Reviewerly/exHarmony huggingface dataset:
Myocardial Revascularization Surgery

Myocardial Revascularization SurgeryIntroduction: Acute myocardial infarction (AMI) is characterized as the cellular death of the muscle that involves the heart, causing ischemia, which is associated with the clinical presentation, presenting electrocardiographic compatibility and / or electrocardiographic changes typical of the reduction or interruption of blood flow to the myocardium.Myocardial revascularization (MRI) is a surgical procedure that connects mammary arteries, radial arteries, or saphenous veins.These "bridges" allow the blood to return to the coronary arteries preserving them, in any part of their follow-up.Objectives: To describe the casuistry of the patient with a diagnosis of acute myocardial infarction (AMI), developing for a post-surgical picture of chronic renal failure (CRI), including therapeutic management, specific care, criticism and referential confrontations.Methodology: This is a descriptive and casuistic study.The study was based on a review of recent and recent publications regarding the proposed theme, electronic search of articles and journals in the following databases: in the portal of CAPES and BIREME, LILACS, SCIELO, MEDLINE, conducting authors' confrontation and exposition of a case carrying out the specific considerations.The data collection instrument consists of data collection and has as study period from May 2016 to September 2016.Results: Description and analysis of the clinical picture of the patient JJFG, male, 77 years old, hospitalized in a hospital of the private network , where he was hospitalized in this hospital for more than a hundred days.After the therapeutic interventions the patient presented decay in his clinical picture.With several associated complications that culminated in the death of the patient.Conclusion: The infection table and the old age were determining factors for the clinical decline of this patient.
RESEARCH ON DIFFERENT FEATURE EXTRACTION AND MAMMOGRAM CLASSIFICATION TECHNIQUES

Breast cancer is the primary and the most common disease found among women. Today, mammography is the most powerful screening technique used for early detection of cancer which increases the chance of successful treatment. In order to correctly detect the mammogram images as being cancerous or malignant, there is a need of a classier. With this objective, an attempt is made to analyze different feature extraction techniques and classiers. In the proposed system we rst do the preprocessing of the mammogram images, where the unwanted noise and disturbances in the mammograms are removed. Features are then extracted from the mammogram images using Gray Level Co-Occurrences Matrix (GLCM) and Scale Invariant Feature Transform (SIFT). Finally, the features are classied using classiers like HiCARe (Classier based on High Condence Association Rule Agreements), Support Vector Machine (SVM), Naïve Bayes classier and K-NN Classier. Further we test the images and classify them as benign or malignant class.
Detecting Gaze Direction Using Robot-Mounted and Mobile-Device Cameras

Two common channels through which humans communicate are speech andgaze. Eye gaze is an important mode of communication: it allows people tobetter understand each others’ intentions, desires, interests, and so on. The goalof this research is to develop a framework for gaze triggered events which canbe executed on a robot and mobile devices and allows to perform experiments.We experimentally evaluate the framework and techniques for extracting gazedirection based on a robot-mounted camera or a mobile-device camera whichare implemented in the framework. We investigate the impact of light on theaccuracy of gaze estimation, and also how the overall accuracy depends on usereye and head movements. Our research shows that the light intensity is im-portant, and the placement of light source is crucial. All the robot-mountedgaze detection modules we tested were found to be similar with regard to ac-curacy. The framework we developed was tested in a human-robot interactionexperiment involving a job-interview scenario. The flexible structure of thisscenario allowed us to test different components of the framework in variedreal-world scenarios, which was very useful for progressing towards our long-term research goal of designing intuitive gaze-based interfaces for human robotcommunication.
Paradigm Shift in Curriculum: A Visionary Mission

