Reviewerly/exHarmony huggingface dataset:
The status of digital pathology and machine learning within Alzheimer’s Disease Centers

Abstract Background Digital pathology and machine learning (ML) workflows have paradigm shifting potential especially in the field of Alzheimer’s disease and related disorders. However, many institutions/centers may not have access to these technologies. To provide benchmark data, a survey was developed and distributed to National Institutes of Health’s Alzheimer’s Disease Centers (ADCs) in the United States. Method Survey questions covered topics such as: infrastructure (i.e. type of digital slide scanners used), funding sources (i.e. how the scanner was funded), and data management/storage (i.e. size of digital files). After development, review, and approval by the ADC digital pathology working group, the survey was distributed via email to 35 past and current ADC directors and/or ADC neuropathology core leaders. Participation in the survey was completely voluntary and answers did not contain any personal data. Result The survey generated over a 90% response rate, and the majority of those who completed the survey were neuropathology core leaders; 81% stated their ADC had access to a digital slide scanner, most common brand being Aperio/Leica. One third of respondents stated there was a fee for service to utilize the scanner. For digital pathology and/or ML resources, 40% of respondents stated none are supported in any way by their ADC. To cover the purchase and operation of the scanner, 50% stated they had institutional support. Many were unsure of the approximate average scanned file size of digital images (37%) and total amount of storage space that files occupied (50%). Many (75%) were aware of other departments at their institution working with digital pathology and/or ML, but a similar percentage was unaware of multi‐university or industry partnerships. Conclusion These results demonstrate many ADCs have access to a digital slide scanner and had institutional support to cover the purchase. However, further investigation is needed to understand hurdles and barriers for implementing both digital pathology and ML workflows aiding in standardized methods across ADCs.
Adaptive Weighted Discriminator for Training Generative Adversarial Networks

Generative adversarial network (GAN) has become one of the most important neural network models for classical unsupervised machine learning. A variety of discriminator loss functions have been developed to train GAN's discriminators and they all have a common structure: a sum of real and fake losses that only depends on the actual and generated data respectively. One challenge associated with an equally weighted sum of two losses is that the training may benefit one loss but harm the other, which we show causes instability and mode collapse. In this paper, we introduce a new family of discriminator loss functions that adopts a weighted sum of real and fake parts, which we call adaptive weighted loss functions or aw-loss functions. Using the gradients of the real and fake parts of the loss, we can adaptively choose weights to train a discriminator in the direction that benefits the GAN's stability. Our method can be potentially applied to any discriminator model with a loss that is a sum of the real and fake parts. Experiments validated the effectiveness of our loss functions on an unconditional image generation task, improving the baseline results by a significant margin on CIFAR-10, STL-10, and CIFAR-100 datasets in Inception Scores and FID.
Research and development of linguo-statistical methods for forming a portrait of a subject area

The project aims to solve the fundamental scientific problem of semantic modeling, within the framework of which a methodology is developed for the automated identification of translation links (translation correspondences), as well as hierarchical, synonymous and associative links from Internet texts and the construction of multilingual associative hierarchical portraits of subject area (MAHPSA), in particular, on autonomous uninhabited underwater vehicles (UUV). Accounting for multilingual and heterogeneous resources allows you to get a more complete picture of what is happening in the subject area, to identify the sources of the origin of ideas, the speed and directions of their distribution, to identify significant documents and promising directions. The solution to the problem is based on an integrated approach that combines the methods of statistics, corpus linguistics and distributive semantics, and is implemented in technology that involves the development of linguo-statistical mechanisms for the formation of a multilingual associative hierarchical portrait of a subject area, which is a dictionary of significant terms of the subject area, the elements of which organized in synonymous series (synsets), including translational correspondences, as well as associative and hierarchical relationships.
MPG: A Multi-ingredient Pizza Image Generator with Conditional StyleGANs

Multilabel conditional image generation is a challenging problem in computer vision. In this work we propose Multi-ingredient Pizza Generator (MPG), a conditional Generative Neural Network (GAN) framework for synthesizing multilabel images. We design MPG based on a state-of-the-art GAN structure called StyleGAN2, in which we develop a new conditioning technique by enforcing intermediate feature maps to learn scalewise label information. Because of the complex nature of the multilabel image generation problem, we also regularize synthetic image by predicting the corresponding ingredients as well as encourage the discriminator to distinguish between matched image and mismatched image. To verify the efficacy of MPG, we test it on Pizza10, which is a carefully annotated multi-ingredient pizza image dataset. MPG can successfully generate photo-realist pizza images with desired ingredients. The framework can be easily extend to other multilabel image generation scenarios.
PNS198 Arogya Setu Mobile Application for COVID-19 Self-Assessment, Education and Participatory Disease Surveillance: Perception Among Medical and Technology University Students.

