Reviewerly/exHarmony huggingface dataset:
Building Deep Learning Models to Predict Mortality in ICU Patients

Mortality prediction in intensive care units is considered one of the critical steps for efficiently treating patients in serious condition. As a result, various prediction models have been developed to address this problem based on modern electronic healthcare records. However, it becomes increasingly challenging to model such tasks as time series variables because some laboratory test results such as heart rate and blood pressure are sampled with inconsistent time frequencies. In this paper, we propose several deep learning models using the same features as the SAPS II score. To derive insight into the proposed model performance. Several experiments have been conducted based on the well known clinical dataset Medical Information Mart for Intensive Care III. The prediction results demonstrate the proposed model's capability in terms of precision, recall, F1 score, and area under the receiver operating characteristic curve.
Sistem Informasi Keuangan Pada Panti Asuhan Yatim Putri Aisyiyah II Berbasis Web

Finance is very important for companies and companies in doing business. Yatim Putri Aisyiyah II Orphanage Kadipiro is one of the Surakarta Aisyiyah business charities that has an important role for the community inside and outside the orphanage. The financial management process of Yatim Putri Aisyiyah II Orphanage found problems including the process of recording and making reports on the financial section using a manual system. A manual system causes many errors and also requires a long time. This research aims to develop a web-based financial information system. The system development method used is the Waterfall method including requirements analysis, system design, implementation, testing and system maintenance. The development of this system uses the PHP programming language, MySQL database and CodeIgniter framework. The results of this study are systems that can be used to process data and financial data reports. Based on the results of black box testing, the system developed can run according to its function.
LibGuides: PowerPoint Presentations: Design

A guide to layout, design, best practices, and tips for creating a great PowerPoint presentation for your class.
TRANSFORMATION OF A UNIVERSITY TEACHER’S ACTIVITY AND ITS TIMING IN DISTANCE LEARNING FORMAT

This article discusses educational, methodological and scientific work peculiarities of a university teacher in the context of transition to active usage of distance learning technologies. The possibilities and features of educational activities are revealed. The psychological features of remote interaction work are stated. The possibility of correcting the time frame of the teaching staff activity is considered by carrying out the timing process using specialized software products. The option of recording teacher’s activities is considered on the example of textual teaching materials creation. Recommendations on conducting the timekeeping procedure of the teaching staff in distance learning format are given.
Separation and Concentration in Deep Networks

Numerical experiments demonstrate that deep neural network classifiers progressively separate class distributions around their mean, achieving linear separability on the training set, and increasing the Fisher discriminant ratio. We explain this mechanism with two types of operators. We prove that a rectifier without biases applied to sign-invariant tight frames can separate class means and increase Fisher ratios. On the opposite, a soft-thresholding on tight frames can reduce within-class variabilities while preserving class means. Variance reduction bounds are proved for Gaussian mixture models. For image classification, we show that separation of class means can be achieved with rectified wavelet tight frames that are not learned. It defines a scattering transform. Learning $1 \times 1$ convolutional tight frames along scattering channels and applying a soft-thresholding reduces within-class variabilities. The resulting scattering network reaches the classification accuracy of ResNet-18 on CIFAR-10 and ImageNet, with fewer layers and no learned biases.
Mobile Application Fluentu For Public Speaking Skills Development

In this article the effectiveness of learning public speaking skills through mobile application «Fluentu» is explored. Also there were given analysis with advantages and disadvantages of this mobile platform. Besides new possibilities of English language teaching in a mobile environment are demonstrated by some examples of using mobile device that is crucial in nowadays distance learning. Moreover the article describes «Fluentu» mobile device implementation in English classroom. The main area of research is to check the mobile platform for developing public speaking skills. FluentU is unlike any other card app. It doesn’t just show you a flashcard with an unfamiliar word and its meaning (sometimes with a picture) - you see how this word is used in the video.
Quantitative Linguistic Investigations across Universal Dependencies Treebanks

The paper illustrates a case study aimed at identifying cross-lingual quantitative trends in the distribution of dependency relations in treebanks for typologically different languages. Preliminary results show interesting differences rooted either in language-specific peculiarities or cross-lingual annotation inconsistencies, with a potential impact on different application scenarios.1
Application Analysis of Artificial Intelligence in Computer Technology

