Reviewerly/exHarmony huggingface dataset:
Extended 2D Consensus Hippocampus Segmentation

Hippocampus segmentation plays a key role in diagnosing various brain disorders such as Alzheimer's disease, epilepsy, multiple sclerosis, cancer, depression and others. Nowadays, segmentation is still mainly performed manually by specialists. Segmentation done by experts is considered to be a gold-standard when evaluating automated methods, buts it is a time consuming and arduos task, requiring specialized personnel. In recent years, efforts have been made to achieve reliable automated segmentation. For years the best performing authomatic methods were multi atlas based with around 80-85% Dice coefficient and very time consuming, but machine learning methods are recently rising with promising time and accuracy performance. A method for volumetric hippocampus segmentation is presented, based on the consensus of tri-planar U-Net inspired fully convolutional networks (FCNNs), with some modifications, including residual connections, VGG weight transfers, batch normalization and a patch extraction technique employing data from neighbor patches. A study on the impact of our modifications to the classical U-Net architecture was performed. Our method achieves cutting edge performance in our dataset, with around 96% volumetric Dice accuracy in our test data. In a public validation dataset, HARP, we achieve 87.48% DICE. GPU execution time is in the order of seconds per volume, and source code is publicly available. Also, masks are shown to be similar to other recent state-of-the-art hippocampus segmentation methods in a third dataset, without manual annotations.
A számítógépes vizualizáció múltja és jövője

Computer visualization has a long history with many great strides. However, the 21th century has seen the greatest progress in the development. The area continuously followed the evolution of the available hardwares. As more and more computing capacity based computers became available, computer visualization had been unfolded. New algorithms and technologies have appeared. Nowadays, there is no area in our daily lives where the need for visualization, whether it be a car, a computer game, or even an IoT device, does not appear. In this article, we examine and briefly review the dominant trend that modern real-time visualization currently follows. We cover the key technologies that are an integral part of today's rendering and the opportunities that could be decisive for future real-time rendering. It is difficult to predict the future of visualization, the technology adopted, as it depends heavily on what hardware vendor-supported technology becomes accepted and dominant.
Methodical Competence as the Purpose and Result of Vocational Training of the Future Teacher of Biology

Article is devoted to a problem of vocational training of the future teachers of biology. The theoretical substantiation of methodical competence of the future teacher of biology as the purpose and result of its vocational training is given. Different lines of thought concerning definition of the basic concepts of research are analysed: competence, methodical competence, methodical competence of the teacher of biology. Process of methodical preparation of the future teacher of biology and its basic components is characterised: the general preparation (methodologically-developing); specially-professional (psychology-pedagogical and methodical); personal preparation (self-education of the person of the future teacher, its self-determination). The offered system of methodical preparation of the future teacher of biology has allowed to develop structure of methodical preparation and to analyse its elements: (strategic problems of vocational training of the future teacher of biology), (tactical problems of preparation of the teacher to biology training in institutions of the general secondary education), a substantial component. The attention that preparation of the teacher of biology for training of pupils is a process of finding by the future teacher of methodical competence of training of biology of pupils of institutions of the general secondary education is focused. Methodical competence is a system personal formation which is shown in ability to realisation and the organisation of process of training of biology up-to-date, abilities of the successful decision of methodical problems and is based on theoretical and practical readiness for subject teaching. The conclusion, concerning necessity of finding by the future teacher of biology of methodical competence, as one of the preparation purposes in higher education institutions is drawn.
Improvements of Automatic Extraction of FA Words Tendency using Non_linear Approach

