Reviewerly/exHarmony huggingface dataset:
Context-aware Deep Model for Entity Recommendation in Search Engine at Alibaba

Entity recommendation, providing search users with an improved experience via assisting them in finding related entities for a given query, has become an indispensable feature of today's search engines. Existing studies typically only consider the queries with explicit entities. They usually fail to handle complex queries that without entities, such as what food is good for cold weather, because their models could not infer the underlying meaning of the input text. In this work, we believe that contexts convey valuable evidence that could facilitate the semantic modeling of queries, and take them into consideration for entity recommendation. In order to better model the semantics of queries and entities, we learn the representation of queries and entities jointly with attentive deep neural networks. We evaluate our approach using large-scale, real-world search logs from a widely used commercial Chinese search engine. Our system has been deployed in ShenMa Search Engine and you can fetch it in UC Browser of Alibaba. Results from online A/B test suggest that the impression efficiency of click-through rate increased by 5.1% and page view increased by 5.5%.
비한자권 학습자를 위한 한자, 한자어 교육 연구 - 한자구형학(漢字構形學)의 적용을 중심으로

This paper analyzed 302 beginner Chinese characters for Learners from non-Chinese Character Culture of Jang Il-kyul (2012) based on the theory of Chinese character configurational.A total of 302 direct components are 227, with more than 70% participating in the Configuration as a Ideographic component. This choice takes into account Learners from non-Chinese Character Culture beginners.However, the basic components of 302 characters includes 25 Symbolic Letters and 38 variants. The three-story, four-story Chinese characters contain 13 characters, and 57 Symbolic Letters of grade 3 and 4 that have few conformational motivations, are also included in 302 characters. The 302 characters contain difficult Chinese characters, so you have to re-select the beginner Chinese characters.Based on semantic transparency and the number of combinations, this paper has chosen Chinese characters again that fit the beginner level. Based on semantic transparency and the number of combinations, this paper has chosen Chinese characters again that fit the beginner level.After selecting 185 characters again, the Chinese character education plan for Learners from non-Chinese Character Culture beginners was proposed by applying the theory of Chinese character configuration.
Molson Coors cyberattack leaves production at a standstill

A cyber hack is brewing at Molson Coors in Milwaukee. One source tells FOX6 this hack is crippling – that the company can’t produce beer until it’s fixed.
Fuzzy-Based Stratagem for Teleoperation of Robots in Incoherent Environments

This chapter provides an interesting system for robot controlling in incoherent environments (like, a battlefield, space, or underwater) using human gestures. In this type of places where safety is a major concern, it is not feasible for any person to present there and perform some specified tasks. So to accomplish the given duties, robots can be employed as an alternative. But if the robots are asked to carry out the works by their own, then there is a high chance that the precise goals can be missed owing to the ever changing nature of the incoherent environments. As a solution to this problem, human intelligence can be imparted into the robots by sending gestural commands. Gestures depicting same command may differ not only from subjects to subjects, but also same command while displaying by the same person on different days can vary among them. So, gesture recognition technique employing Interval Type-2 fuzzy system is used. This chapter deals with a novel purpose of robot navigation in incoherent environments which are inaccessible to the human beings. The proposed system has propitious potentials for upcoming applications of robot maneuver based on well-accepted performance metrics when comparing with other existing literatures.
Identifying Patients with Heart Failure in Susceptible to De Novo Acute Kidney Injury: A Machine Learning Approach

Background: Acute kidney injury (AKI) in heart failure (HF) patients with normal renal function is easily to be neglected. To address this problem, we investigated characteristics of de novo AKI susceptible HF patients and proposed a machine learning based risk stratification model.Method: We analyzed an electronic health record (EHR) dataset of heart failure patients from Chinese PLA General Hospital. Adult HF patients with normal renal function at admission were eligible for inclusion. An unsupervised machine learning method, named K-means, were used to separate patients into two phenogroups. We then compared the differences between two phenogroups and validated whether the inferred phenogroup index had potential to be an essential risk indicator by conducting survival analysis, AKI prediction, and the hazard ratio (HR) test.Findings: The AKI incidence rate in phenogroup 2 was significantly higher than in phenogroup 1 (11·5% vs 3·7%, p<0·001). The patients in phenogroup 2 were typically older, had worse physical status, and more likely to experience multi-organ dysfunction and anemia. The survival rate of phenogroup 2 was consistently lower than that of phenogroup 1 (p<0·005). By logistic regression, the univariate model using the phenogroup index achieved promising performance in AKI prediction (sensitivity 0·710). The phenogroup index was also significant to serve as a risk indicator for AKI (HR 3·20, 95% confidence interval 2·55-4·01). Consistent results were yielded by applying the proposed model on an external validation dataset extracted from MIMIC III pertaining to 1,006 HF patients with who had normal renal function.Interpretation: Using a machine learning analysis on EHR data, patients with HF who had normal renal function were clustered into separate phenogroups associated with different risk levels of de novo AKI. Our investigation suggests that using machine learning can facilitate patient phengrouping as well as risk stratification in clinical settings where the identification of high-risk patients has been challenging.Funding Statement: This study was partially supported by the National Key Research and Development Program of China under grant no. 2018YFC0910700 and the National Nature Science Foundation of China under grant no. 61672450. Declaration of Interests: None declared.Ethics Approval Statement: The study protocol was approved, with a waiver of consent granted on the basis of minimal harm and general impracticability, by the Health Institutional Review Boards atZhejiang University and PLAGH, respectively.
Penyuluhan Makanan Bergizi Seimbang Melalui Pendekatan Metode Ular Tangga