Artificial intelligence is the result of the development of the times. Artificial intelligence is also constantly reforming and innovating following the pace of the times. The increasing application of artificial intelligence in today’s society is the best witness to the development of artificial intelligence. As an important core of computers, artificial intelligence is an indispensable part of improvement.It can maximize the needs of contemporary people and improve the efficiency and quality of workers. This article first briefly introduces the concept of artificial intelligence, then briefly analyzes some of the shortcomings in the current application of artificial intelligence and computer applications, focuses on the analysis of the application of artificial intelligence in computer technology, and briefly puts forward suggestions to promote the development of artificial intelligence for the shortcomings.
PROJECT LEARNING TECHNOLOGY AT HIGHER SCHOOL AS A PRACTICAL TRAINING FORMAT

The necessity to introduce project learning technology at higher school is updated as, firstly, it is a new education format in practical training introduction at a legal level, secondly, it allows to form student’s professional competences and, thirdly, to meet the employers’ requirements to the quality of professional training of specialists. Concrete practical experiences of introducing project learning technology within project weeks at a private educational institution of higher education “International Institute of Design and Service” is described.
Development of Online Academic Portal System Android Based on National University: Development of Online Academic Portal System Android Based on National University

Online academic portal is a system of information section in every tertiary institution. Various academic information ranging from displaying all student information which includes academic activities of students, lecturers and administrative staff. However, the online academic portal system at national universities is still not effective in using web-based services. Therefore, the aim of the researchers is to design an Android-based national university academic portal system so that it can help users / students access online academic portals anywhere without having to open the National University web. Application trial results can display all academic information data with 100% accuracy. In developing the national university's academic portal system, researchers used the waterfall method which is a mature method for researching the development of a system, so that many researchers use this method for research. Then this application is designed using the PHP programming language, PostgreSQL and android studio, this research methodology uses the waterfall method which has several stages of research namely data collection, literature study, application creation, system testing. The results of this study are Android-based online academic portal systems. This research methodology uses the waterfall method which has several stages of research namely data collection, literature study, application making, system testing. The results of this study are Android-based online academic portal systems. This research methodology uses the waterfall method which has several stages of research namely data collection, literature study, application making, system testing. The results of this study are Android-based online academic portal systems.
On the Innovative Practice Path of College Students’ Archives Work

The archives can be divided into three stages according to the filing time and the student files.This paper summarizes and analyzes all kinds of problems in the three stages, turns the difficulties and pain points in the work into innovation breakthrough points, puts forward corresponding solutions or measures, and constantly considers and innovates in the work practice, increases the filing range of student archives, and explores a feasible way of innovative practice of college student archives work.
Correspondence Learning for Controllable Person Image Generation

We present a generative model for controllable person image synthesis,as shown in Figure , which can be applied to pose-guided person image synthesis, $i.e.$, converting the pose of a source person image to the target pose while preserving the texture of that source person image, and clothing-guided person image synthesis, $i.e.$, changing the clothing texture of a source person image to the desired clothing texture. By explicitly establishing the dense correspondence between the target pose and the source image, we can effectively address the misalignment introduced by pose tranfer and generate high-quality images. Specifically, we first generate the target semantic map under the guidence of the target pose, which can provide more accurate pose representation and structural constraints during the generation process. Then, decomposed attribute encoder is used to extract the component features, which not only helps to establish a more accurate dense correspondence, but also realizes the clothing-guided person generation. After that, we will establish a dense correspondence between the target pose and the source image within the sharded domain. The source image feature is warped according to the dense correspondence to flexibly account for deformations. Finally, the network renders image based on the warped source image feature and the target pose. Experimental results show that our method is superior to state-of-the-art methods in pose-guided person generation and its effectiveness in clothing-guided person generation.
MIOpen: An Open Source Library For Deep Learning Primitives