Human beings came to the world along with ideas which got nurtured and transmitted from generation to generation. To upgrade quality of life he became educated through formal, informal and non-formal ways. Curriculum was structured formally at different levels of education which is being upgraded and refined from time to time. Here in this paper an attempt has been made to relocate the paradigm shift in curriculum in a mission mode taking the suggestions as follows: Culture specific pedagogy; Moral Education for revival; Curricular renovation, reformation and innovation in terms of reality and fact; Vocationalization in true sense; Emphasis on Practical aspect; Meeting the needs of the locality; Imparting Patriotism through curriculum; Preaching and practising Yoga Education; Indian Traditional Culture from the age old spiritual scriptures; Committee consisting people having practical experience from the grass root level; Placing importance upon joyful learning; Providing opportunity to prepare the ground for all round development; Meeting aims of educations from a broader perspective; Adopting innovation of other countries; Fund for conducting Research; Application of Research findings; Finding the Vision and Mission; Making them free from the over burden of examination; Protecting environment through education; Emphasizing experiential learning; To inculcate global human values among the youth; To prepare for global citizenship.
A Study on the Impact of Principal’s Decision Making Styles on Organizational Culture Openness and Teachers’Commitment

본 연구에서는 열린 교육행정을 위한 민주적인 형태의 참여적 의사결정과 학교장 중심의 단독적 의사 결정이 학교조직풍토개방성과 교사조직몰입에 미치는 영향을 비교하였다. 이를 위해 경상남도교육청 및 울산광역시교육청 소속 초등학교 교사 922명의 설문조사 자료를 활용하여 학교규모별 구조방정식모형다 집단 비교분석을 실시하였다. 분석 결과 첫째, 학교규모와 무관하게 초등학교장의 참여적 의사결정이 학교조직풍토개방성에 정적인 영향을 미치는 것으로 나타났다. 둘째, 참여적 의사결정이 교사조직몰입에도 중소규모와 대규모 학교 모두에서 정적인 영향을 미치는 것으로 나타났다. 셋째, 대규모 학교에서만 단독적 의사결정이 학교조직풍토개방성에 정적인 영향을 미치는 것으로 분석되었다. 넷째, 초등학교장의 단독적 의사결정은 중소규모와 대규모 학교 모두에서 교사조직몰입에 부적으로 영향을 미치는 것으로 분석되었다. 다섯째, 학교조직풍토개방성이 교사조직몰입에는 중소규모와 대규모 학교 모두에서 정적으로 영향을 미치는 것으로 나타났다. 초등학교장 중심의 단독적 의사결정보다는 학교구성원인 교사들이 의사결정과정에 참여하는 의사결정이 대규모와 중소규모 초등학교 모두에서 학교조직풍토개방성과 교사들의 조직몰입에 더 많은 긍정적 영향을 미치는 것으로 분석되었다. 한편 단독적 의사결정이 대규모 초등학교에서 학교조직풍토개방성에 정적인 영향을 미치는 것으로 나타난 부분에 대해서는 추후 연구가 이루어지기를 기대해 본다.The purpose of this study is to analyze the effect of principal’s decision making styles on organizational culture openness and teachers’ commitment according to school size. The data for this study was collected from the questionnaires of teachers from elementary schools under the educational government of Gyeongsangnamdo and Ulsan. Participatory decision making has positive effects on openness of organizational culture in small sized schools (under 36 classrooms) as well as large sized schools (over 36 classrooms). Directive decision making has a statistically significant positive effect on openness of organizational culture only in large sized schools. Participatory decision making has positive effects on teachers’ commitment while directive decision making has negative effects on teachers’ commitment both in large and small sized schools. Openness of organizational culture has positive effects on teachers’ commitment both in large and small sized schools. There can be differences in the impact of principals’ administrative behavior styles on outcomes of school organization depending on school size.
Dynamics Of Readiness For Learning Of University Students

