Reviewerly/exHarmony huggingface dataset:
Test-taking strategies and students’ achievement in EFL reading tests

This research aims at investigating the effects of reading test-taking strategy training on EFL students' performance in English reading tests.The participants of the research were 90 prep-class students chosen randomly and divided into three groups of 30 students as face-to-face training group, online self-training group, and control group.The first group was involved in strategy training sessions for six weeks in school context (face-to-face) whereas the second group was only informed about the contend of the training sessions and directed to study through online strategy videos (online self-training).The last group was the control group the who were excluded from strategy training sessions.The reading test scores of the participants were analyzed via SPSS 16 with the aim of revealing whether or not there is an impact of strategy training.Moreover, semi-structured interviews were carried out with the participants, and the findings were analyzed through content analysis.Results of the research revealed that (a) the students' awareness of test taking strategies are in parallel with their test scores; (b) face-to-face strategy training was found to be more effective than online strategy training; (c) strategies related to 'drawing inference' and 'guessing the meaning from the context' were found to be the most effective ones while strategies such as detecting the question types, finding the main idea, skimming and scanning were other important strategies.The results suggested that strategy training on test taking might be included in the regular curriculums; students' awareness of test taking strategies should be fostered starting from the early stages of formal education; reading theories and strategies might be integrated into current reading courses with an inter-disciplinary model.
Optimization of English Speaking Skill and English Grammatical Competence of Second Semester College Students in English Literature of Bung Hatta University Through Role-play Technique: Classroom Action Research of English As Foreign Language

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Mining and Representing Unstructured Nicotine Use Data in a Structured Format for Secondary Use

The objective of this study was to use rules, NLP and machine learning for addressing the problem of clinical data interoperability across healthcare providers.Addressing this problem has the potential to make clinical data comparable, retrievable and exchangeable between healthcare providers.Our focus was in giving structure to unstructured patient smoking information.We collected our data from the MIMIC-III database.We wrote rules for annotating the data, then trained a CRF sequence classifier.We obtained an f-measure of 86%, 72%, 69%, 80%, and 12% for substance smoked, frequency, amount, temporal, and duration respectively.Amount smoked yielded a small value due to scarcity of related data.Then for smoking status we obtained an fmeasure of 94.8% for non-smoker class, 83.0% for current-smoker, and 65.7% for past-smoker.We created a FHIR profile for mapping the extracted data based on openEHR reference models, however in future we will explore mapping to CIMI models.
Pembuatan Aplikasi Buta warna untuk penderita buta warna

Color blindness is the reason a person is unable to distinguish certain colors. Color blindness is experienced by someone from birth because of lack or absence of pigment in the retinal cone cells of the eye. So that someone will be difficult to distinguish and identify colors. The purpose of making this color-blind application is to help people with color blindness and know the color by making color transfusion and color correction to display names, RGB and HSV values of a color. This Color Blind application is an Android OS application that will be embedded in a smartphone that can be easily used by people with color blindness
Model-based clustering in very high dimensions via adaptive projections

Mixture models are a standard approach to dealing with heterogeneous data with non-i.i.d. structure. However, when the dimension $p$ is large relative to sample size $n$ and where either or both of means and covariances/graphical models may differ between the latent groups, mixture models face statistical and computational difficulties and currently available methods cannot realistically go beyond $p \! \sim \! 10^4$ or so. We propose an approach called Model-based Clustering via Adaptive Projections (MCAP). Instead of estimating mixtures in the original space, we work with a low-dimensional representation obtained by linear projection. The projection dimension itself plays an important role and governs a type of bias-variance tradeoff with respect to recovery of the relevant signals. MCAP sets the projection dimension automatically in a data-adaptive manner, using a proxy for the assignment risk. Combining a full covariance formulation with the adaptive projection allows detection of both mean and covariance signals in very high dimensional problems. We show real-data examples in which covariance signals are reliably detected in problems with $p \! \sim \! 10^4$ or more, and simulations going up to $p = 10^6$. In some examples, MCAP performs well even when the mean signal is entirely removed, leaving differential covariance structure in the high-dimensional space as the only signal. Across a number of regimes, MCAP performs as well or better than a range of existing methods, including a recently-proposed $\ell_1$-penalized approach; and performance remains broadly stable with increasing dimension. MCAP can be run "out of the box" and is fast enough for interactive use on large-$p$ problems using standard desktop computing resources.
Cyclic Codes with Four Weights and Sequence Families with Four‐Valued Correlation Functions

