatroids in further similar studies. Here, we are especially interested in hierarchy of participants determined by the access structure, and we distinguish two main classes: they are compartmented and hierarchical access structures. The main results obtained for access structures determined by uniform integer polymatroids and a monotone increasing family <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi mathvariant="normal">Δ</m:mi> </m:math> \Delta can be summarized as follows. If the increment sequence of the polymatroid is non-constant, then the access structure is connected. If <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi mathvariant="normal">Δ</m:mi> </m:math> \Delta does not contain any singletons or the height of the polymatroid is maximal and its increment sequence is not constant starting from the second element, then the access structure is compartmented. If <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mi mathvariant="normal">Δ</m:mi> </m:math> \Delta is generated by a singleton or the increment sequence of the polymatroid is constant starting from the second element, then the obtained access structures are hierarchical. They are proven to be ideal, and their hierarchical orders are completely determined. Moreover, if the increment sequence of the polymatroid is constant and <m:math xmlns:m="http://www.w3.org/1998/Math/MathML"> <m:mo>∣</m:mo> <m:mi mathvariant="normal">Δ</m:mi> <m:mo>∣</m:mo> <m:mo>&gt;</m:mo> <m:mn>1</m:mn> </m:math> | \Delta | \gt 1 , then the hierarchical order is not antisymmetric, i.e., some different blocks are equivalent. The hierarchical order of access structures obtained from uniform integer polymatroids is always flat, that is, every hierarchy chain has at most two elements.
Peningkatan Kenyamanan Pelanggan dengan Sistem Customer Relationship Management (CRM) pada Smile Dental Care Padang

In a business / company engaged in health both hospitals, clinics, practice requires something that can entice patients. In order to be comfortable and get facilities that can make patients loyal to treatment. One of the most supportive systems is the construction of an information system portal that can facilitate patients and companies in carrying out their activities and can establish good communication and get reciprocal relationships between patients and doctors. Smile Dental Care is a dental clinic specializing in braces installation in the city of Padang, West Sumatra. The purpose of this research is to apply Customer Relationship Management (CRM) to improve the relationship between patients and doctors, so that they get comfortable with each other. The results of this study are the creation of an information system portal, which is useful to support the improvement of Smile Dental Care, and provide excellent service to patients.
Penerapan Algoritma K-Means Clustering untuk Melihat Hubungan Kegiatan Tahfiz dengan Hasil Belajar (Studi Kasus Madrasah Aliyah Negeri 1 Bukiktinggi)

The purpose of this study is to evaluate whether Tahfiz activities and learning outcomes are effective or not. The data processed in this study were data on tahfiz activities and data on student learning outcomes in class XI (eleven) totaling 42 data sourced from memorization of tahfiz, tahfiz grades, and student grades in Madrasah Aliyah Negeri 1 Bukittinggi. Based on the analysis of the data, this classification uses one of the methods of the Data Mining algorithm, K-Means Clustering. K-Means Clustering algorithm works based on the grouping method, In this data mining technique consists of data testing and training data with the input of the number of memorization of tahfiz, and the value of tahfiz as well as learning outcomes. The results of this study the school can determine how influential this activity tahfiz on student grades.