Reviewerly/exHarmony huggingface dataset:
The Early Modern Dutch Mediascape. Detecting Media Mentions in Chronicles Using Word Embeddings and CRF

While the production of information in the European early modern period is a wellresearched topic, the question how people were engaging with the information explosion that occurred in early modern Europe, is still underexposed.This paper presents the annotations and experiments aimed at exploring whether we can automatically extract media related information (source, perception, and receiver) from a corpus of early modern Dutch chronicles in order to get insight in the mediascape of early modern middle class people from a historic perspective.In a number of classification experiments with Conditional Random Fields, three categories of features are tested: (i) raw and binary word embedding features, (ii) lexicon features, and (iii) character features.Overall, the classifier that uses raw embeddings performs slightly better.However, given that the best F-scores are around 0.60, we conclude that the machine learning approach needs to be combined with a close reading approach for the results to be useful to answer history research questions.
Probing Integrated Household Information Systems for Integrated Food Practices

Recent publications propose concepts of systems that integrate the various services and data sources of everyday food practices. However, this research does not go beyond the conceptualization of such systems. Therefore, there is a deficit in understanding how to combine different services and data sources and which design challenges arise from building integrated Household Information Systems. In this paper, we probed the design of an Integrated Household Information System with 13 participants. The results point towards more personalization, automatization of storage administration and enabling flexible artifact ecologies. Our paper contributes to understanding the design and usage of Integrated Household Information Systems, as a new class of information systems for HCI research.
Bridging Natural Language and Graphical User Interfaces

“Language as symbolic action” (https://en.wikipedia.org/wiki/Kenneth_Burke) has a natural connection with direct-manipulation interaction (e.g., via GUI or physical appliances) that is common for modern computers such as smartphones. In this chapter, we present our efforts for bridging the gap between natural language and graphical user interfaces, which can potentially enable a broad category of interaction scenarios. Specifically, we develop datasets and deep learning models that can ground natural language instructions or command into executable actions on GUIs, and on the other hand generate natural language descriptions of user interfaces such that a user knows how to control them in language. These projects resemble research efforts intersecting Natural Language Processing (NLP) and HCI, and produce datasets and opensource code that lay a foundation for future research in the area.
The Development of a Bilingual English-Oshikwanyama Dictionary App

A significant number of indigenous communities in Africa are struggling to maintain traditions amongst themselves and others, in a system that is dominated by a western worldview. Like the rest of Africa, Namibians are also finding it hard to preserve and use their indigenous languages in their day-to-day communication. With the decrease in use of native languages, the future generations might not have sufficient knowledge of the language and they will be unable to relate to their heritage. Hence, there is a possibility of the language becoming extinct. Dictionaries are known to improve communications for both native and non-native users of any language, and a digital mobile dictionary application is even more convenient. In this study, an Oshikwanyama-English dictionary app is developed in android studio using the Java language, and using the Incremental Iterative Delivery Programming methodology. A post-questionnaire was carried out after using the dictionary. The study found that the dictionary is easy to use, effective and can improve communication. However, a bigger dataset will have to be incorporated, before the app goes into the market.
Don't Discard All the Biased Instances: Investigating a Core Assumption in Dataset Bias Mitigation Techniques.

Existing techniques for mitigating dataset bias often leverage a biased model to identify biased instances. The role of these biased instances is then reduced during the training of the main model to enhance its robustness to out-of-distribution data. A common core assumption of these techniques is that the main model handles biased instances similarly to the biased model, in that it will resort to biases whenever available. In this paper, we show that this assumption does not hold in general. We carry out a critical investigation on two well-known datasets in the domain, MNLI and FEVER, along with two biased instance detection methods, partial-input and limited-capacity models. Our experiments show that in around a third to a half of instances, the biased model is unable to predict the main model’s behavior, highlighted by the significantly different parts of the input on which they base their decisions. Based on a manual validation, we also show that this estimate is highly in line with human interpretation. Our findings suggest that down-weighting of instances detected by bias detection methods, which is a widely-practiced procedure, is an unnecessary waste of training data. We release our code to facilitate reproducibility and future research.
A robot navigation algorithm based on cognitive mechanism of hippocampus

The hippocampal formation in the animal brain is the core brain region to realise spatial cognition. Aiming at the problems of inaccurate loop closure detection and lack of effective obstacle perce...
Adaptable Agent Populations via a Generative Model of Policies