The value distribution of an exponential sum based on a class of Niho exponents is determined. As applications, we also completely determine the weight distribution of a class of four-weight cyclic codes and the correlation distribution among sequences in a sequence family, which extend some known results.
Point-to-Point Video Generation

While image manipulation achieves tremendous breakthroughs (e.g., generating realistic faces) in recent years, video generation is much less explored and harder to control, which limits its applications in the real world. For instance, video editing requires temporal coherence across multiple clips and thus poses both start and end constraints within a video sequence. We introduce point-to-point video generation that controls the generation process with two control points: the targeted start- and end-frames. The task is challenging since the model not only generates a smooth transition of frames, but also plans ahead to ensure that the generated end-frame conforms to the targeted end-frame for videos of various length. We propose to maximize the modified variational lower bound of conditional data likelihood under a skip-frame training strategy. Our model can generate sequences such that their end-frame is consistent with the targeted end-frame without loss of quality and diversity. Extensive experiments are conducted on Stochastic Moving MNIST, Weizmann Human Action, and Human3.6M to evaluate the effectiveness of the proposed method. We demonstrate our method under a series of scenarios (e.g., dynamic length generation) and the qualitative results showcase the potential and merits of point-to-point generation. For project page, see https://zswang666.github.io/P2PVG-Project-Page/
Data Privacy in the Smart Grid: A Decentralized Approach

Evolution toward the smart grid includes implementation of elements such as smart meters, embedded microprocessors, two-way communication systems from consumers to system operators, and automated demand response as supported through dynamic pricing.Dynamic pricing throughout the smart grid will require frequent transfer of energy consumption data from the customers to the ISOs.Privacy and security issues related to transferring this data are widely studied.However, typical frameworks rely on a trusted third party, such as the ISO or a load aggregator, that would then have access to all of the consumer data.This paper proposes a Bitcoin-like decentralized model as a solution for secure information transfer within the smart grid, eliminating the presence of a centralized data aggregator or other third party operator.Each smart meter participates as an equal peer in the proposed peer-to-peer network, and elements of authentication, confidentiality and data verification are developed similar to the existing Bitcoin framework.The contribution of this paper is the proposed framework for the smart grid which cryptographically secures the transfer of energy consumption data while ensuring privacy.
Use of Software Agent Technology in Management Information System: A Literature Review and Classification

Technological innovations over the years have accentuated the workings in corporate- connected organizations and different application platforms. Hence, a unified management information system (MIS) that can utilize the Web and propel programming developments is required. Software agents, the latest developments in computer software technology, can be utilized to rapidly and effortlessly build integrated information systems. Consequently, 59 research papers on the use of software agents in MIS were identified from top 40 MIS journals published between 2007 and 2017. Then, we reviewed and classified all the research papers according to two categories: application fields and application categories. The application fields consisted of eight sub-groups: manufacturing, telecommunication systems, traffic and transportation management, information filtering and gathering, electronic commerce, business process management, entertainment, and medical care; whereas the application categories consisted of three sub-groups: multi-agent systems, personal assistants, and multi-agent simulation. The research papers were further divided into journal and year of publication, and journal and application field. The objective of our research was to understand the trend of the use software agent technology in MIS by examining the published research paper beside to add knowledge and content to the information system academic discipline.
SITUATED LEARNING IN THE NEW WORLD OF TECHNOLOGY WITH COSITO – THE TEACHING AND LEARNING PLATFORM

Appears in: INTED2019 Proceedings Publication year: 2019Pages: 959-966ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.0321Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
FROM STEM TO STEAM USING LEGO MINDSTORMS IN LEARNING PROJECTS OBTAINED FROM LOMCE

Appears in: INTED2019 Proceedings Publication year: 2019Pages: 5592-5598ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.1374Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
The Attitude Of Digital Natives Towards Intrapersonal Communication

Intrapersonal communication is an important element of the human communication process which embodies the essence of the process of communication. It is at the start of communication that impulses are perceived and processed for the needs of external communication. The study demonstrated that the same tools of communications techniques are observable both in intrapersonal communications and in tools that are characteristic of the communication process in general: from the perception of impulses to the translation and adaptation of the information that is received and an active or passive response to the informative material that is received. In order to study the particular features of intrapersonal communication, digital natives as an analysis group were used because they have an active day-to-day communicative experience. The author conducted a survey among young adults, asking them about their attitude to intrapersonal communication and their opinion on the importance of this form of communication in the complex process of human interpersonal communication for the purposes of the research. The survey established the frequency of the use of intrapersonal communication, times, topics, and content, and the importance of the inner dialogue. The survey proved that intrapersonal communication is a very intensely-used form of communication among young adults which introduces the next step - communication with the outside world. The study concluded that communication processes can also occur in a single person as a dialogue. Intrapersonal communications are a continuous process of which the recipient is aware only under the circumstances of an extremely strong impulse.
0465 Performance of Revised Machine Learning Models for Prediction of Non-Diagnostic Home Sleep Apnea Tests