The authors consider readiness for learning as the basis of professional development, a component of professional culture, which determines the level of professional achievements of a specialist in modern society. Readiness for learning is studied in the paradigm of the system-genetic approach in psychology and is defined as an integral mental quality, the internal psychological basis of which is the structure of the individual qualities of a person that determine the success of training (qualities required for training). A conceptual model of the psychological structure of readiness for learning of students of pedagogical high school, consisting of five functional blocks qualities required for learning is worked out. The article presents the results of the research of the main indicators of the dynamics of students readiness for vocational training at high school. The empirical study was conducted on students of pedagogical University of different courses, the total group – 80 people. It is established that in the process of professional training the indicators of quality required for learning development increase, their interrelations are improved, the psychological structure of readiness for training as a whole is optimized. The most significant development effect was noted in relation to quality required for learning: professional orientation, task acceptance, introduction skills, attention performance, arbitrary regulation of activity, empathy, verbal memory. The development of readiness for learning is an indicator of the development of professional culture of students in the process of studying at high school.
PENERAPAN ALGORITMA K-MEDOIDS CLUSTERING UNTUK PENGELOMPOKKAN PENYEBARAN DIARE DI KOTA MEDAN (STUDI KASUS: KANTOR DINAS KESEHATAN KOTA MEDAN)

The health office is in charge of instructing and registering diarrhea sufferers in each region, then the area will be evaluated which areas are most affected by diarrhea. And checking directly into the field revealed that the most basic cause was about the unclean environment such as trenches that were too much garbage, causing floods during the rainy season. The health office also encourages the community to always maintain environmental cleanliness and familiarize people to always wash their hands with soap before eating and after cleaning with simple things like this is expected to help reduce diarrhea sufferers in the city of Medan. K-Medoids Clustering is clustering algorithm which is similar to K-Means. The difference between these two algorithms is the K-Medoids or PAM algorithm uses the object as a representative (medoid) as the center of the cluster for each cluster, while the K-Means uses the mean (mean) as the center of the cluster.Keywords: Diarrhea, Service office, Data mining, K-Medoids Algorithm
Tweaking Harassment Through Tweets: A Critical Discourse Study of #MeToo

The study aims to conduct an analysis of the discourse on #MeToo which the study takes to be the unmediated voice of the victims of sexual harassment to determine the ideology imbibed in the discourse. Teun A. van Dijk&amp;rsquo;s Ideology and discourse: A multidisciplinary introduction (2000) serves as the theoretical basis for the study as it attempts to categorize what constitutes harassment for the victims by looking at 3000 tweets posted over thirty days. The critical analysis of the data reveals that one of the most lacking elements in the life of the victims of sexual harassment is an acknowledgment of harassment as harassment. Most of the victims are abused, shamed and silenced when they try to share their panic experiences of life. The study shows that sexual harassment is a widespread social epidemic and can occur to a person of any age group, at any place and in any type of relationship. The study is significant as it presents the unmediated view of the victims of sexual harassment and compares it with the existing view of harassment. The significance of the study also lies in the fact that it analyzes the features of Twitter to determine their role in shaping the discourse. Previous studies on harassment talk about the issue or explore its features and types through various angles, but none of them focuses on the voice of the victims themselves.
Something Phish-y is Going On Here: A Teaching Case on Business Email Compromise

This case utilizes a real-world example of a cyberfraud incident at a U.S. public company. The company was the victim of a Business Email Compromise (BEC) scheme in which an employee inadvertently wired millions of dollars to fraudulent accounts based upon email instructions purportedly sent by a company executive and external legal counsel. This is a timely and important issue to examine given its rising prevalence and magnitude in the corporate world. The case allows students to examine a topic (phishing techniques and email scams) which they are likely to be familiar with on a conceptual level, through the lens of internal controls and auditing. Examining the case information, SEC filings and articles from the business press, students will gain an understanding of internal control issues related to BEC and critically think of ways to remediate or implement controls to reduce cybersecurity risk. Students will research PCAOB, AICPA and SEC policies regarding cyberfraud disclosure and the auditor's role in cybersecurity. They will gain an understanding of the financial and nonfinancial impact of BEC on corporations. The case also requires students to consider the growing responsibilities of auditors related to technology and its associated risks.
CONVERSATIONAL CHATBOT SYSTEM FOR STUDENT SUPPORT IN ADMINISTRATIVE EXAM INFORMATION