Field association (FA) terms are used to identify the subject of text (document field) by extracting specific words in that text. In this paper we use FA terms to study the effect of time change on specific terms by calculating the frequency of this terms, which associated with the archive field in a specific period. This paper also introduces a new approach for automatic evaluation of the stabilization classes using non-linear approach. The stabilization classes refer to the changing of FA terms with time in a specific period. The new approach improves the performance of decision tree than linear approach by using non-linear approach. The corpus that used in this approach has number of 1,356 files, and it is about 7.49 MB, after comparing the presented approach with the traditional one, we conclusion that the new approach enhanced the F-measure for increment, steady, decrement classes by 7.7%, 3.1%, 2.2%, sequentially.&amp;nbsp;&amp;nbsp;
WEB INFORMATION QUALITY VERSUS TURBULENCE ON URL DECAY: CRITIC ON RELIABILITY OF AUTHORITY CITATIONS

Internet usage provides environment for learning, research, entertainment, and business.Web design is crucial for marketability of the Web page, whereas, Web information is essential for enhancing research skills for academic and institutional growth and development.This study aims to assess information provided in the various Internet sites according to several literature content compliance and gaps on URL forming rots over time as inaccessible URLs may be subject to copyright infringement.
BASIC CONCEPTS OF THE THEORY AND TECHNIQUE OF TRANSLATION OF SCIENTIFIC AND TECHNICAL LITERATURE

Conference proceedings are devoted to the development of modern science under global changes. General issues of the engineering, medical, psychological, philological, economic sciences, history of art, social communications and so on are considered. The publication is designed for scientists, lecturers, postgraduate students, students, as well as for the general readers. International Scientific Conference Development of Modern Science Under Global Changes: Conference Proceedings, 22th May, 2020. Riga, Latvia: Baltija Publishing. 104 pages.
Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning

Learning and planning in partially-observable domains is one of the most difficult problems in reinforcement learning. Traditional methods consider these two problems as independent, resulting in a classical two-stage paradigm: first learn the environment dynamics and then plan accordingly. This approach, however, disconnects the two problems and can consequently lead to algorithms that are sample inefficient and time consuming. In this paper, we propose a novel algorithm that combines learning and planning together. Our algorithm is closely related to the spectral learning algorithm for predicitive state representations and offers appealing theoretical guarantees and time complexity. We empirically show on two domains that our approach is more sample and time efficient compared to classical methods.
Understanding Generalization in Neural Networks for Robustness against Adversarial Vulnerabilities

Neural networks have contributed to tremendous progress in the domains of computer vision, speech processing, and other real-world applications. However, recent studies have shown that these state-of-the-art models can be easily compromised by adding small imperceptible perturbations. My thesis summary frames the problem of adversarial robustness as an equivalent problem of learning suitable features that leads to good generalization in neural networks. This is motivated from learning in humans which is not trivially fooled by such perturbations due to robust feature learning which shows good out-of-sample generalization.
Reading Difficulties of Grade 5 Pupils in English

The main purpose of the study was to diagnose the reading difficulties of grade 5 pupils in English. The researchers made use of descriptive method to obtain the data on the reading difficulties, comprehension, and behavioral performance of the respondents. To gather the data, the researchers adopted the reading selections from Philippine Informal Reading Inventory as a tool in examining the reading level of the pupils. As for the respondents’ reading miscues and behavioral performance, a teacher-made questionnaire was used to determine the learning areas that require intervention. The findings of the study pointed out that grade 5 pupils had difficulties on word recognition and reading comprehension. They tend to mispronounce English words and their behavior affects their performance while reading. A proposed reading program was included in this study to provide a reading remediation to learners with reading difficulties. Alongside with this initiative, teachers may conduct drill lessons to monitor progress of the pupils on areas that need improvement. Teachers must also be aware on the common errors committed by the learners to be able to provide remedial instruction.
Web Service to Automate Bibliographic Research – Case of Dependability Ontology