Home sleep apnea testing (HSAT) is a less expensive modality than in-lab polysomnography (PSG). Most patients with non-diagnostic HSAT studies (AHI < 5/hr) should undergo in-lab PSG due to the risk of false negatives. We previously developed machine learning models to predict which patients are at high risk of a non-diagnostic HSAT using validated patient questionnaires and anthropomorphic measurements collected during routine clinical practice as inputs. The current study extends this work, examining revised machine learning models that incorporate several additional questionnaire items. Data from 415 patients undergoing HSAT within the Greater Los Angeles VA were analyzed. Pre-HSAT surveys included the Epworth Sleepiness Scale, Insomnia Severity Index, Patient Health Questionnaire-2, STOPBANG and 13 de novo items (e.g. use of sleep aids and caffeine, sleep schedule, nap frequency, diagnosis of post-traumatic stress disorder [PTSD]). Data were split into 85% training and 15% testing sets. Missing data (2.3%) was imputed using a k-nearest neighbors algorithm. Random forest and gradient-boosted decision tree (GBDT) models were trained using the Partial Area Under the Precision-Recall Curve (pAUPRC) as the optimization metric. Repeated k-fold cross-validation was used in addition to validation using the held-out test set. The GBDT model yielded the best result (pAUPRC on test dataset: 0.628 for GBDT versus 0.606 for random forest). Using the preferred calibration threshold, this model achieved a sensitivity of 0.43 and specificity of 0.96 on the test dataset. The following items significantly improved predictive model performance: 1) rank order representation of patient-reported bedtime and waketime, 2) binary representation of PTSD presence or absence, 3) frequency of sleep aid medication use, 4) number of caffeinated drinks per day, and 5) number of naps per week. These de novo items carried greater predictive value than all other model inputs with the exception of age, body mass index (and its components) and collar size. This study identifies several new questionnaire items that demonstrate promise for inclusion in machine learning models as important predictors of non-diagnostic HSAT results. ASPIRE Fellowship Grant
MEMBANGUN KARAKTER SISWA MELALUI LITERASI DIGITAL DALAM MENGHADAPI PENDIDIKAN ABAD 21 (REVOLUSI INDUSTRI 4.0)

The development of the world at this time has changed the era of industrial revolution 4.0, human life forms have shaped information. Therefore, in preparation that is supported and able to compete globally, as well as regulating the development of technology is very important for all people and for the future of the nation and state. Therefore digital literacy needs to be developed in the world of education today to build a better national character and be better prepared for the 21st century education era. This article aims to learn how to build the character of students as students from elementary school to digital secondary school through Digital Literacy (Digital-Age Literacy) in learning for education with 21st Century education. Education with this literal digital dimension can develop digital literacy learning materials and methods in schools and outside schools, in relation to the 21st century education era (Industrial Revolution 4.0). This study uses a Qualitative Descriptive method with a scientific background, the aim of which is to describe the phenomena that occur in the current environment, data obtained through observation, interviews and documentation .
Reducing Adversarial Example Transferability Using Gradient Regularization

Deep learning algorithms have increasingly been shown to lack robustness to simple adversarial examples (AdvX). An equally troubling observation is that these adversarial examples transfer between different architectures trained on different datasets. We investigate the transferability of adversarial examples between models using the angle between the input-output Jacobians of different models. To demonstrate the relevance of this approach, we perform case studies that involve jointly training pairs of models. These case studies empirically justify the theoretical intuitions for why the angle between gradients is a fundamental quantity in AdvX transferability. Furthermore, we consider the asymmetry of AdvX transferability between two models of the same architecture and explain it in terms of differences in gradient norms between the models. Lastly, we provide a simple modification to existing training setups that reduces transferability of adversarial examples between pairs of models.
USE OF EYE TRACKING METHOD IN THE RESEARCH FOR VISUALIZATION AND INTERPRETATION OF STUDENT STRATEGIES IN SOLVING NATURAL SCIENCE-BASED TASKS

USE OF EYE TRACKING METHOD IN THE RESEARCH FOR VISUALIZATION AND INTERPRETATION OF STUDENT STRATEGIES IN SOLVING NATURAL SCIENCE-BASED TASKS
On Cohen’s Critique of Technology and Social Justice