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 8294-8301ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.1974Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
Research of background-oriented schlieren based on two-dimensional de Bruijn sequence color coding technology

Background-oriented schlieren (BOS) is a novel flow visualization technology, which has the advantages of simple device, low cost, and quantitative measurement. In this paper, a BOS technique with two-dimensional color coding background is presented, which can be referred to as color background-oriented schlieren (CBOS). Different from traditional background schlieren technique, we designed a pattern combining ‘cosine dot’ and two-dimensional color coding as the background of BOS technique. Inspired by the coding principle based on De Bruijn sequence coding in the spatial coding method of traditional structured light coding technology, the pattern of ‘cosine dot’ is generated by multiplying the fringes in two perpendicular directions. In order to integrate the intensity value of cosine dots and corresponding encoded colors into a single pattern, and to separate them completely, the HSV color model is applied to address the problem. We calculate the perturbation degree of test flow fields by searching positions of the local intensity maximum of the cosine dot patterns with and without flow fields. The function of two-dimensional color coding is employed to locate the relative position of each local intensity maximum point. Finally, we carried on the simulation experiment and the real experiment to verify the feasibility of this method.
Extended algorithm to construct a quadtree from Freeman chain code in four directions

This paper introduces improvements to the algorithm that was proposed in 2001 by Chen and Chen. The algorithm constructs a quadtree directly from Freeman chain code in four directions. We have improved the algorithm in two ways: Firstly, a time efficient solution using the space filling Z-order curve is proposed for a self-intersection case that was not considered by Chen and Chen. Secondly, the algorithm is expanded to handle geometric objects containing holes. The computational efficiency of the extended algorithm was confirmed by the experiments.
New approach to calculating the fundamental matrix

The estimation of the fundamental matrix (F) is to determine the epipolar geometry and to establish a geometrical relation between two images of the same scene or elaborate video frames. In the literature, we find many techniques that have been proposed for robust estimations such as RANSAC (random sample consensus), least-squares median (LMeds), and M estimators as exhaustive. This article presents a comparison between the different detectors that are (Harris, FAST, SIFT, and SURF) in terms of detected points number, the number of correct matches and the computation speed of the ‘F’. Our method based first on the extraction of descriptors by the algorithm (SURF) was used in comparison to the other one because of its robustness, then set the threshold of uniqueness to obtain the best points and also normalize these points and rank it according to the weighting function of the different regions at the end of the estimation of the matrix''F'' by the technique of the M-estimator at eight points, to calculate the average error and the speed of the calculation ''F''. The results of the experimental simulation were applied to the real images with different changes of viewpoints, for example (rotation, lighting, and moving object), give a good agreement in terms of the counting speed of the fundamental matrix and the acceptable average error. The results of the simulation show this technique of use in real-time applications
ESCAPE ROOMS FOR TEACHING IT-SECURITY

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 6815-6824ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.1623Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
Long-Term Visual Object Tracking via Continual Learning

Long-term visual tracking is one of the most challenging problems in computer vision and is closer to practical application needs. In long-term video sequences, tracking targets often undergo dramatic appearance changes over time due to various factors such as scale variation, illumination change, occlusions and so on. In this work, we propose a novel robust long-term tracking framework based on continual learning and dynamic sample set modules. We transform the online tracking process into a continual learning process of the target model, and continuously learn various appearance changes to adapt to different scenarios. The continual learning module distills the beneficial knowledge of the old network to the new network through warm-up and joint training to achieve a comprehensive and holistic memory of the target appearance. Combining the dynamic sample set can effectively balance the short-term memory and long-term memory of the model, and establish a near-complete target appearance description in the long-term dimension to cope with various challenging situations. Experimental results on the large-scale long-term benchmark datasets LaSOT and UAV20L show that the proposed method performs favourably against other state-of-the-art trackers.
Sigma-pi neural unit