In order to identify the existence of an ontology of dependability, we conducted a bibliographic review. However, we encountered a real problem while researching and selecting articles that address this issue. Indeed the research process in various scientific databases with standard techniques involve the application of a number of manual and duplicative steps. This makes it a fairly costly and faulty process. To surmount these challenges, we offer a solution that automates search and selection items. The proposed solution is essentially derived from the popular method called systematic mapping. In this article, we suggest a Web Service as an implementation of our proposed approach. This Web Service will allow users to query scientific databases to obtain the metadata of selected articles. Our proposal will make the selection of scientific articles easier and faster.
The Behavioral Investigation of Industry 4.0 Concept: A Research On Twitter

&#x0D; &#x0D; &#x0D; &#x0D; Abstract:&#x0D; Aim: This paper is going to investigate how Industry 4.0 concept especially the components of it, behaves in social networks and the context of this innovative approach find a place in time in means of content and sentiment comprising.&#x0D; Design / Research methods: Expeditious progress in industrialization and information techniques has made great advancement in developing the next span of production technology. Industry 4.0 is an imperative action where the intention is the alteration of modern production through digitalization and profiteering of the capabilities of new advancements. Today, the absence of powerful appliances still feigns a significant impediment for utilizing the ample potential of Industry 4.0. Notably, behavioral approaches are essential for understanding Industry 4.0, which professes novel trials. This paper briefly surveys the area of Industry 4.0 as it relates to behavioral operations by using sentiment analysis and social network analysis methods and tools by describing features of the relationship network either through numerical and visual representation&#x0D; Conclusions / findings: First of all, it should be presumed that the name Industry 4.0 describes various, fundamentally internet-based developments in manufacturing operations. These advancements do not only have technological but moreover accomplished organizational engagements. Appropriately, a shift from product to service orientation is assumed. Following, the introduction of novel varieties of businesses can be envisioned which embraces new particular functions within the production process sequentially the value-creation networks.&#x0D; Originality / value of the article: Within the context of the current state of the art in operations management literature, this paper fulfills the gap between behavioral operations and industry 4.0 context for the researchers both in operations management and behavioral sciences will benefit from this analysis.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; Keywords: Behavioral Operations Management, Sentiment Analysis, Industry 4.0, Social Network Analysis. &#x0D; JEL: C88, D23, D24, E71, M11, O14, O33&#x0D; &#x0D; &#x0D; &#x0D;
THE IMPLEMENTATION OF GIST (GENERATING INTERACTION BETWEEN SCHEMATA AND TEXT) STRATEGY TO IMPROVE STUDENTS’ READING COMPREHENSION OF THE TENTH GRADE STUDENTS AT SMAN 16 MAKASSAR

Abstract&#x0D; The objective of the research was to find out whether the implementation of GIST strategy can improve reading comprehension of the tenth grade students of SMAN 16 Makassar. The researcher applied Pre-Experimental method where one group of students was involved .The sample consisted of 40 students who were taken from the tenth grade (X MIA 4 Class) students of SMAN 16 Makassar using purposive sampling technique. The instrument of this research was reading comprehension test which consist of 20 multiple choice items. The data were collected in pretest and posttest and analyzed using SPSS. The result of data analysis showed that the mean score of pretest was 42.00 and posttest was 78.62. It indicates that there was improvement between those mean score. The standard deviation in pretest 14.268 and the posttest was 10.377. In addition, the t-test value of posttest was 0.00 which was smaller than (α) = 0.05. Therefore it concluded that the Implementation of GIST strategy improves the reading comprehension of the tenth grade students at SMAN 16 Makassar.&#x0D; &#x0D; Key terms: Reading Comprehension, GIST (Generating Interaction Between Schemata and Text).&#x0D; &#x0D; Abstrak&#x0D; Tujuan dari penelitian ini adalah untuk mengetahui apakah penerapan strategi GIST dapat meningkatkan pemahaman membaca siswa kelas sepuluh SMAN 16 Makassar. Peneliti menerapkan metode Pra-Eksperimental di mana satu kelompok siswa terlibat. Sampel terdiri dari 40 siswa yang diambil dari siswa kelas X (Kelas X MIA 4) SMAN 16 Makassar dengan menggunakan teknik purposive sampling. Instrumen penelitian ini adalah tes membaca pemahaman yang terdiri dari 20 item pilihan ganda. Data dikumpulkan dalam pretest dan posttest dan dianalisis menggunakan SPSS. Hasil analisis data menunjukkan bahwa skor rata-rata pretest adalah 42,00 dan posttest adalah 78,62. Ini menunjukkan bahwa ada peningkatan antara skor rata-rata tersebut. Simpangan baku pada pretest 14.268 dan posttest adalah 10.377. Selain itu, nilai uji-t postes adalah 0,00 yang lebih kecil dari (α) = 0,05. Oleh karena itu disimpulkan bahwa Implementasi strategi GIST meningkatkan pemahaman membaca siswa kelas sepuluh di SMAN 16 Makassar.&#x0D; Kata kunci: Pemahaman Membaca, GIST
Virtual Keyboard Recognition with e-Textile Sensors

