Reviewerly/exHarmony huggingface dataset:
Titles of editions: Between advertising and pragmatics

The title, as one of the most important elements of any publication, has a dual nature. The aim of the article is to evaluate the correlation of advertising and pragmatic functions in the titles of modern mass literature publications. The study was conducted on the basis of an experiment. Thirty-four titles of fiction publications were the material for it; these are books by the Eksmo Publishing House, published in the first half of February 2022. Respondents were asked to choose no more than five titles of books that they would like to read. After that, they had to briefly describe what they thought each selected book was about. Eighty-five people took part in the survey. Successful book titles (chosen by more than 10% of respondents) and unsuccessful ones (chosen by fewer than 5% of respondents) were taken for further research. All of them were divided into three groups - depending on how accurately the respondents were able to determine the subject, genre or content of the book. The study confirmed the hypothesis that the title of the book should clearly indicate to the potential reader what kind of work awaits them. In some cases, lexical “marking” of a genre orientation is enough for this. According to these signs, the titles Soul Catchers (“souls”: fantasy, mysticism), Looking at the Sea (“sea”: romance), People Are Stronger Than Walls (heroic pathos of comparison) and even Show of Family Secrets (“secrets”: detective, thriller) were correctly interpreted. On the contrary, the title Thrice Risen was associated with mysticism, philosophy, although the genre of the work turned out to be different. The pragmatic component can also be provided by a capacious reflection of the subject matter of the work. On this basis, the problems of books with the titles When Mom is You (“Mom”: the theme of motherhood and relationships with children) and partly Chronicles of the Asylum (“Asylum”: the theme of borderline states of the psyche) were correctly “read”. But the title A Career Requires Sacrifice can be considered unfortunate, since it evoked clear (but false) associations: the difficulty of balancing a career and personal or family life. The book title can also be associated with the text by its style. Thus, the title Looking at the Sea seemed “soft” and “lyrical” to the respondents, which corresponds to the idea of a sentimental novel. In the course of the experiment, the most serious errors of publishers when approving the title were also revealed. One of them is the choice of a title similar to another well-known one (The Mentalist, The Ice Heart). Another common problem is the ambiguity of the title when it includes completely unknown words (The Pursuit of the Pankera) or using complex metaphors (Windows in the Clouds, Rapid Jelly). It is proved that a successful title should be informative and should clearly indicate the genre, thematic focus, problems and style of the work. It also should not contain excessive pathos, should not be stereotyped and should be original enough. The author declares no conflicts of interests.
A Comparative Study on Unsupervised Domain Adaptation Using Subspace Alignment

Unsupervised domain adaptation (DA) aims to build a classification model that performs well in the target domain by utilizing some data or information from a source domain that is different but associated with the target domain and has sufficient labeled instances. In this paper, a comparative study on unsupervised domain adaptation methods using subspace alignment was conducted. Two main algorithms are considered. One is the subspace alignment DA and the other is the subspace distribution alignment DA. They are based on dimension reduction using PCA (principal component analysis) and basis vector alignment of the subspace or distribution alignment of the subspace. In addition, a method for realizing domain adaptation through subspace alignment while utilizing supervised PCA for subspace derivation was proposed and compared with the previous two methods. In an image classification data analysis, it was confirmed that the subspace distribution alignment domain adaptation method showed superior results than the subspace alignment domain adaptation, and the proposed domain adaptation method utilizing a supervised PCA and subspace alignment showed the best performance in some situations.
Causality Change in Life Insurance Demand: Focusing on Financial Market and Insurance Provider Factors

This paper examined the Granger causality and changes in its intensity for Korea life insurance demand, focusing on the financial market and insurance provider factors. The significant causality ratio (SCR) in Kwon (2018), which can measure the intensity as well as the change in the significance of Granger causality, was applied. The intensity of the Granger causality of the three-year treasury bond rate, three-year AA corporate bond rate, KOSPI200 index, and number of planners was examined for each life insurance demand from January 1997 to May 2022. The change in the intensity of Granger causality for life insuance demand were visualized through the time plot of SCR by demand factor and life insurance type which are endowment, pure-endowment insurances and insurance against death, respectively. As a result, it was confirmed that the existence and intensity of Granger causality of each demand factor for each insurance type changed, and the pattern of change varies by factor and life insurance type. The factor with higher Granger causality than other periods in the global financial crisis is the interest rate and the Granger causality of the number of planners showed the opposite pattern. The Granger causality of the stock index for insurance against death was lower than that of other insurances.
The visual attentional pattern toward smoking area signs in legal and illegal cigarette smokers: Preliminary findings

Attentional patterns towards signs of smoking area might be different on individual levels. This would play a significant role in the decision-making process of illegal smoking behavior. In order to understand and effectively intervene the such behavior, this study aims to investigate the attentional pattern of the legal and illegal smokers toward the area signs (e.g. smoking area vs. no-smoking area) using a free viewing task and eye-tracking method. The participants were grouped into 25 legal smokers groups (LSG) and 15 illegal smokers groups (ISG) based on their usual smoking spots specified in the self-report questionnaire. During the free-viewing task where their visual attentional pattern was measured by an eye-tracking method, the participants were presented with eight pictorial stimuli with the area signs and the smoking-related cues. To examine the initial orientation process, the initial fixation latency, total dwell time, and dwell time by time blocks were analyzed for the smoking area signs. As a result, while LSG showed faster initial fixation toward the smoking area signs than no-smoking area signs, ISG did not. Also, LSG showed higher proportion of initial visual attention to smoking area signs. These findings suggest that the initial orienting attentional pattern of LSG toward the area signs might play a significant role in the legal smoking behavior.
Sequential relationship analysis of potential learning concepts: using structural equation modeling and HMM