Electrical circuit to control power is designed for TTL IC sigma-pi neural units. The designed unit is implementable as an integral circuit. The unit representation features are considered in a given circuitry basis. A neural circuit simulation is performed through the PSpice interpreter. The properties of neural networks are considered. The prospects for creating multi-bit processors based on sigma-pi neural units are discussed.
Providing teaching resources for young learner classes: Best practices in efl context

The availability of teaching resources is one of important factors to create successful lessons in teaching English to young learners (TEYL). Teachers can use flashcards, toys, songs, rhymes, books, audio visual materials, digital recourses and others to support teaching and learning process. Ready-made materials are available in stores, however they are usually expensive. The aim of this article is to share one of the best practices in providing resources for young learners in learning English. In the academic year of 2018, 40 students of English Department of IKIP Siliwangi took English for Young Learners (EYL) course for two credit hours. This is the second subject which is related to teaching young learners after they learned TEYL subjects as the perquisite subject in the previous year. In this course, students re-learned the concept of TEYL and the concepts how to provide teaching materials and resources for TEYL classes. At the end of the course, they should show their projects and demonstrate how to use them in TEYL. The findings reveal that students’ are very creative in designing resources for TEYL classes. This ability is very crucial in order to create child-friendly pedagogy in EYL classrooms.
INTERNET AND EDUCATION: PROJECT APPROACH

Appears in: ICERI2019 Proceedings Publication year: 2019Pages: 4641-4649ISBN: 978-84-09-14755-7ISSN: 2340-1095doi: 10.21125/iceri.2019.1146Conference name: 12th annual International Conference of Education, Research and InnovationDates: 11-13 November, 2019Location: Seville, Spain
Research on feature extraction and matching algorithm based on speckle structured light binocular vision system

Binocular stereo vision combined with structured light technology has developed rapidly in recent years. We have studied the blob extraction and matching algorithm of randomly distributed infrared speckle structured light, proposed an improved blob detection algorithm based on Laplacian of Gaussian (LoG) operator, which combines the contrast of the blob, the intensity difference and statistics between the center and edge pixels of the blob. The improved blob detection algorithm can extract the blobs of various scales and brightness effectively at one time, and restrain the influence of edges, bright strips and corners. According to the randomness of projected dot distribution, a matching method based on the characteristics of surrounding blob distribution is proposed. In order to solve the correspondence problem, we attach a descriptor to each blob. The descriptor at a reference blob center captures the angle and distance of the remaining blobs relative to it. In a small local region, the corresponding point sets in the two images are approximately affine transformed, and the transformed point sets have similar descriptive values. Experiments show the feasibility and correctness of this improved blob detection algorithm and matching method.
Sistem Pakar Diagnosis Penyakit Jamur pada Manusia Menggunakan Input Suara Berbasis Android

Fungal skin disease is a type of disease that is often suffered people in the tropics. Phenomena in the community often assume that this disease will heal by itself. However, if left the effects of fungal skin disease can worsen the sufferer condition. The importance of early detection and treatment is very necessary, but this requires patients go to hospital or doctor so that patients spend a lot of time and money. For this reason, was build an android expert system with speech to early diagnose fungal skin diseases. From this initial diagnosis will save time and money and provide alternative prevention for sufferers. The method used in this study is the Certainty Factor of 20 patients. The accuracy of the test results to the system compared to the results of the doctor's diagnosis is 95%. So that, this expert system can be an early alternative in diagnose fungal skin diseases in humans.
Choosing between Long and Short Word Forms in Mandarin

Between 80% and 90% of all Chinese words have long and short form such as 老虎/虎 (laohu/hu , tiger) (Duanmu, 2013).Consequently, the choice between long and short forms is a key problem for lexical choice across NLP and NLG in Chinese.Following on from earlier work on abbreviations in English (Mahowald et al., 2013), we bring a probabilistic perspective to word length choice, using both a behavioural and a corpus-based approach.Thus, we hypothesise that, in Chinese, short forms are likelier in supportive than in neutral contexts.Our corpus and behavioral study supported this hypothesis, but a closer analysis revealed striking differences between different types of Chinese words.