Reviewerly/exHarmony huggingface dataset:
P4-559: DETECTION OF PROBABLE DEMENTIA CASES IN UNDIAGNOSED PATIENTS USING STRUCTURED AND UNSTRUCTURED ELECTRONIC HEALTH RECORDS

Dementia is underdiagnosed in both the general population and among Veterans. This underdiagnosis decreases quality of life, reduces opportunities for interventions, and increases health-care costs. New approaches are therefore necessary to facilitate the timely detection of dementia. This study seeks to identify cases of undiagnosed dementia by developing and validating a weakly supervised machine-learning approach that incorporates the analysis of both structured and unstructured electronic health record (EHR) data. A topic modeling approach that included latent Dirichlet allocation (LDA), stable topic extraction, and random sampling was applied to VHA EHRs. Topic features from unstructured data and features from structured data were compared between Veterans with (n=1,861) and without (n=9,305) ICD-9 dementia codes. A logistic regression model was used to develop dementia prediction scores, and manual reviews were conducted to validate the machine-learning results. A total of 853 features were identified (290 topics, 174 non-dementia ICD codes, 159 CPT codes, 59 medications, and 171 note types) for the development of logistic regression prediction scores. These scores were validated in a subset of Veterans without ICD-9 dementia codes (n=120) by experts in dementia who performed manual record reviews and achieved a high level of inter-rater agreement. The manual reviews were used to develop a receiver of characteristic (ROC) with different thresholds for case detection, including a threshold of 0.061, which produced an optimal sensitivity (0.827) and specificity (0.830). Dementia is underdiagnosed, and thus, ICD codes alone cannot serve as a gold standard for diagnosis. However, this study suggests that imperfect data (e.g., ICD codes in combination with other EHR features) can serve as a silver standard to develop a risk model, apply that model to patients without dementia codes, and then select a case-detection threshold. The study is one of the first to utilize both structured and unstructured EHRs to develop risk scores for the diagnosis of dementia.
Contents and Interactivity of National Library Websites

&#x0D; &#x0D; &#x0D; The contents and interactivity of national library websites around the world is analysed. The study was confined to ninety nine selected national library websites. A checklist along with a data sheet was used as the tool for data collection and Microsoft Excel was used as the tool for data analysis. The analysis revealed that the websites have almost identical pattern of contents and interactivity. Majority of the websites used interactive applications. Facebook is the most preferred application followed by Twitter, RSS and blogs. The websites preferred extreme top right corner and extreme bottom right corner of their homepages to provide links to the applications and web objects. This study is useful for developing design standards for library websites and portals.&#x0D; &#x0D; &#x0D;
Repurposing: Another R to prioritize in data curation

ABSTRACT Data repurposing has great potential for innovative research. But there are distinct risks of researchers outside the group who originally collected the data misunderstanding the actual meaning of particular fields and values. These meanings may not be sufficiently well documented, as those within the collecting group know what is really meant in the context of the original purposes of collection.
Research on Chinese Sign Language Recognition Methods Based on Mechanomyogram Signals Analysis

This paper presents an integrated approach to Chinese sign language (CSL) actions recognition, which involves Teager-Kaiser energy operator (TKEO) segmentation, wavelet feature extraction and support vector machine (SVM) classification on mechanomyogram (MMG) Signals. It used a four-channel wireless signal acquisition system to collect the MMG signals of the extensor digitorum (ED), flexor carpi radialis (FCR), flexor carpi ulnaris (FCU) and extensor carpi radialis (ECR). After filtering, the TKEO algorithm was used to segment the MMG signals. The wavelet packet energy (WPE) of MMG signals were extracted as features for further analysis. SVM was applied as a classifier to recognize 18 CSL actions. Compared with other commonly used methods, the proposed method had better recognition accuracy and recognition performance as well. The average recognition accuracy of the proposed method was up to 95.38%.
Leveraging Multi-head Attention Mechanism to Improve Event Detection

Event detection (ED) task aims to automatically identify trigger words from unstructured text. In recent years, neural models with attention mechanism have achieved great success on this task. However, existing attention methods tend to focus on meaningless context words and ignore the semantically rich words, which weakens their ability to recognize trigger words. In this paper, we propose MANN, a multi-head attention mechanism model enhanced by argument knowledge to address the above issues. The multi-head mechanism gives MANN the ability to detect a variety of information in a sentence while argument knowledge acts as a supervisor to further improve the quality of attention. Experimental results show that our approach is significantly superior to existing attention-based models.
Implementasi Electronic Health Record (EHR) Pada Poli Rawat Jalan Di Rumah Sakit Umum Daerah Ratu Zalecha Martapura