Deep Learning has established itself to be a common occurrence in the business lexicon. The unprecedented success of deep learning in recent years can be attributed to: an abundance of data, availability of gargantuan compute capabilities offered by GPUs, and adoption of open-source philosophy by the researchers and industry. Deep neural networks can be decomposed into a series of different operators. MIOpen, AMD's open-source deep learning primitives library for GPUs, provides highly optimized implementations of such operators, shielding researchers from internal implementation details and hence, accelerating the time to discovery. This paper introduces MIOpen and provides details about the internal workings of the library and supported features. MIOpen innovates on several fronts, such as implementing fusion to optimize for memory bandwidth and GPU launch overheads, providing an auto-tuning infrastructure to overcome the large design space of problem configurations, and implementing different algorithms to optimize convolutions for different filter and input sizes. MIOpen is one of the first libraries to publicly support the bfloat16 data-type for convolutions, allowing efficient training at lower precision without the loss of accuracy.
Multi-Sensory Technology In Teaching English To Young Learners

Language is a natural skill in humans and every day more people recognize how important is to be multilingual.Teachers, linguistics, and parents believe that early childhood is the best period to learn the four areas that structure a language which are speaking, listening, reading and writing.When an infant is learning a second language, the educator should design a program with activities that can improve each of these areas and according to Garner, there are multiple intelligences and different styles of learning from the outside world, styles such as auditory, visual, tactile, and kinesthetic.Multisensory Technology states that teaching preschoolers a foreign language recognizes that every child is capable of learning, allowing every individual to acquire knowledge according to his/her characteristics.The Russian system offers public kindergarten to it's citizens and the main classes are taught in the Russian language with the option of having English classes as an additional service.Classes are two times a week, with a duration of 30 minutes per class and the average group of students has 8 to 10 kids.Based on the experiences and the results observed in different students, the multi-sensory method is the answer for teaching English as a second language in the kindergarten because the method accomodates to different learning styles while developing motivation, attention and energy in the kids.
Improving the Neural Network Algorithm for Assessing the Quality of Facial Images

The paper considers the task of obtaining a quality assessment of facial images for usage in various video surveillance systems, video analytics, and biometric identification. The accuracy of person recognition and classification depends on the quality of the input images. We consider an approach to obtaining single face image quality assessment using a neural network model, which is trained on pairs of images that are split into two possible classes: the quality of the first image is better or worse than the quality of the second one. Two modifications of the selected baseline algorithm are proposed. A face recognition system is applied to change the loss function and image and face quality attributes are used when training the model. Experimental studies of the proposed modifications show their effectiveness. The accuracy of selecting the best and worst frame is increased by 1.3% and 1.9%, respectively.
The Effect Of Modified Domino Cards Game On Students’ Vocabulary Mastery

This research aimed to find out the effect of modified domino cards game on students’ vocabulary mastery at the seventh grade students of Mts Negeri 3 Mataram in academic year 2019/2020. The research was pre experimental design. The population of the study was the seventh grade students that consisted of five classes. The sample of the study was class VII C that consists of 39 students. The class was treated using modified domino cards game. The result of the study shows that there is significance positive effect of modified domino cards game on students’ vocabulary mastery. The data of the research were gathered from data analysis and inferential analysis. In data analysis, the mean score of pre test was 44.62 and post test was 73; the mode score of pre-test was 45.9 and post test was 78.3; the median score of pre-test was 44.8 and post test was 78.14; the score of standard deviation on both of the test was 11.27. In inferential analysis, the result showed that the value of t-test (18.94) was higher than the value of t-table (2.024) with significance level of 5%. The finding of this study led into the conclusion that the use of modified domino cards game shows positive effect on students’ vocabulary mastery at the seventh grade of Mts Negeri 3 Mataram. This is based on the t-test &gt; t-table (18.944 &gt; 2.024) in degree significant of 5%. It means that Ha was accepted and Ho was rejected. Therefore, it can be concluded that modified domino cards game gives positive effect on students’ vocabulary mastery at the seventh grade students of MTs Negeri 3 Mataram in academic year 2019/2020
The Quality of the Department of Library Science's Website by WebQual 4.0