Technology plays a tremendous role in the active surveillance and communication in COVID-19 containment. We estimate the perceptions of medical and technology university students from India towards the use of Arogya Setu mobile application developed by the Ministry of Health and Family Welfare, Government of India.
Quantum technologies of forming semantic reading strategies at students – future teachers

The paper considers the problem of forming the semantic reading strategies at students - future teachers as that being the universal educational actions [hereinafter - UEA], which they should master in the university in order to be able to use them in teaching schoolchildren. These requirements are set forth in the Federal State Educational Standards for Higher Education [hereinafter referred to as the Standard] and in the Standards for Primary General, Basic General, Secondary General Education [hereinafter referred to as the Standards for General Education], which defines the lines of their continuity. Relevance of the problem is the need to develop of semantic reading strategies for the students - future teachers - to work with students in accordance with the requirements of General education Standards, on the one hand. On the other hand, first-year students who are starting to study pedagogy, did not study at school according to the new Standards and do not know the strategies of semantic reading. Modern children have changed a lot over the past decades (they have a new "system-semantic type of consciousness"), and in a different way than adults perceive, process and assimilate information, which requires the development of new approaches and technologies for their education and upbringing. Purpose of the paper is to reveal the essence and specifics of innovative quantum technologies aimed at forming semantic reading strategies at students – future teachers as universal educational actions, which will ensure the continuity of educational programs of general education and pedagogical education. The methodological basis of the problem under study is the psycholinguistics of child development (within the framework of the A.A. Leontyev’s scientific school), which studies the issues of the interconnected development of personality and consciousness of up-to-date children in the process of mastering speech activity in the context of multilingual education (in their native, non-native, foreign language, “subject language”). In the course of the study, the following methods were used: comparative analysis of scientific papers, questionnaires, training experiment, Quantum express method, analysis and evaluation of students' activity products. The results of the study confirmed the hypothesis and proved the effectiveness of Quantum technologies for forming semantic reading strategies based on the Quantum express method. In the course of studying the discipline "Pedagogy", students mastered the strategies of semantic reading, everyone was able to prepare a "student's Pedagogical Navigator" as a product of project research activities.
A Pseudo-labelling Auto-Encoder for unsupervised image classification

In this paper, we introduce a unique variant of the denoising Auto-Encoder and combine it with the perceptual loss to classify images in an unsupervised manner. The proposed method, called Pseudo Labelling, consists of first applying a randomly sampled set of data augmentation transformations to each training image. As a result, each initial image can be considered as a pseudo-label to its corresponding augmented ones. Then, an Auto-Encoder is used to learn the mapping between each set of the augmented images and its corresponding pseudo-label. Furthermore, the perceptual loss is employed to take into consideration the existing dependencies between the pixels in the same neighbourhood of an image. This combination encourages the encoder to output richer encodings that are highly informative of the input's class. Consequently, the Auto-Encoder's performance on unsupervised image classification is improved in terms of stability, accuracy and consistency across all tested datasets. Previous state-of-the-art accuracy on the MNIST, CIFAR-10 and SVHN datasets is improved by 0.3\%, 3.11\% and 9.21\% respectively.
The Ability of Indonesian EFL University Students in Writing an Explanation Text

