Reviewerly/exHarmony huggingface dataset:
Pemetaan Kebisingan Menggunakan Software Golden Surfer 11 di Kawasan Universitas PGRI Palembang

Research about noise mapping in University of PGRI Palembang area using Surfer 11 has been done on march 2021. Purposes of this research are to determine the noise level and mapping noise level using software golden surfer 11. Method purpossive sampling and metod of frequency distribution are used on this research. So that the noise level L eq obtained. The results obtained indicate that at each measurement point the noise level has passed the quality standard limit except when the measurement is carried out in the morning. Parking zone and the main campus entrance are exceed the limits of noise levels and shown by contour maps.
Image Feature Extraction

In the last chapter we discussed the acquisition and processing of images. We learned that images are simply large arrays of pixel values but for robotic applications images have too much data and not enough information. We need to be able to answer pithy questions such as what is the pose of the object? What type of object is it? How fast is it moving? How fast am I moving? And so on. The answers to such questions are measurements obtained from the image and which we call image features. Features are the gist of the scene and the raw material that we need for robot control.
ART THERAPY IN SEARCH FOR LIFE MEANINGS

An art therapy exercise program is posed in the article. The author has proven the effectiveness of the art therapy program for a person's search for life meanings. Study participants are 59 women aged 18 to 20 years (M=18,63; Std.=0,72), who noticed various manifestations of the state of meaning loss (apathy, emptiness, boredom, etc.). Standardized psychological diagnostic techniques were used in the research. The first psychological diagnostic technique was the test of life-meaning orientations by D. Crumbot and L. Makholik in adaptation of D.A. Leont’ev). This test allows to identify the life guidelines of a person. The second psychological diagnostic technique was the methodology "Scale of psychological well-being" by K. Riff in adaptation of L.V. Zhukovskaya, E.G. Troshikhina. This methodology was used to measure the level of psychological well-being, which was a subjective indicator of the effectiveness of the art therapy program. The empirical base of the study was made up of two groups of respondents. The first group was experimental (E-group, N=25; M=18,50; Std.=0,60), the second one was a control group (С-group, N=22; M=18,76; Std.=0,72). The author used descriptive statistics, difference reliability analysis method (Mann-Whitney U test, Wilcoxon test), correlation analysis by the r-Spearman method. The effectiveness of the developed art therapy program was confirmed for a person's search for life meanings by the results of an empirical research. The indicators of life-meaning orientations and psychological well-being increased, the strength and intensity between both indicators increased because of the strengthening of the creative activity of the person, which contributed to the deep awareness of the participants in the process of their life experience, significant connections with other people and the world in general, fixation on creative images and immersion in personal meanings that filled these creative images.
Asymmetric two-stream network for screen content image quality assessment based on region features

With the latest popularization of remote desktop software and online work, screen content images (SCIs) are increasingly being contacted by people. Many image quality assessment (IQA) methods based on deep learning have been proposed for SCIs. However, most IQA methods for SCIs pay less attention to regional characteristics. An asymmetric two-stream network based on region features is proposed for SCI objective quality assessment, in which features are derived from a channel separation feature extraction (CSFE) sub-network and a spatial analysis feature extraction (SAFE) sub-network. In the CSFE sub-network, three channel separation (CS) modules are utilized to strengthen the ability for capturing deepthwise features in the pictorial regions. In the SAFE sub-network, two spatial analysis (SA) module are applied to focus on the structural information in the spatial domain for the textual regions. Two asymmetric sub-networks can efficiently extract the corresponding region features by separately considering the pictorial and textual regions of SCIs. In addition, an adaptive global weighting strategy is introduced to estimate the quality for SCIs. The experimental results on the screen image quality assessment database show that the proposed model is superior to the other state-of-the-art SCI quality assessment methods.
Online Informal Learning of English Activities to Improve Students’ English Communication Skills

This study aims to learn about students' experiences developing their speaking skills using Online Informal Learning of English (OILE) activities. The researcher gathered data for this narrative study by interviewing and observing three English education students at a State University in Central Java. The data were then evaluated qualitatively. The results indicated that students learned several aspects of speaking and communicating in English using Youtube video content, including pronunciation, intonation, and expressiveness. Additionally, the students used a variety of social media and chat platforms to engage with their international peers in English. Additionally, students favoured this informal learning mechanism because they recognized the efficacy of these online everyday learning activities in pleasantly achieving meaningful learning goals. Additionally, OILE activities aided students' speaking performance during informal learning activities.
A expressão de singularidades em gêneros narrativos análise da classificação de fanfictions