In this study, we propose a gesture recognition method using e-textile sensors and involving the pressing of numeric keys from "0" to "9".An e-textile sensor comprises a double-layer structure with complementary resistance characteristics, and it is attached to the garment to obtain a resistance signal.For gesture recognition, we tested dynamic time warping (DTW), machine learning, long short-term memory (LSTM), and bidirectional LSTM (BiLSTM).Before applying each machine learning technique, we performed normalization and resized the data to ensure that they are of the same length.A total of 120 iterations were performed for each gesture for a single subject.The results indicate that the lowest gesture classification accuracy for DTW was 74.2%, followed by 78.8 and 91.6% for LSTM and BiLSTM, respectively.
Towards General RPG Playing

General videogame playing has come a long way in a short period of time, but remains at the level of solving relatively short games made up of distinct and isolated episodes. Even simple console role-playing games (RPGs) are far beyond the reach of current techniques, requiring the synthesis of cultural knowledge with compositional reasoning over several interconnected sub-games. We explore how the challenges of playing these games could spark new advances in compositional analysis of games and common-sense reasoning. General RPG playing can leverage advances in episodic general game playing and in areas like text understanding, image classification, and automated game design learning. It has direct applications in design support and AI-based game design, and the techniques used to enable it could generalize to other families of games such as adventure, open-world, and simulation games. In this paper, we describe the motivation behind general RPG playing in a sub-domain of Nintendo Entertainment System (NES) RPGs, some promising approaches to some of its fundamental issues, and immediate next steps; we conclude by describing a few concrete benchmark problems on the path towards automated play of these complex games.
AN ANALYSIS OF THE STUDENTS’ PARAGRAPH COMPOSITIONPERFORMANCE

An investigation ofcomposition performanceisimportant matter of contention toprobethat one may achievefurthercompelling and authenticending. Paragraph composition performance is one of the concerns.Thetarget of the contemporaryanalysisistoinspectthe extent to which the students’ paragraph composition performance. Therefore, survey study was conceived to achieve the purpose. The third semester students of English Study Program of FKIP – UNISI Tembilahan were determined as the shareholders. They were requiredto composetwo kinds ofparagraph; process paragraph and comparison/contrast paragraph. There are five evaluation criterions; format, punctuation and mechanics, contents, oganization, and sentence structure. Dealing the results ofdata analysis,itdisclosed that theirparagraph composition performance on each compositionelements was diverse. It could be justified from the datawhich sixparticipants (27.3%) worked outin the admirablegrade, nineof them (40.9%) were recognized in competent level, and sevenparticipants (31.8%) could achieve in sufficientcategory. As the final comment, it could be determined that their paragraph compositionperformance was in the sufficient to admirable level. Nevertheless, to gain better endings, more practice isbrought to their mind.
ANALYSIS OF READING COMPREHENSION FINAL TEST AT ENGLISH DEPARTMENT OF MUHAMMADIYAH ACEH UNIVERSITY