This research aims at finding out the students’ ability in writing an explanation at first semester students of English Study Program of Nusa Cendana University, Kupang NTT. The researcher focuses on evaluating the students’ writing ability in five aspects of writing namely content, organization, grammar, vocabulary, and mechanics. The researcher applied the quantitative method and descriptive analysis design. The research was conducted in August 2019. This research was conducted at First semester students of the English Study Program of Nusa Cendana University, Kupang. The population of this research was First semester students of the English Study Program of Nusa Cendana University, Kupang in the 2020/2021 academic year. The number population is 160 in four classes. The researcher took 5 students from each class as the sample of the research. Therefore, there were 20 students as a sample. The test was used to find out the students’ ability in writing explanation text. In collecting data, the researcher asked the students to write an argumentative essay by choosing one of the given topics. To analyze the data, the researcher focused on evaluating the students’ writing in five criteria. The result of the research shows that the mean score of the test is 6.86. It shows that the students have an average degree of capability in writing explanation text. The biggest problem for the students in developing an explanation text is the organization (43%), it followed by the language use (37%), vocabulary (33%), content (30%), and the smallest problem is mechanics (30%). Some factors that hamper the students in writing: 1) the students face difficulties in expressing ideas, choosing appropriate words, and arranging ideas in writing, 2) the students seldom practice their writing skill, 3) the students still find difficulty in using punctuation in writing from, 4) the students do not enrich themselves with knowledge.
The effectiveness of a designed device for measuring and improving choice reaction time among players of physical education and sport Science College

The main purpose of the current study was to design a device for measuring and improving choice reaction time.The device is made up of mechanical materials such as a plastic box, buttons, signal lights) as well as electronic materials, and by relying on an electronic engineering (Arduino) program.The program is linking electronic circuits to mechanical materials.The device is a smart circuit and system that contain a battery of energy storage as well as a place to store information and transfer it on a SD card which the information can be transferred to the computer to the Excel program.The researcher used the experimental method for its suitability with the nature of the study.( 24) Undergraduate Male students were chose from the second year of college of physical education and sports science, students at Salahaddin University -Erbil.(n=24, age 19 ± 1.45).The researcher chose the sample from the players of the college of physical education and sport science that practicing the following games (football, volleyball, and basketball), divided into two groups (experimental and control group) each group consisted of 12 students.After six weeks of practice on the CRT, the results showed the effectiveness of the designed device in the posttest for the advantage of the experimental group.
PENERAPAN METODE SQ3R MENINGKATKAN KEMAMPUAN MEMBACA PEMAHAMAN PADA SISWA SDN 002 TOAPAYA

In learning to read, it involves students to be active with teacher’s guidance, so that the concepts on the subject can be understood, so as to improve students' reading skills. By improving reading skills through the use of SQ3R learning method, students are expected to be able to solve problems, make decisions, think critically, and think creatively so that students’ learning outcomes can also be improved. The SQ3R method is expected that students can understand andremember the material in a longer / permanent period of time. The use of the SQ3R method in learning will feel more interesting so that it can increase motivation to understand a reading. In essence, reading is a physical and mental activity to find the meaning of writing, although in that activity there is a process of recognizing letters. Based on the two opinions above, the researcheragrees that reading involves many things including physical, namely the eyes, involving mental, namely thoughts, especially perception and memory. To achieve the goal of reading, it requires not only the ability to understand what is implied but also the skills to understand what is implied in a reading text.
The Analysis of Phonology in First Language Acquisition Melayu Pattani in Children Three-Year-Old

The study aims at finding out how the children in Pattani, Thailand acquire their first language acquisition. The study is focused on the children of three-year-old due to the fact that they are able invited to communicate in two ways and already comprehend the time when their turn to talk and when other person’s turn to talk. Therefore, the researcher wants to research the utterances in process of first language acquisition in phonology. The study is conducted to address the language acquisition in Melayu Pattani due to the fact that it does not identify in Melayu Malaysia. In addition, the study uses a descriptive qualitative method for analyzing and describing the production of children's utterances. The data were taken by recording and interviewing the children. Finally, it is inferred that children absolutely do the simplification, such as substitution, omission, and assimilation to help them to produce the utterance when they make the conversation.
Confidential Machine Learning on Untrusted Platforms: A Survey

With the ever-growing data and the need for developing powerful machine learning models, data owners increasingly depend on various untrusted platforms (e.g., public clouds, edges, and machine learning service providers) for scalable processing or collaborative learning. Thus, sensitive data and models are in danger of unauthorized access, misuse, and privacy compromises. A relatively new body of research confidentially trains machine learning models on protected data to address these concerns. In this survey, we summarize notable studies in this emerging area of research. With a unified framework, we highlight the critical challenges and innovations in outsourcing machine learning confidentially. We focus on the cryptographic approaches for confidential machine learning (CML), primarily on model training, while also covering other directions such as perturbation-based approaches and CML in the hardware-assisted computing environment. The discussion will take a holistic way to consider a rich context of the related threat models, security assumptions, design principles, and associated trade-offs amongst data utility, cost, and confidentiality.
Extrinsic evaluation of UDPipe pre-trained models in application to hyper-hyponymic verbal pairs extraction from dictionary definitions