In the natural world, life has found innumerable ways to survive and oftenthrive. Between and even within species, each individual is in some mannerunique, and this diversity lends adaptability and robustness to life. In thiswork, we aim to learn a space of diverse and high-reward policies on any givenenvironment. To this end, we introduce a generative model of policies, whichmaps a low-dimensional latent space to an agent policy space. Our methodenables learning an entire population of agent policies, without requiring theuse of separate policy parameters. Just as real world populations can adapt andevolve via natural selection, our method is able to adapt to changes in ourenvironment solely by selecting for policies in latent space. We test ourgenerative model's capabilities in a variety of environments, including anopen-ended grid-world and a two-player soccer environment. Code,visualizations, and additional experiments can be found athttps://kennyderek.github.io/adap/.
Empirical investigations on evolution strategies to self-adapt the mutation and crossover parameters of differential evolution algorithm

Differential evolution (DE) is a simple and robust evolutionary algorithm. Incorporation of parameter control mechanisms to DE is one thriving research area to improve its performance. Evolving the...
Exploring Reliability of Gold Labels for Emotion Detection in Twitter

Emotion detection from social media posts has attracted noticeable attention from natural language processing (NLP) community in recent years.The ways for obtaining gold labels for training and testing of the systems for automatic emotion detection differ significantly from one study to another, and pose the question of reliability of gold labels and obtained classification results.This study systematically explores several ways for obtaining gold labels for Ekman's emotion model on Twitter data and the influence of the chosen strategy on the manual classification results.
Pyrite zonation and source of gold in the Pangjiahe orogenic gold deposit, West Qinling Orogen, central China

The Pangjiahe deposit is an orogenic gold deposit located on the northwestern margin of the Fengtai Basin and has proven reserves of 38 t Au at an average grade of 6.3 g/t. Phyllite is widely distributed in the mining area with Triassic granite porphyry and diabase dykes intruded in faults crosscutting it. Gold mineralization is mainly hosted in phyllite rocks. The granite porphyry present in the deposit is locally mineralized when it shares the same space with ore-controlling faults. Pyrite always displays zoning textures: Py0 and Py1 are present in the core; rim Py2 replaces and/or overgrows Py0 and Py1; and Py3 comprises the outermost rim. Previously determined in situ δ34S values indicate that Py0, Py1, and Py2 and Py3 are diagenetic, magmatic hydrothermal, and hydrothermal ore stage in origin, respectively. Electron microprobe analysis (EMPA) mapping of the zoned pyrite (especially Py2) shows a negative correlation between sulfur and arsenic, indicating the substitution of sulfur by As1-. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) mapping and spot analysis of Py2 and Py3 reveal two Au and As relationships. In the mineralized phyllite and granite porphyry, Au has strong positive correlations with As, Sb, Cu, and Ag, similar to other arsenian pyrites in hydrothermal ore deposits. However, in altered samples, Au and As display decoupled geochemical behavior, especially in Py2, which has the same levels of As, Sb, Cu, and Ag but 2–5 orders of magnitude lower Au. We think that the ore fluid reacted with altered samples located distal to the ore-controlling fault (distal to the ore fluid center), and the fluid may not have been sufficiently charged with those elements, especially Au. Because As, Sb, Cu, and Ag could maintain at the same level in the ore fluid after precipitation of pyrite enriched in those elements, but Au was sharply depleted. This was also noted in a published fluid inclusion study in Carlin-type gold deposits in Guizhou Province, which has similar zoned pyrite texture. Based on the similar δ34S values (8‰ and 10‰) and trace element enrichments (Au, As, Sb, Cu, and Ag) between hydrothermal ore-stage pyrite and the Devonian seafloor exhalation sequence in the Fengtai Basin, the source of the gold in the Pangjiahe deposit should be attributed to metamorphism of the Devonian seafloor exhalation sequence during the Triassic orogeny.
The Robot CRS 255

The robot A255 by CRS Robotics is a smaller industrial robot than the A465 but with only five degrees of freedom. It owns also a special kinematic arrangement which makes it an interesting case of study.
Implicit Task-Driven Probability Discrepancy Measure for Unsupervised Domain Adaptation.