A system of Electronic Health Record (EHR) is an activity computerized the contents of the medical record and process related. Based on the preliminary studies in Hospital of Ratu Zalecha Martapura obtained that already some clinics that implement EHR systems and for some clinics will get their turn to apply the system. The purpose of this research was to identify the security system (security), clinical support (clinical support), and reports (report) on the system of the EHR. The method of this research uses descriptive research with qualitative analysis. Research instrument this is manual observation and interview guidelines. This research was conducted to 8 informant head installation medical record, IT officers, three doctors and three nurses. The results of research at in Hospital of Ratu Zalecha Martapura to be able to access the EHR user must use a username and password. Username and password are made according to their respective limits and authority. Clinical support in the system is good, doctors and nurses fill their own diagnoses into EHR applications, service time is more effective and more efficient so as to improve patient services. Reports produced were reports of 10 major outpatient diseases, outpatient visit reports, daily outpatient census reports, RL1, RL2, RL3, RL4 and RL5.
Factors Contributing Students Motivation Toward English Language Learning

The purpose of this research is to identify those factors that students are motivated toward English language learning. Furthermore, the study applied quantitative approach and the instrument was questionnaire to collect the data, and the questionnaire have been adopted, the software for analyzing the data were SPSS and calculated the percentage for the findings. Moreover, the major findings revealed as follow; first, English helps/will help me meet foreigners, second, English will be helpful for my career, third; English helps/will help me in my travel overseas and fourth; Studying English can be important for me because it will help me to further my studies. DOI: https://doi.org/10.5281/zenodo.3376488
A Survey of Web Mining and Various Web Mining Techniques

Mining is essence of valuable information from the huge set of raw information. Mining techniques in data mining is known as web mining. The rapidly increasing number of web contents including image, multimedia, and digital data. The knowledge gained from the web can be utilised for increase the performance for searching of data. In the internet there is so many duplicate data in present. Thus how we can utilise the useful data from the whole collection of data is a tough task.Web mining shows the past work on using different web algorithms. Today The huge amount of data is present on web. The web crawler plays the essential role in updating the current data. The search engine are depends on the ranking technology instead of the other vector based approaches. This paper will focuses on different web mining techniques and the various algorithm used in it.
Construction of the Talent Training System of New Engineering Specialty in Engineering Education Certification

The purpose of the work is to propose a talent training system of new engineering specialty integrated with the engineering education certification standards.Firstly the talent training system is constructed according to the establishment of training objectives, graduation requirements, curriculum knowledge system, engineering ability training system and the improvement of continuous improvement mechanisms based on the quality evaluation system.Then the automation, information and electrical specialties have practiced the proposed talent training system in the College of Electrical and Information Engineering of Beihua University.At last the disciplines have received connotative development.
The Effectiveness of Using Collaborative Strategic Reading (CSR) on Students’ Reading Comprehension of Narrative Text

This study aimed to find out whether or not the use of collaborative strategic reading (CSR) will be effective on students’ reading comprehension of narrative text. The study used a quantitative method with pre-experimental design. The instruments used in this study were pre-test and post-test and the subjects of this study were the tenth-grade students of MA Annida Al-Islamy. The data were analyzed by using the t-test. The results showed that the students mean score in pre-test was 64 while in post-test mean score was 78. The result of this study analysis obtained 8.439 to and 2.045 tt with significant of 5%. Thus, it can be said that the use of collaborative strategic reading (CSR) on students’ reading comprehension of narrative text was effective.
Content-Based Image Retrieval Based on Improved Rotation Invariant LBP Descriptor

This paper proposes an improved rotation invariant LBP descriptor (improved rotation invariant LBP, ILBPri) by adding sampling to improve the performance of the classic LBP descriptor description and retrieval efficiency employed in the CBIR (content-based image retrieval) system. Firstly, Harris corners are extracted from the original image by ILBPri descriptor, then the original image is sampled centered on the Harris corners; secondly, the sampled image are encoded in rotation invariant LBP; thirdly, the LBP histograms of each image are counted; finally, images are ranked by Euclidean distance between LBP histograms of images. A CBIR system was designed in this paper to test the performance of ILBPri descriptor, and an image retrieval experiment was designed with test image database Caltech 256. Experimental results show that precision has been increased by at least 1.8% and recall has been increased by at least 2.4% compared with classic LBP and classic improved LBP descriptors. The query time has been increased by 23.78ms and 0.77ms compared with LBP and LBPri.
A Study on Talent Acquisition Practices at DXchange