This research discusses the quality of the website of the Library Science Study Program Universitas Islam Negeri Alauddin Makassar as a medium of information using the WebQual 4.0 method. Three measurement variables are used, namely: Usability Quality, Information Quality, and Interaction Quality. This descriptive study uses a quantitative approach in presenting data. The data were obtained through online questionnaires and website observations. The population in this study was 448,440 the number of website visitors and a sample of 100 student respondents who were determined by incidental sampling technique. The validity and reliability tests used SPSS 23 software. The results showed that the quality of usability and information quality of the website of the Department of Library Science UIN Alauddin Makassar were in the good category with a percentage of 75.1% and 73.7%. Meanwhile, the interaction quality is in the very good category with a percentage of 81.5%. So it can be said that the quality of this website is in a good category.
Peningkatan Keterampilan Menulis Berita Melalui Model Pembelajaran Kooperatif Tipe Jigsaw Siswa Kelas VIII D MTS Pondok Pesantren As-Salam Naga Beralih Kabupaten Kampar

Based oninitial observation the fiel, the student news writing skills MTs Boarding School As-Salam Naga Beralih Kampar regency still low. This isi caused by several factors, one of which is the selection of the learning modeling accuracies. Learning model used is still the main choice in lecture learning. Another factor that comes from the students was the lack of motivation to write the story bacauce it was though that writing astoryisa difficult activity. To correct this condition carried through Classroom Action Research type Jigsaw Cooperative Learning Model.&#x0D; Purpose of this research class action (1) describing the process of improving the student skill in writing news items in class VIII D of class VIII d MTs boarding School As-Salam Naga Beralih Kampar regency increases trough Jigsaw cooperative learning model, and (2) describing the supporting factors improved writing skills class VIII D news MTs Boarding School As-Salam Naga beralih Kampar regency increases trough jigsaw cooperative learning model. Class room Action research was conducted in two cycles. Each cycle through the stages of (1) planning, (2) action, (3) observation, (4) reflection. The subjects were students of class VIII D Boarding School As-Salam Naga Beralih Kampar regency.&#x0D; The results of this study showed on increase in news writing skill class VIII D with respect to completeness of the content of the news (5 w = 1 H), regularity of exposure, use of effective sentences, vocabulary used, the accuracy of using EYD, and attractiveness of headlines along with the formulation of several contributing factors in improving writing news class VIII D boarding School As-Salam Naga Beralih Kampar Regency. Jigsaw cooperative learning model type is suitable for use by teachersin teaching students to writing news. Teachers should choose appropriate learning steps in using the model of cooperative learning Jigsaw type new sin the learning process.
Geometric Distance for Fast Micro-Expression Detection

In this paper, we propose a new model for micro-expression detection in videos in conjunction with a set of facial keypoints. The main contribution lies at the construction of geometric features extracted using the geometric distances between pairs of keypoints in different groups. The proposed geometric features-based micro-expression detection model requires a very low computation complexity and simultaneously attains highly accurate detection rates. We compare the proposed geometric features-based model to the existing state-of-the-art micro-expression detection and recognition models in three datasets, where the proposed method has achieved better, or at least comparably accurate results but requiring much less computation time.
Evaluasi Sistem Informasi Administrasi Terhadap Kualitas Pelayanan dan Kinerja Program Studi

The administrative information system is a website-based information system that is used to assist the administrative activities of the Computer and Information Technology Education Program (P.TIK) of the IKIP PGRI Pontianak. The purpose of this study was to determine the service quality and performance of the P.TIK study program after implementing the study program administration information system. The method used in this research is a survey method with a descriptive evaluative research approach. The research sample consisted of 185 students of P.TIK IKIP PGRI Pontianak using purposive sampling technique by selecting students who had used the study program administration information system. The data collection tool used was a closed questionnaire with data analysis techniques using descriptive statistics. The results showed that the service quality and performance of the study program after using the administrative information system were in the very good category
Exploring Adversarial Examples via Invertible Neural Networks

Adversarial examples (AEs) are images that can mislead deep neural network (DNN) classifiers via introducing slight perturbations into original images. This security vulnerability has led to vast research in recent years because it can introduce real-world threats into systems that rely on neural networks. Yet, a deep understanding of the characteristics of adversarial examples has remained elusive. We propose a new way of achieving such understanding through a recent development, namely, invertible neural models with Lipschitz continuous mapping functions from the input to the output. With the ability to invert any latent representation back to its corresponding input image, we can investigate adversarial examples at a deeper level and disentangle the adversarial example's latent representation. Given this new perspective, we propose a fast latent space adversarial example generation method that could accelerate adversarial training. Moreover, this new perspective could contribute to new ways of adversarial example detection.