Our ongoing research is dedicated to the development of a method of computer-aided hyper-hyponymic verbal pairs extraction from dictionary definitions. Syntactic signals provide important information for the task. The main advantage of syntax-based method is that it allows one to distinguish hypernyms from synonyms, which is very difficult for distributional methods such as word embeddings as long as hypernyms and synonyms both tend to occur in similar contexts. This paper focuses on extrinsic evaluation of all three UDPipe pre-trained models for the Russian language. It is shown that despite high performance on different corpora the models’ perform poorly on our highly specific corpus consisting of dictionary definitions of verbs.
온라인 개학 중 학교현장실습의 실태와 영향요인 분석

The purpose of this study is to identify the limitations and possibilities of online practicum in the Korea teacher education program that were conducted in the context of COVID-19. For this purpose, the researchers interviewed eight pre-service teachers and two in-service teachers and analyzed relevant data. As a result of the study, there are various problems in online practicum; class observations, conducting classes without students being physically present, low levels of feedback, and lack of counseling opportunities and alternative programs. However, through online-practicum, pre-service teachers were able to acquire practical online-skills and assess their teaching aptitude. Factors affecting problems of online-practicum were (1) lack of basic government guidelines, (2) (2) lack of preparation for the emergency by the university(teacher training institution), (3) weak cooperation between the university and practicum school, (4) insufficient preparation for online class by a practicum school, (5) lack of active attitudes from in-service teachers and pre-service teachers. Based on the results of this research, specific guidelines are required for any online practicum and teacher training institutions should play a faithful role in managing the quality of the practicum. Administrative supports for online classes are needed. Finally, exploring ways to maximize the advantages of an online-practicum is required.
Methodology for the Curriculum Structuring, Formation and Analysis Based on a Quantitative Assessment of Logical Connectivity

The article deals with the curricula structuring through the concept of a module as an indivisible unit of educational content. The concepts of input and output terms are introduced, which form a semantic network of subject area knowledge, as well as the connectivity structure of the education modules of the educational program. The module is presented as some kind of operator for converting input terms into output ones, which allows us to present the curriculum itself as a digraph of the terms connectedness. An approach to the quantitative assessment of the teaching materials coherence in the curriculum is given. Ultimately, the curriculum itself is formally presented as a network planning model, where the learner’s potential abilities are the resources.
Las TIC como herramientas para entender la competencia habilitante en el nivel medio superior

espanolCuando se implemento el Aprendizaje Basado en Competencias (ABC) en el Nivel Medio Superior se senalo que estas competencias tambien son transversales ya que determinan el nivel de desempeno no solamente educativo sino personal en el empleo y a lo largo de la vida. Los alumnos requieren para su funcionamiento academico y su integracion social y profesional, adquirir ciertas destrezas y habilidades tanto instrumentales, como interpersonales y sistemicas que permitan generar una actitud o predisposicion a intervenir de un modo determinado ante una idea, persona o institucion con cierta eficacia y de modo positivo. Asi, el presente trabajo analiza la instrumentacion de la competencia habilitante de las Tic a lo largo de toda la formacion educativa en Mexico, pero en especial en el bachillerato. La propuesta senala de manera descriptiva las actividades que se proponen en la propuesta federal para el logro de la mencionada competencia habilitante. EnglishWhen competency-based learning was implemented at the Higher Education, it was pointed out that these competences are also transversal, since they determine the level of performance not only educational but personal in employment and throughout life. In this way, the students require for their academic functioning and their social and professional integration, to acquire certain instrumental, interpersonal and systemic skills and abilities that allow generating an attitude or predisposition to intervene in a certain way before an idea, person or institution with determined efficiency and positively. So, the present work analyzes the instrumentation of the ICT enabling competence throughout all educational training in Mexico, but especially in high school. The proposal describes in a descriptive way the activities proposed by federal educational authorities and the proposal for the achievement of the mentioned enabling competence.