Talent acquisition would be a newly coined terminology for many of us but it's not new for the HR practioners. Talent acquisition, is "a strategic approach to identifying, attracting and on boarding top talent to efficiently and effectively meet dynamic business needs. There is always a huge potential for highly talented resource globally and acquiring such talent has always been a challenging task for practioners. The increased competitiveness in the talent acquisition led to organizations spending more time, effort and resources on developing their talent acquisition strategy. In order to attain company objectives, it is essential to recruit people with requisite skills, qualification and experience keeping the present and future requirements in mind. Competition among business organizations for acquiring the best potential has increased focus on innovation, and management decision making. Selectors aim to acquire only the best candidates. The purpose of the project is to study the current talent acquisition process in the organization and identify areas for improvement. Secondly, the project studies the extent of adoption of best practices in the firm.
Application of Blended Teaching in Hydraulic Pneumatic Transmission and Control Course Based on MOOC and FanYa Platform

The hydraulic pneumatic transmission and control course has the characteristics with difficult theory and complicated application in the teaching process.How to change the problems of traditional classroom teaching such as dull, monotonous, boring, relatively fixed teaching time and place, rigid learning methods, low learning efficiency, etc., the MOOC and SMOOC technology were studied.The FanYa platform was adopted to realize blended teaching.The teaching team was organized before class, and the curriculum syllabus was developed according to the talent training program, and the teaching program, teaching plan, teaching PPT, animation production and micro-lesson video shooting were completed.The FanYa platform was used to complete pre-class preview, preview effect tracking, classroom communication and discussion and homework.Through the pilot program in the last three years, the students can make full use of fragmented time and learn at any time and anywhere by adopting blended teaching method.Teachers can greatly improve teaching efficiency.This work summarized the material block diagram and execution process of blended teaching, and realized the four-in-one blended teaching in the traditional hydraulic pneumatic transmission and control course, including the combination of theory and practice, pre-class and after-class, online and offline, traditional classroom and network classroom.
Investigation of graph databases suitable for work with big data while detecting money laundering and terrorism financing cases

This paper discusses the currently popular graph database management systems (DBMSs) working with Big Data and can be used to store information obtained while dealing with money laundering and terrorist financing criminal (ML/FT) cases. The aim of this study is to choose a secure graph DBMS suitable for working with Big Data for such financial investigations. The authors consider the existing graph DBMSs, analyze and compare them with each other with special emphasis on the information security protection methods of stored data. The advantages and disadvantages of software products are studied and a comparison with the help of selected parameters characterizing system's ability to keep information secure is made. The results of the comparison are followed by detailed comments. On its basis the most convenient, flexible and up-to-date DBMS was chosen for usage while searching ML/FT cases. It was found that graph DBMSs are suitable for Big data tasks and as a final result JanusGraph was selected as a foreground DBMS in this project according to selected parameters.
Transductive Parsing for Universal Decompositional Semantics

We introduce a transductive model for parsing into Universal Decompositional Semantics (UDS) representations, which jointly learns to map natural language utterances into UDS graph structures and annotate the graph with decompositional semantic attribute scores. We also introduce a strong pipeline model for parsing into the UDS graph structure, and show that our transductive parser performs comparably while additionally performing attribute prediction. By analyzing the attribute prediction errors, we find the model captures natural relationships between attribute groups.
Part-based pyramid loss for person re-identification

Person re-identification (ReID) is a challenging problem in computer vision, meanwhile attracted the attention of industry. Person ReID focuses on identifying person among multiple different cameras. A key under-addressed problem is to learn a good metric for measuring the similarity among images. Recently, deep learning networks with metric learning loss has become a common framework for person ReID, such as triplet loss and its variants. However, the previous method mainly uses the distance to measure the similarity and the distance measure is more sensitive when the scale changes. In this paper, we propose part-based pyramid loss to learn better similarity metric for the person ReID, in which batches of quadruplet samples as the input. Specifically, we simultaneously use the relationship of distance and angle among samples learn the local body-parts features of person images. Our approach uses the pyramid relationship in triangles as a measure of similarity, minimising the angle at the negative point of the triangle. Pyramid loss can learn better similarity metric and achieve a higher performance on the person ReID benchmark datasets. The experimental results show that, our method yields competitive accuracy with the state-of-the-art methods.
MODEL OF ENGINEERING EDUCATION WITH THE USE OF THE COMPETENCE-PROJECT APPROACH, ONTOLOGICAL ENGINEERING AND SMART CONTRACTS OF KNOWLEDGE COMPONENTS