It is supposed that to be just in society is the intrinsic pursuit of Marxist theory in Marx's original text.While as the result of historical context, according to Marx, the just society can be realized in a far future.Cohen holds materialism standpoint to illustrate historical materialism creatively by functional explanation in the modern history context.In a new time with much more advanced science and technology, he is keeping going with the route of Marxism for overcoming the technique alienation and argues that in order to realize freedom, equality and justice, appealing to empirical critique of technology and exploration of social theory is essential.The demonstration of that freedom, equality and justice are compatible, which is a cornerstone of practical just social theory.As Cohen is in the analytical tradition, his creative functional explanation presents obvious empiricism and analytical character.He digs out the key of resolving problem of development in moral dimension apart from the materialism, and conducts the argument to attack the political designs, which separates free distribution in market, quality in society, and just spirit from each other.This essay is intended to figure out Cohen's argument that is based on the traditional Marxism and stand, while points out a new way to help people reach the just society at the much more near future.
IMPORTANCE OF LABORATORY PRACTICES DURING MATERIAL SCIENCE COURSES FOR ENGINEERING STUDENTS

Appears in: INTED2019 Proceedings Publication year: 2019Pages: 3365-3372ISBN: 978-84-09-08619-1ISSN: 2340-1079doi: 10.21125/inted.2019.0872Conference name: 13th International Technology, Education and Development ConferenceDates: 11-13 March, 2019Location: Valencia, Spain
USE OF ETHNO CULTURAL ELEMENTS IN EDUCATIONAL PROCESS

1 Southern Federal University (RUSSIAN FEDERATION)2 Chechen State Pedagogical University (RUSSIAN FEDERATION)
Geochemical evolution in Nodusahn Zn-Pb hydrothermal deposit with an emphasis on ore mineralography and sulfide analysis

Geochemical evolution in Nodusahn Zn-Pb hydrothermal deposit with an emphasis on ore mineralography and sulfide analysis
Reasoning about Block-based Cloud Storage Systems

Owing to the massive growth in the storage demands of big data, Cloud Storage Systems (CSSs) have been put forward to improve the storage capacity. Compared with traditional storage systems, CSSs have lots of advantages, such as higher capacity, lower cost, and easier scalability. But they are also with higher complexity. In order to ensure CSSs to be reliable, it is necessary to prove the correctness of CSSs management programs. In fact, we are going to verify Block-based Cloud Storage Systems (BCSSs), since BCSSs are the most popular CSSs. In this paper, the correctness of management programs in BCSSs have been proven, and a verification framework based on separation logic is proposed to finish the proven process. The main contributions are as follows. (1) A novel framework with two-tier heap structure is constructed to reflect the characteristics of BCSSs, and a modeling language is defined based on it. (2) Assertions based on separation logic is constructed to describe the properties of BCSSs. (3) The Hoare-style specifications are proposed to reason about the BCSSs. The results demonstrate that the correctness and reliability of BCSSs can be verified by the above proposed methods. Furthermore, the proposed specifications is sound in the application of reasoning about BCSSs.
TOWARDS EFFICIENT AND CONTINUING USAGE OF THE DIGITAL CULTURE ECOSYSTEM FOR LEARNING PURPOSES

1 Institute of Mathematics and Informatics, Bulgarian Academy of Sciences (BULGARIA)2 Kettering Universiy (UNIITED STATES) / Institute of Mathematics and Informatics, Bulgarian Academy of Sciences (BULGARIA)
Stereotypic Repetitive Hand Flapping Movement Detector for Children with Autism

The prevalence of autism spectrum disorder (asd) has increased at a significant rate in recent years, especially in developed nations such as the united states, japan, and south korea. Children affected with autism tend to exhibit a spectrum of symptoms depending on the severity of the disease. These behaviors are primarily repetitive, self-stimulatory, and stereotypic behaviors such as hand flapping (i.e., repeatedly shaking their hands), body rocking (i.e., swaying their body back and forth), drumming, walking around in a confined space, and walking with shortened steps on toes, etc. in this research project, a simple reminder system is proposed using wearable sensors to automatically detect significant hand flapping movements. The reminder system consists of a speaker encoded with the voice of mother, father, or any other custom designed voice. an algorithm was designed to trigger the audio device when the child showed significant hand flapping activity (i.e., hand flapping more than 10 times) within a given time frame. the time frame and the hand flapping count can be customized per severity of the child's symptoms. The device was successfully tested in the laboratory by simulating the hand flapping movement shown by the child. It is hoped that this system provides a valuable service to parents and the child by alerting the child to autistic movements, preventing the habit from turning into self-injurious behavior, and taking away the burden from parents and caregivers.