The objective was to understand how fanfiction narrative genres are classified in repositories, describing the users perceptions and motivations to accomplishthe indexing. The research is descriptive and exploratory, with the Intensive Direct Observation method in virtual groups of fans who write and consume fanfictions;the data supported a qualitative analysis of the fanfictions narrative genres used in theirindexingin digital repositories. The analysis demonstrated that many of narrative genres used in the repositories express concern with the representation of gender, sexual and physical aspects. Furthermore, natural language words, neologisms and other foreignwords are re-semantized to represent narrative genres. It was concluded that narrative genres are used to classify the stories, to express singularities andtogive representation to demands of marginalized groups of the publishing market.
Multi-objective Feature Selection with a Sparsity-based Objective Function and Gradient Local Search for Multi-label Classification

In classification, feature selection (FS) removes irrelevant and redundant features to improve the classification performance. Most of the existing FS approaches are designed specifically for single-label classification, wherein each instance is associated to a single class label. However, many real-world problems have more than one class label for each instance, also known as multi-label classification (MLC). Label-to-label interactions in MLC information presents a new challenge for FS, whereas single-label FS methods typically only consider feature-to-feature (redundancy) and feature-to-label (relevancy) information. Sparsity-based FS is an efficient and effective method for MLC which has demonstrated its ability in considering label-to-label interactions. However, existing sparsity-based approaches can be trapped at local optima due to their gradient-based search. In addition, they cannot consider different trade-off between the two objectives of FS: to minimise the number of features and to maximise the classification performance. Evolutionary multi-objective optimisation (EMO) can address the above issues, but EMO has not been applied to achieve sparsity-based FS for MLC. This paper proposes a novel sparsity-based representation, objective function, and local search method to achieve sparsity-based EMO FS for MLC. The experimental results indicate improved efficiency and effectiveness in the MLC performance in comparison to existing state-of-the-art multi-label feature selection methods.
I Wish I Would Have Loved This One, But I Didn’t – A Multilingual Dataset for Counterfactual Detection in Product Review

Counterfactual statements describe events that did not or cannot take place.We consider the problem of counterfactual detection (CFD) in product reviews.For this purpose, we annotate a multilingual CFD dataset from Amazon product reviews covering counterfactual statements written in English, German, and Japanese languages.The dataset is unique as it contains counterfactuals in multiple languages, covers a new application area of ecommerce reviews, and provides high quality professional annotations.We train CFD models using different text representation methods and classifiers.We find that these models are robust against the selectional biases introduced due to cue phrase-based sentence selection.Moreover, our CFD dataset is compatible with prior datasets and can be merged to learn accurate CFD models.Applying machine translation on English counterfactual examples to create multilingual data performs poorly, demonstrating the language-specificity of this problem, which has been ignored so far.
How Technology Helps Protect Global Health and Fight the COVID-19 Pandemic

Whether it is mindlessly scrolling through social media, or even using voice assistant devices to order products online, there is no doubt that technology has fundamentally changed our lives. As COVID-19 hospitalizations and deaths climb, new and innovative digital technologies are being harnessed to support the global response to COVID-19 (Whitelaw, Mamas, and Van Spall, 2020). With no effective antiviral treatment in sight and vaccines only just becoming available, global efforts have been focused on containment and prevention strategies. The countries with the most effective handling of the virus have successfully implemented digital technologies to aid in contact tracing, patient diagnosis through artificial intelligence, and telemedicine for remote treatment options.
Nonlinear Feedforward enabling Nonlinear Quadrature Measurement toward Fault-tolerant Universal Quantum Computation

We demonstrate nonlinear feedforward combined with non-Gaussian ancillae localized in time, which realizes nonlinear quadrature measurement. Our technology in principle enables fault-tolerant universal quantum computation by improving prepared ancillae.
Generative Sequence Labelling

With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature, including classification, sequence labelling, and sequence-to-sequence problems. Topics covered include statistical machine learning and deep learning models, text classification and structured prediction models, generative and discriminative models, supervised and unsupervised learning with latent variables, neural networks, and transition-based methods. Rich connections are drawn between concepts throughout the book, equipping students with the tools needed to establish a deep understanding of NLP solutions, adapt existing models, and confidently develop innovative models of their own. Featuring a host of examples, intuition, and end of chapter exercises, plus sample code available as an online resource, this textbook is an invaluable tool for the upper undergraduate and graduate student.
Materializing the Agency of Design in Innovation Practices