The article presents the results of research related to the use of ontological and design competence approaches for the development of knowledge components and their subsequent use for designing individual trajectories of engineering education. The methodology of engineering education is considered, which, together with the initiative CDIO, the project-competence model and the knowledge display in the form of ontology, can be used as the main tool for modelling the propositional presentation of thought. Within the framework of the ontological approach, a knowledge specification language has been developed, which allows modelling the ontologies of supporting concepts of the semantic context of educational resources and specifying them in the form of knowledge expressions. The introduced formalisms and rules of the language of knowledge specification give the expressions of knowledge the properties of adaptability, extensibility, easement of processing and maintenance, which is important in designing engineering education level programs. This technique was tested on the material of the famous monograph by Hassan Goma “UML. Designing real-time systems, parallel and distributed applications" for the project "Banking system of client-server type" and is used on classes. Expressions of knowledge, together with their interfaces, are knowledge components from which individual learning trajectories are constructed.
Toward a Design Theory of Sleepy Games

For many, healthy sleep is either not a priority or not a possibility, a deficit which has far-reaching consequences. We explore the potential for "sleepy games" as a genre of transformational games with embedded content, relevant in both the digital and physical design space. We present design challenges unique to sleepy games, synthesized through an iterative design process. Lights Out, one of nine sleepy games created, provides an example of our insights in context.
THE APPLICATION OF EDUTAINMENT METHOD IN DEVELOPING BEGINNER-LEVEL WRITING COMPETENCY FOR STUDENTS OF EARLY GRADE IN ELEMENTARY SCHOOL

&lt;p&gt;Beginner-level writing is one of the dimensions in language development of early grade students in elementary school that need to be focused on. Writing is the final stage of literacy learning. Theoretically, before learning to write, children must go through some stages, such as listening, speaking and reading. In developing the competency of beginner-level writing for students of early grade in elementary school, a fun method must be used so that children can participate in activities well and without feeling depressed. One of the methods is known as edutainment. Edutainment is a combination of educational content that is presented with entertainment which aims at stimulating children to learn beginner-level writing through fun and interesting activities. Learning beginner-level writing with edutainment methods can be done with a variety of games, role playing activities or involvement of attractive learning media. With the edutainment method, children will not feel bored in learning beginner-level writing.&lt;/p&gt;
Learning Basic Grammar Using Task-Based Learning: A Perspective on Analyzing Online Media Text

This paper displayed the perspective on analyzing online media text using task-based learning in learning basic grammar. The data were collected for 6 months through observation, interview and questionnaires from July to December 2018 in IAIN Tulungagung. It involves 45 Indonesian undergraduate students who were taking English Basic Grammar with online media text. The data was analyzed using a descriptive qualitative approach. The finding revealed that the students got experience of using online media text as learning basic grammar medium. Their perspectives on analyzing online media text using task-based learning are various (not interesting, passive in the learning process, low interest in reading, tend to rely on friends, and difficult to analyze the online text). Furthermore, their’ perspective of using task-based learning in learning Basic English Grammar can be categorized into five types: the act of acquring strategy, the experiencing process, the process of acquiring benefits, the pupils’ responses, and evaluating their performance. It also reported that some benefits of task-based instruction strategy in teaching learning Basic English Grammar can be ability to deep understanding the materials, having good cooperation, having the ability to memorize, managing the time effectively, identifying the kinds of grammar part, and increasing the communication abilities. While the disadvantages of task-based learning in learning Basic English Grammar through analyzing the online media text included having difficulties in analyzing, not being used to with the learning model, getting bored and uncomfortable with the strategy, and being burdened with the task.
Computer Generated Hologram-Based Image Cryptosystem with Multiple Chaotic Systems

Based on computer generated hologram (CGH) and multiple chaotic systems, a novel image encryption scheme is presented, in which shuffling the positions and changing the values of image pixels are combined to confuse the relationship between the ciphertext and the original image. In the encryption process, the complex distribution is permuted by use of the designed scrambling algorithm which is based on Chen’s chaotic system and logistic maps firstly. Subsequently, the Burch’s coding method is used to fabricate the CGH as the encrypted image. Finally, the pixel values of the encrypted CGH are changed by sine map to withstand statistical analysis attacks. Simulation results demonstrate that the proposed method has high security level and certain robustness against statistical analysis attacks, data loss and noise disturbance.