The aim of this study is not only to analyze the model and the items test set by lecturer of Reading Comprehension subject but also the ability of students according to the item questions of each final test. This study analyzes the contents taken from the document test and it used descriptive quantitative approach. The gained data derived from three Reading subjects, they are: Intensive Reading Comprehension, Reading Comprehension III dan Academic Reading. The total number of the items from those three subjects is 60 items. The findings revealed that the kind of questions asked by lecturers varied, namely; Multiple Choice, Open-ended Question, Word Matching, and True and False. Based on the those documents the writer found that 6 questions about Main Idea, 16 questions about Vocabulary, 4 about references, 6 questions about inference and 28 questions about details. Then, the results of students' reading ability in answering the items were; main idea: ​​63.59%, Detail: 76, 92%, Inference: 44,04, Reference ; 86, 89% and Vocabulary : 73,45 %. From the five aspects students were better to answer questions in the Reference item. The implication of this research is to provide input to examiners and lecturers in giving material and in testing students at the end of the semester and to improve the ability to make test items.
Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract)

Automatic speech recognition(ASR) systems play a key role in many commercial products including voice assistants. Typically, they require large amounts of high quality speech data for training which gives an undue advantage to large organizations which have tons of private data. We investigated if speech data obtained from publicly available sources can be further enhanced to train better speech recognition models. We begin with noisy/contaminated speech data, apply speech enhancement to produce 'cleaned' version and use both the versions to train the ASR model. We have found that using speech enhancement gives 9.5% better word error rate than training on just the original noisy data and 9% better than training on just the ground truth 'clean' data. It's performance is also comparable to the ideal case scenario when trained on noisy and it's ground truth 'clean' version.
A semantic relation preserved word embedding reuse method

net Recurrent net 图 1 (网络版彩图) 深度自然语言处理任务框架示意图 Figure 1 (Color online) The illustration of the deep NLP framework 量参数的数量是任务本身数量的 10 倍左右或者更高时, 联合词向量一起端到端进行训练会有一定的 困难.
Topic Subject Creation Using Unsupervised Learning for Topic Modeling

We address the problem of topic mining and labelling in the domain of retail customer communications to summarize the subject of customers inquiries. The performance of two popular topic mining algorithms - Non-Negative Matrix Factorization (NMF) and Latent Dirichlet Allocation (LDA) &amp;ndash; were compared, and a novel method to assign topic subject labels to the customer inquiries in an automated way was proposed. Experiments using a retailer&amp;rsquo;s call center data verify the efficacy and efficiency of the proposed topic labelling algorithm. Furthermore, the evaluation of results from both the algorithms seems to indicate the preference of using Non-Negative Matrix Factorization applied to short text data.
Social Media Content Analysis: Study on Brand Posts of Telco Companies

Social media has become more popular in recent years because its interactivity that lead direct engagement from users.Engagement is the first step in building loyalty on social media marketing.Telco companies in Indonesia faced a fierced competition to retain their consumer from shifting, since Indonesian consumer are very priced sensitive but yet expect maximum benefit from their product.This research aims to study how cellular operator as a part of telco industry in Indonesia used their social media and investigate the affordance experience dimension of perceptual, social, epistemic, and embodied gainconsumer engagement.Since cellular operator have their own social media brand page, they don't have a knnowledge from their post on social media that affected engagement from their consumer to the brand.This study uses data collection method by retrieving data from Facebook brand page of five cellular operators with the highest number of users in Indonesia.Total of 923 brand post from are collected from July -September 2019.Four dimention of affordance experience are used to categorized each brand post.The result and discussion from this research are further discussed in this paper.
Making Educational Technology Invisible

Interfaces are what separates us from the tools we use. Interfaces are presently becoming more natural and human-oriented. We are moving from keyboard-oriented tools to those that exploit other human senses, such as sight and sound. In this paper, we explore how voice recognition and generation, augmented reality, and unperceivable sensors help in making educational technology more invisible.