Abstract This article critically reviews how we think about design in technology and service innovation. Human-centered design has emerged in this science-driven field as a way to include the interests of humans and their needs in production processes. As such, design has a considerable effect on the development of new technologies and services. Making visible the agency of design in these practices thus is of immense importance. A gap remains in the ability of current concepts of design to visualize and conceptualize design agency. Therefore, drawing on concepts of materiality in design and practice, this article proposes a framework that makes design agency visible.
Assessment of Some Trace Elements Levels and Their Relation to Land Uses by Multivariate Analysis and GIS - Burg El Arab – Egypt

In the present study, the environmental quality evaluation of Burg El Arab district of Alex Governorate has been done by assessment of some trace elements levels, such as Ag, Al, B, Ba, Ca, Cd, Co, Cr, Cu, Fe, Mg, Mn, Mo, Ni, Pb, Si, Sr, V and Zn in soils and plants.Some trace metal risk indices, such as the Top Enrichment Factor (TEF), the Enrichment Factor (EF), geoaccumulation Index (Igeo), Contamination Factor (CF), and Soil Pollution Index (SPI) have been estimated.The results reveal that the mean values of TEF for studied metals are more than 1, except for the Al, B and Mn.The maximum values of the EF were observed with Cd and Pb, respectively, compared with the other associated elements.The mean values of Igeo for elements remained in class "0", except for the Cd.So, the studied area is considered within the uncontaminated category.The mean of all CF values was less than 1, except that for Cd that was 11.74.So, CF for Cd indicated very high degree of contamination.The mean value of SPI for some elements concentrations was less than 1, except that for Sr was 1.52.Multivariate analysis (principal component analysis method) and GIS techniques were applied to identify the sources of some elements and to analyze the relationships between elements contents and soil properties.Principal component analysis (PCA) classified the elements into six groups, in terms of the human influence (different land uses) and calcareous sediments (lithogenic origins) and interaction between them.The concentrations of Pb in different plant species were investigated according to the bioaccumulation (BAC).The highest BAC (7.95) occurred in Maize and the lowest one (0.04) occurred in Pepper.
Spatial Modeling of Phosphogypsum Dusting of Disposal Site Using the Example of the Balakovo Branch of "Apatit" JSC

The simulation of dusting of phosphogypsum dump of Balakovsky branch of JSC "Apatit" of "PhosAgro" Group of Companies was conducted. On the basis of the analysis of the meteorological data for the period 2006–2019, the information on a projective covering by vegetation for the period 2006–2019, a relief and a soil map modeling of relative concentration for the particles the size less than 0,01 mm; 0,01–0,03 mm; 0,03–0,05 mm; 0,05–0,1 mm; 0,1–1 mm and 1–8 mm was done. It was found as a result of the joint analysis of the constructed maps and field data, that the map of the weighted sum of relative concentrations of the analyzed particles well enough reflects spatial variability of the maintenance in soil La and Ce, prevailing components among the analyzed rare-earth elements (correlation coefficient 0.74 and 0.68 accordingly). The modeling results can be used to assess the impact of phosphogypsum dumps on the adjacent territory and its soil cover.
Real-time optimization of quantum state engineering protocol

We applied an optimization algorithm to dynamically engineer qudit states through a Quantum Walk based protocol. Our approach allows us to consider experimental imperfections and to adapt the algorithm in presence of external perturbations.
Do UD Trees Match Mention Spans in Coreference Annotations?

One can find dozens of data resources for various languages in which coreference -a relation between two or more expressions that refer to the same real-world entity -is manually annotated.One could also assume that such expressions usually constitute syntactically meaningful units; however, mention spans have been annotated simply by delimiting token intervals in most coreference projects, i.e., independently of any syntactic representation.We argue that it could be advantageous to make syntactic and coreference annotations convergent in the long term.We present a pilot empirical study focused on matches and mismatches between handannotated linear mention spans and automatically parsed syntactic trees that follow Universal Dependencies conventions.The study covers 9 datasets for 8 different languages.
A SYSTEMATIC REVIEW OF CAD SYSTEM BASED APPROACH IN DIAGNOSING BREAST CANCER AND ANALYZE EFFECTIVENESS OF MACHINE LEARNING AND DEEP LEARNING ALGORITHMS IN EARLY DETECTION