Probability discrepancy measure is a fundamental construct for numerous machine learning models such as weakly supervised learning and generative modeling. However, most measures overlook the fact that the distributions are not the end-product of learning, but are the input of a downstream predictor. Therefore, it is important to warp the probability discrepancy measure towards the end tasks, and towards this goal, we propose a new bi-level optimization based approach so that the two distributions are compared not uniformly against the entire hypothesis space, but only with respect to the optimal predictor for the downstream end task. When applied to margin disparity discrepancy and contrastive domain discrepancy, our method significantly improves the performance in unsupervised domain adaptation, and enjoys a much more principled training process.
Pedagogical Skill for Affordable Teaching in Vocational High School

This article looks at teacher's nature and quality, in particular at teacher in professional training. It also explains the idea of accessibility to the educational content and the necessity of its application. It also performs the chalenges in front of the teacher in a vocational school and his responsibility to form durable and multidirectional knowledge and skills, which can make the student a flexible, adaptive and creative citizen of the world, a student with sensibility to other people's and world's problems.
Enhancing Cyber Defense Preparation Through Interdisciplinary Collaboration, Training, and Incident Response

To enhance the capabilities of a cyber defense collaborative, a psychometric analysis team was embedded in a collaborative incident response team. Collaborative incident response community members included the State of Colorado, the Colorado National Guard, Regis University, private companies, and others. The collaborative training developed when National Guard leadership saw the Rocky Mountain Collegiate Cyber Defense Competition held at Regis, and planning began around the potential of collaborative training. The case presented shows the progressive efforts that allowed this to move from enhancing training exercises to being embedded during live cyber defense operations. Some outcomes of the psychometric evaluation are presented here as an embedded quantitative study within the framing case analysis. The case analysis is then used to formulate a generalized model designed to support opportunities for a range of interdisciplinary collaboration in support of technical endeavors with operations security requirements as exemplified by cyber defense. The resulting model provides a framework for expanding research to other disciplines.
Varieties of Plain Language

Many organizations seek or need to produce documents that are written plainly.In the United States, the "Plain Writing Act of 2010" requires that many federal agencies' documents for the public are written in plain English.In particular, the government's Plain Language Action and Information Network ("PLAIN") recommends that writers use short sentences and everyday words, as does the Securities and Exchange Commission's "Plain English Rule."Since the 1970s, American plain language advocates have moved away from readability measures and favored usability testing and document design considerations.But in this paper we use quantitative measures of sentence length and word difficulty that (1) reveal stylistic variation among PLAIN's exemplars of plain writing, and (2) help us position PLAIN's exemplars relative to documents written in other kinds of accessible English (e.g., The New York Times, Voice of America Special English, and Wikipedia) and one academic document likely to be perceived as difficult.Uncombined measures for sentences and vocabulary-left separate, unlike in traditional readability formulas-can complement usability testing and document design considerations, and advance knowledge about different types of plainer English.
Interpretive Blindness

We model here an epistemic bias we call \textit{interpretive blindness} (IB).IB is a special problem for learning from testimony, in which one acquiresinformation only from text or conversation. We show that IB follows from aco-dependence between background beliefs and interpretation in a Bayesiansetting and the nature of contemporary testimony. We argue that a particularcharacteristic contemporary testimony, \textit{argumentative completeness}, canpreclude learning in hierarchical Bayesian settings, even in the presence ofconstraints that are designed to promote good epistemic practices.
Implementation of the K-Means Clustering Algorithm for Hope Family Program Participants Using Android-Based Retrofit Library

Program is a conditional non-cash social assistance program for Beneficiary Families who are designated as beneficiary families. By using K-Means which is a clustering algorithm to be used to collect data into data groups from the cluster center point (centroid) closest to the data. The purpose of this study is to apply k-means for the Family Hope Program clustering by using an android-based retrofit library so that it will accumulate the value of category weights and produce good decisions. It is hoped that this application is always up to date, interactive, and can be a reference not only for facilitators in the family of hope program but also for all applications and all circles as information technology development.
The Value of Information When Deciding What to Learn

All sequential decision-making agents explore so as to acquire knowledge about a particular target. It is often the responsibility of the agent designer to construct this target which, in rich and complex environments, constitutes a onerous burden; without full knowledge of the environment itself, a designer may forge a sub-optimal learning target that poorly balances the amount of information an agent must acquire to identify the target against the target's associated performance shortfall. While recent work has developed a connection between learning targets and rate-distortion theory to address this challenge and empower agents that decide what to learn in an automated fashion, the proposed algorithm does not optimally tackle the equally important challenge of efficient information acquisition. In this work, building upon the seminal design principle of information-directed sampling (Russo & Van Roy, 2014), we address this shortcoming directly to couple optimal information acquisition with the optimal design of learning targets. Along the way, we offer new insights into learning targets from the literature on rate-distortion theory before turning to empirical results that confirm the value of information when deciding what to learn.
PEMANFAATAN SISTEM DATA POKOK PENDIDIKAN (DAPODIK) DALAM PENGELOLAAN SEKOLAH DASAR