The health issue is still a primary obstacle in Indonesia. All sectors need to pay attention to it; otherwise, the human resource level will be low. In line with this socialization is needed to encourage children especially, to start aware of consuming a healthy diet. In addition, this can broaden children’s horizons about what they better eat. The method in this activity is by using snake ladder game which is more attractive and fun for children. This method, in fact, can enhance children's knowledge. During the pre-test, the correct answers were 11,9 on average; while after the socialization the right answers were 14,5 on average. It shows that the sharing knowledge by snake ladder game is effectively helpful for children to increase their knowledge.
Information educational environment as a resource for advancing a teacher-musician’s skills in the additional children education system 

Following the development of modern Russian education, updating the system of additional education for children, introducing the Professional standard “Teacher of additional education for children and adults”, developing a high-tech information educational environment, new requirements are placed on the professional activity of a teacher: new requirements for educational technologies, the content of the educational process, fluency in modern information technologies, methods of their active use, including various types of distance education. In this regard, the social order for extended education of teachers-musicians, working both in the system of additional education of children and in children's music and art schools using modern computer and computer technologies, is changing. The article highlights the results of a pedagogical study aimed at developing methods and technologies for using informational educational environment capabilities in the professional activities of a modern teacher-musician.Keywords: Informational educational environment, information technology, music education, computer-computer technologies, teacher-musician. RESUMENTras el desarrollo de la educacion rusa moderna, la actualizacion del sistema de educacion adicional para ninos, la introduccion de la norma profesional Profesor de educacion adicional para ninos y adultos, el desarrollo de un entorno educativo de informacion de alta tecnologia, se imponen nuevos requisitos a la actividad profesional de un profesor: nuevos requisitos en materia de tecnologias educativas, el contenido del proceso educativo, el dominio de las modernas tecnologias de la informacion, los metodos de su utilizacion activa, incluidos diversos tipos de educacion a distancia. A este respecto, esta cambiando el orden social para la ampliacion de la educacion de los maestros-musicos, que trabajan tanto en el sistema de educacion adicional de los ninos como en las escuelas de musica y arte para ninos que utilizan tecnologias informaticas y de computacion modernas. En el articulo se destacan los resultados de un estudio pedagogico encaminado a desarrollar metodos y tecnologias para utilizar las capacidades del entorno educativo informativo en las actividades profesionales de un profesor-musico moderno.Palabras clave: Entorno educativo informativo, tecnologia de la informacion, educacion musical, tecnologias informaticas, profesor-musico.
On Sequential-Pattern-Based Intelligent Compilation of Aircraft Assembly Process

Abstract The aviation industry which aircraft manufacturing dominates is an important sector to measure a nation’s air power. The application of new technologies to optimize the process, increase the speed and upgrade the quality of airplane assembly, a crucial link in its manufacturing, is an effective method to improve the capacity. The combination of traditional processes and emerging technologies greatly improves its efficiency, reduces its labor costs and promotes the innovation and upgrade of traditional technologies. For aircraft manufacturers, the Assembly Outline (AO) refers to an essential document used for the guidance of the assembly process. Low efficiency and under-structuration of compilation, which is also difficult to upgrade, put a limit on the application of information and digitization technologies and has an impact on the overall airplane production cycle, due to present manual work in quantity and imbalance of informationization. Via sequential-pattern-based data mining introduced in this paper, patterns of AO processes are dug up to form a set based on which it is possible to quickly make a recommendation of the optimal process for the compiler, effectively reducing the duration of compilation and modification and improving the efficiency.
Trace Link Recovery Using Semantic Relation Graphs and Spreading Activation.