This study intends to throw some light on the different treatment gateways of breast cancer.As we know that women are worst affected by this life threatening disease around the globe, everyone should be aware of the fact that this disease can be tackled if it is detected at the initial stage.In India, the most number of women are affected by this fatal carcinoma and that results in a huge death rate.MRI, Biopsy, USG, Mammography, Histopathological images and many other diagnostic tests can confirm the presence of breast cancer in women.This paper will focus on the prediction of the test samples to be malignant or not by studying the ways of performing machine learning based computer aided systems.By reviewing many important and promising papers in this area, it has been found that there is an established system of detection of carcinoma that is known as Computer Aided Detection.This system consists of the different stages as in image pre-processing, segmentation of images, extraction of relevant features and image classification.We also found from the review that the
The Impact of VR Graphical User Interface on Oculus Touch Controller and Oculus Rift

It is undeniably true that Virtual Reality (VR) has continuously been developed since 1800s and still have been produced till today. However, very few studies have attempted to study on the design of Virtual Reality Graphical User Interface (VR-GUI) that effectively empowers users to interact and immerse in a simulated world, via hardware and software with ease. Therefore, the aims of this research are to compare four different types of VR GUI Controller designs including (2D, 2D animation, 3D, and 3D animation) and to determine UI response time of the Oculus Touch Controller and compare the results with UI response time of Oculus Rift to determine what VR GUI is appropriate for which ages. 168 participants were purposely selected, aged from 12 to 17, 18 to 33, and 34 to 45. The experiment results showed that VR GUI had a significant impact on UI response time resulted from different types of VR GUI controllers. Last but not least, analysis of VR GUI controller user data had suggested that VR GUI developers should design appropriate VR GUI controllers that match all age groups in order for them to experience a fully immersive, perceptually real environment as quickly and efficiently as possible.
Tendency of Test Item of the Korean History Competence Test and the Effect on the Perception of Buddhist History - Focusing on the Analysis of Previous Test Item and Surveys -

초록·키워드 목차 오류제보하기 This paper analyzed the impact of the Korean History Competence Test(KHCT) on applicants" perceptions of Buddhist history and Buddhist culture, and suggested a direction to improve the test item on the KHCT. For this study, test items of the KHCT conducted from 2011 to 2020 divided into a person related to Buddhism, Buddhist cultural heritage, and Buddhist-related events. In addition, a survey was conducted to determine whether the KHCT provide an opportunity to know facts related to Buddhist history and Buddhist culture. Through these results, the effectiveness of the KHCT and the direction of improvement of the test item were proposed. It was confirmed that the KHCT provides an opportunity to convey and understand knowledge related to Korean Buddhist history because it utilizes various historical facts, materials, and data. Since this is the fundamental purpose of conducting the KHCT, it is judged that the KHCT is exerting more effects than expected. However, it should be noted that there is a high tendency to ask schematic and typical test items. This is because it promotes the tendency to simply memorize historical facts rather than understanding them. Therefore, more diverse data should be presented and specific descriptions should be made to encourage candidates to understand the Buddhism history and culture. In addition, it is necessary to extract exemplary test items and continue to develop new types of questions. Increasing the percentage of questions appropriate to the evaluation standard is also a way to improve the reliability and quality of the KHCT. #한국사능력검정시험 #역사 인식 #불교사 #불교문화 #불교인물 #문항 개선 #Korean History Competence Test #History of Buddhism #Culture of Buddhism #Figures of Buddhism #Better Item Development 1. 序言2. 한국사능력검정시험의 불교사 관련 문항 분석3. 한국사능력검정시험 불교사 관련 문항 개선 제안4. 結語참고문헌
Multi-step Prediction for Learning Invariant Representations in Reinforcement Learning

In this paper, we focus on how to achieve task-relevant feature representations in reinforcement learning from image observations without relying either on domain knowledge or pixel-reconstruction. Although the existing algorithms based on reconstruction and contrastive learning have achieved excellent success, the sample efficiency and robustness of the algorithm are limited due to task-irrelevant information. In this paper, we utilize bisimulation metrics to construct an invariant representation learning method and extract task-relevant information. The research shows that the multi-step prediction environment model can retain longer-term state-transition information. In addition, we propose a multi-step prediction method to collect cumulative loss and update the extractor for representing learning, thereby improving the relevance of the extracted information of the task. Experiments on tasks with or without distractors show that the proposed method achieves better results.