This study aims to explore the use of the basic education data system (Dapodik) at El Fitra Elementary School that supports school management. The research method used is qualitative, Sources of data obtained from interviews with respondents, namely the principal and the operator of SD El Fitra, through observation and documentation. The results of the study indicate that the Dapodik system that has been used by SD El Fitra is the curriculum menu, students, educators and education personnel (PTK), and infrastructure. The results showed that data that had been recorded in the center was not followed by optimizing the use of data for school management. The Basic Education Data System (Dapodik) provides data that is indispensable in school management. The understanding of school managers on the use of dapodik for school management must be fostered in order to achieve effective and efficient school management.
OSA Patient Monitoring Based on the Beidou System

This paper presents an OSA patient interactive monitoring system based on the Beidou system. This system allows OSA patients to get timely rescue when they become sleepy outside. Because the Beidou position marker has an interactive function, it can reduce the anxiety of the patient while waiting for the rescue. At the same time, if a friend helps the OSA patients to call the doctor, the friend can also report the patient's condition in time. This system uses the popular IoT framework. At the bottom is the data acquisition layer, which uses wearable sensors to collect vital signs from patients, with a focus on ECG and SpO2 signals. The middle layer is the network layer that transmits the collected physiological signals to the Beidou indicator using the Bluetooth Low Energy (BLE) protocol. The top layer is the application layer, and the application layer uses the mature rescue interactive platform of Beidou. The Beidou system was developed by China itself, the main coverage of the satellite is in Asia, and is equipped with a high-density ground-based augmentation system. Therefore, the Beidou model improves the positioning accuracy and is equipped with a special communication satellite, which increases the short message interaction function. Therefore, patients can report disease progression in time while waiting for a rescue. After our simulation test, the effectiveness of the OSA patient rescue monitoring system based on the Beidou system and the positioning accuracy of OSA patients have been greatly improved. Especially when OSA patients work outdoors, the cell phone base station signal coverage is relatively weak. The satellite signal is well-covered, plus the SMS function of the Beidou indicator. Therefore, the system can be used to provide timely patient progress and provide data support for the medical rescue team to provide a more accurate rescue plan. After a comparative trial, the rescue rate of OSA patients using the detection device of this system was increased by 15 percentage points compared with the rescue rate using only GPS satellite phones.
USO DA FERRAMENTA PRESSURE ULCER SCALE FOR HEALING PARA AVALIAR A CICATRIZAÇÃO DE LESÕES POR PRESSÃO

Due to the incidence of high pressure injuries, resulting in high financial costs, both for the individual and for the health institution, in addition to social, emotional and psychological consequences for two patients. Considering these factors, it is of fundamental importance that new works in the area continue to be developed, in order to improve the resources of existing technologies, so as not to treat vacations, as well as to make them cheaper and more accessible, especially for the less fortunate. less developed classes and societies with less financial contribution (ESPIRITO SANTO et al., 2013a). The objective was to increase the knowledge of two academics about the PUSH scale, also seeking a vision that encourages the search for the implementation of the PUSH scale, showing its advantages and disadvantages, taking into account the amount of daily material expenses with pressure injuries in addition to prejudice to the quality of life of two patients. Monitoring and documenting the evolution of the treatment of skin lesions is a fundamental activity so that it is possible to effectively measure two procedures, products and medicines used, in order to minimize costs and minimize the healing time of two yeasts. This study addresses the experiences of nursing students and preceptors during the Supervised Stage II, developed in the 9th phase of the Nursing Course at the University of the West of Santa Catarina (UNOESC). These activities will take place no later than May 2021. In the current activity, an assessment is made of the number of pressure injuries in a given environment in a hospital in the far west of Santa Catarina. The stages of the study will be constituted mainly, not being the conclusion of the method of assessment of injuries described above. In addition to this brief research on the PUSH scale, it was possible to reiterate some positive topics related to its application and how it works, that is, how I found such current needs of the person selected in the status field. However, its implementation in hospital units intends to move two work processes, opening a discussion on routine care, ethical concepts and training of everyone involved in the process.