Trace Link Recovery tries to identify and link related existing requirements with each other to support further engineering tasks. Existing approaches are mainly based on algebraic Information Retrieval or machine-learning. Machinelearning approaches usually demand reasonably large and labeled datasets to train. Algebraic Information Retrieval approaches like distance between tf-idf scores also work on smaller datasets without training but are limited in providing explanations for trace links. In this work, we present a Trace Link Recovery approach that is based on an explicit representation of the content of requirements as a semantic relation graph and uses Spreading Activation to answer trace queries over this graph. Our approach is fully automated including an NLP pipeline to transform unrestricted natural language requirements into a graph. We evaluate our approach on five common datasets. Depending on the selected configuration, the predictive power strongly varies. With the best tested configuration, the approach achieves a mean average precision of 40% and a Lag of 50%. Even though the predictive power of our approach does not outperform state-of-the-art approaches, we think that an explicit knowledge representation is an interesting artifact to explore in Trace Link Recovery approaches to generate explanations and refine results.
Guides @ UF: Research Reproducibility: Readings and Resources

A Listing of Reproducibility and Open Science resources at the University of Florida and beyond. Links to other lessons and readings
Towards an E journalism Based on Semantic Web Technologies

The electronic journalism industry became one of the most important achievements of technology in the two decades. Through online media platforms, information and instant news delivered easily and cheaper than before. In addition to that, e-journalism reduces the time and space needed in traditional journalism industry, and hence improve the information lifecycle beginning from collecting reaching to delivering the news to users in convenient ways. On the other hand, Semantic Web technologies enrich the meaning of web content by converting the unstructured data to structured format. So, our proposed works aims to build robust e-journalism system based on Semantic Web technologies to improve the quality of service for journalists and readers.
RECOGNITION AND CLASSIFICATION OF MALARIA PARASITES OF THIN BLOOD SMEARS

The project comprises of an image processing system that identifies the malaria parasites in the blood cells of our humanbody. To detect the malaria parasites, various methods are used in this system. The functioning of this system is categorizedinto two parts. In the first part of the system, morphological processing technique is used to extract the Red Blood Cells(RBC). The regions in the blood cells will be detected, so does the parasitic images in the blood. Through this detection,classification of affected and non affected red blood cells can be known including the count of RBCs. The second part of thesystem uses the cross correlation function to categorize the parasite into one of the four species namely, Plasmodiumfalciparum, Plasmodium vivax, Plasmodium ovale. Accurately, the system detects 95% of the parasite occurance in theblood.
Academic impact of covid-19 on peruvian university students

Introduction: As a result of the coronavirus pandemic, many students are worried that they may lose their academic term Objective: Validate a scale to measure the perception of possible academic impacts among Peruvian university students Method: A validation process was conducted of a test measuring the perception of university students about possible academic impacts The validation was based on a scientific bibliography search, development of a preliminary overview, validation of the test by 59 experts: epidemiologists, researchers and physicians, exploratory factor analysis, and statistical analysis Results: In terms of relevance, item 7 was found to be more essential or important than the others (V = 1 00;CI 95 %: 0 73-0 96) Item 8 (M = 3 80;σ = 1 152) exhibits the highest mean, and item 6 the lowest (M = 3 03;SD = 1 342) AFE relevance is justified by the KMO index (0 85) and Bartlett's test (12577 0;gl = 28;p = < 0 001), both of which were found to be acceptable and significant A Cronbach's α coefficient of 0 899 was obtained, with a confidence interval of 95%, SD 0 882-0 898, indicating a good consistency level Conclusions: A single factor scale was validated which measures the perception of university students about the possible impacts of the coronavirus pandemic on their studies It is necessary to evaluate each reality, and the tool may serve as a base scale for that purpose © 2021, Editorial Ciencias Medicas All rights reserved
Predicting Laughter Relevance Spaces in Dialogue

In this paper we address the task of predicting spaces in interaction where laughter can occur. We introduce the new task of predicting actual laughs in dialogue and address it with various deep learning models, namely recurrent neural network (RNN), convolution neural network (CNN) and combinations of these. We also attempt to evaluate human performance for this task via an Amazon Mechanical Turk (AMT) experiment. The main finding of the present work is that deep learning models outperform untrained humans in this task.
Data Models, Pivot, and CIM

In the previous chapter, you learned about lookups and their various types. We also discussed tags, reports, and alerts in Splunk. In this chapter, you learn how to create a data model, an event action, and a Common Information Model.
Intra Prediction-Based Hologram Phase Component Coding Using Modified Phase Unwrapping

In this paper, we propose a method for compressing the phase component of a full-complex hologram. The JPEG (Joint Photographic Experts Group) Pleno is undergoing standardization for compressing full-complex holograms. If the full-complex hologram is compressed in the form of amplitude and phase components, the three-dimensional information of the hologram may be better preserved. Therefore, in order to solve the disadvantages of the method of independently compressing real and imaginary parts, we propose a method for directly compressing phase information. We select the HEVC (High Efficiency Video Coding), which has the best performance in compressing holograms from previous studies, as the anchor codec, and propose an algorithm for converting the phase information into the form suitable for the HEVC. Since the phase component is very random, we propose a modified phase unwrapping technique to improve this. In addition, in order to make good use of the property of HEVC Intra coding, the phase unwrapping considering Intra prediction is applied, and the most suitable HEVC Intra coding condition is searched. Compared with the result of compressing the phase using the HEVC, the hologram was improved by 2 dB or more and the reconstruction result was improved by more than 4 dB at a compression ratio of 80:1. If the compression ratio is increased, the proposed method has better results.
Complicações pulmonares em pacientes diabéticos com infecção por covid-19 / Pulmonary complications in diabetic patientes with covid-19 infection

INTRODUCTION:The disease called COVID-19 has become a worldwide public health concern due to its rapid spread to several countries, setting up a pandemic.Several studies have indicated Diabetes mellitus a contribution to an increased risk for serious pulmonary events.The aim of the article is to discuss the respiratory complications present in diabetic patients infected with SARS-CoV-2.METHODOLOGY: A bibliographic research was performed selecting the studies published in the last five years by the databases PubMed, Scielo and BVS MS, in the period of January 2021.RESULTS: It was observed that
Evaluation of Virtual Hang-Gliding Applications in Terms of Tourism with Swot Analysis

With the development of the internet, many internet users have the opportunity to access a different world. Thanks to the fact that users can access virtual tours outside their environment. Through virtual reality entertainment can be arranged many activities such as design and simulation. The purpose of study of the people with the development of technology in their lives especially one of the sports of aviation activities in the entertainment field of virtual reality and applications that are used to evaluate the use of hang-gliding activities in terms of tourism. This study examines the use of virtual hang-gliding flights as a substitute tourism application in tourism. Some basic problems and problems related to the integration of this application with tourism are analyzed and some suggestions are made for future applications regarding the use of VR in tourism. In this study, we searched the literature review in this area through Google scholar, Scopus and online sources and the SWOT analysis was made by evaluating the collected information. The purpose of using SWOT analysis in the study is to evaluate the advantages and disadvantages of these applications in terms of tourism by evaluating the studies and applications related to virtual hang-gliding. Another aim is to determine how strengths can be developed through opportunities and how threats that can affect weaknesses can be eliminated. As a result, even if this technology is perceived as a threat, it is concluded that it is an effective promotion and marketing tool for tourism.
Mapping of Tuberculosis Case and Climate Condition of Padang City

Padang as one of the cities in West Sumatra Province has a fairly high confirmed Tuberculosis case. The prevalence of pulmonary tuberculosis is influenced by ecological, geographic and climatic factors. Geographic Information Systems (GIS) that can be used as a tool that can show public health problems, especially health problems that are area-based. The aim of the study was to look at the distribution of positive smear pulmonary TB cases and the conditions of rainfall, humidity, temperature and wind speed with the use of the GIS web application in Padang City in 2018. Data are presented in the form of vulnerability maps and tables. The city of Padang has the highest humidity and suspected cases of AFB + in the Koto Tangah District.
Recording of Academic Transcript Data to Prevent the Forgery based on Blockchain Technology

Diploma certificate and transcript forgery is a serious issue in education.The government is still finding the best way to prevent and minimize this issue in the future.The diploma certificate and transcript are very easy to duplicate, not only from third parties.Even the university can easily produce a fake diploma certification and transcript for their benefit.Blockchain technology is a new technology and now can be used to prevent the fake graduation documents.This research shows the simulation of blockchain technology used (Multichain) for data recording of academic transcript as one of the graduation documents.FGD has been carried out by inviting several reputable universities to validate the prototype.As a result, the FGD participants validated the prototype and agreed if it possible to be implemented in university, especially for recording the academic transcript data.Recording the academic transcript on blockchain technology can contribute to prevent forgery.