As people use non-face-to-face learning frequently, interest in adaptive learning for efficient learning is increasing. In order for students to easily learn, it is necessary to set up a learning path that considers students' learning outcomes. However, as everyone recognizes, learning pathways are not created based on learning logs, but rather rely on the curriculum that experienced teachers have used. However, the answer to the question “Can today's students learn efficiently with the existing curriculum system?” is perhaps not certain. In addition to studies whose subjects were creating a learning path, this study uses a structural equation model, Hidden Markov Model (HMM) and inductive reasoning to create a hierarchical learning path between latent factors at a higher level. Using the mathematics learning data of company D in Korea, a learning path of concepts rather than a learning path of subdivided concepts was created. It was confirmed that the subdivided concepts showed reliable observation values for the upper concepts and that the subdivided concepts conveyed the contents whose concepts were conveyed with validity.
A Simulation Study on Robustness of Classification Model with Mislabeled Data

In order to increase the accuracy and performance of classification models, the quality of data must be guaranteed. There are various factors that affect the quality of these data, such as measurement accuracy, missing value, and sampling biases. This study focuses on the robustness of the classification model for mislabeled data. The reason we are interested in mislabeled data is that it significantly degrades the performance of the model more than other common measurement errors. In this study, the efficiency of various classification methods for data with mislabels is reviewed. Fisher's linear discriminant analysis model (LDA), quadratic discriminant analysis model (QDA), and logistic regression model were considered in the statistical model-based method, and SVM (support vector machine) and boosting are compared in the algorithm-based method. As a result of simulation study, it is found that the statistical model based approaches show better results in terms of robustness in the data assuming various situations of mislabels.
Sharing climate data through ICA&amp;D

&amp;lt;p&amp;gt;Historical climate data is fundamental for understanding local climate trends and extremes and evaluating the impact of climate change on agriculture, food security and water resources. In addition, the data is &amp;amp;#160;used for implementing adaptation measures for protecting lives and adapting socio-economic sectors to the changing climate conditions. While global climate trends can already be assessed with available data, regional data disparities result in blind-spots for climate change assessments&amp;amp;#8212;particularly for areas which are the most vulnerable.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;To contribute to filling this gap, the International Climate Assessment &amp;amp; Dataset (ICA&amp;amp;D) has been extended to the climate-vulnerable areas of the Caribbean, the Pacific and in 5 sub-regions in Africa. ICA&amp;amp;D provides an accessible, web-based system to collect, prepare, quality control, and analyze basic climatological data with daily resolution. The system was developed over 25 years ago by the Meteorological Service of the Netherlands (KNMI) as the backbone of the European WMO data-node of the Regional Climate Centre (https://www.ecad.eu/) and implemented in Southeast Asia by meteorological service of Indonesia (BMKG). Now, with support from the EU-funded ClimSA project, under which WMO is implementing a &amp;amp;#8364;5.5 million grant, ICA&amp;amp;D will be further extended and run by Regional Climate Centers assigned and supported by WMO.&amp;lt;/p&amp;gt; &amp;lt;p&amp;gt;WMO and KNMI collaborated in 2022 through CLIMSA project to expand ICA&amp;amp;D to two pilot regions, the Caribbean and West-Africa on https://caribbean.icad-wmo.org/ and http://west-africa.icad-wmo.org/. The collaboration has led to setting up new websites which are designed to be user friendly and highly cyber secure. The websites, one for each region, consist of information platforms, including a geographical map with the locations of the stations&amp;amp;#8217; datasets, and a feature to quickly plot timeseries from derived data and an e-learning module on the website&amp;amp;#8217;s functions. The data sharing policy ensures that access to raw observational data from National Meteorological and Hydrological Services (NMHS) remain restricted while allowing derived indices to be accessed by the public. Indices alone can monitor critical areas and impacts of climate change, such as the temperature of the warmest night of the year, the subsequent impact on health and &amp;amp;#160;induced excess of mortality.&amp;lt;/p&amp;gt;
Longitudinal assessment of tsunami knowledge in an Italian school.

Italy is at tsunami risk, a phenomenon characterized by low frequency of occurrence that can cause widespread and destructive impact on coastlines.The activities carried out by the INGV's Tsunami Alert Center (CAT-INGV), in concert with Italian Department of Civil Protection, include tsunami risk mitigation through: i) the study of tsunami risk perception, ii) the Tsunami Ready program, and iii) educational and dissemination activities with different methodologies.In this work we analyze the effectiveness and durability of learning about knowledge and tsunami risk with Lazzaro Spallanzani Scientific High School students, in Tivoli (Rome province).The assessment involved the administration of an online questionnaire composed of selected items from the tsunami risk perception survey carried out by CAT for the tsunami risk perception study (Cerase et al., 2019, Cugliari et al., 2022).The survey sample consists of 90 students identified by age group (16-19 y.o.) and study address (high school scientific address).The assessment was made administering the questionnaire in two stages, two months apart (March 2022 and May 2022) before and after a tsunami scientific lesson with the support of multimedia tools (photos, videos, animations and infographics).A third survey is planned for March 2023, respecting the statistical-methodological survey criteria.Data analysis shows an evident increase in tsunami risk knowledge. Student educational needs also emerge that can be used as leverage to structure targeted and effective interventions and increase young people's awareness of tsunami risk in other areas. There is also evidence that fieldwork, with the aid of multimedia and possibly interactive or assisted media, provides successful maintenance of attention and facilitates assimilation.&amp;#160;
Social &amp; Physics Based Data Driven Methods for Wildfire Prediction

&amp;lt;p&amp;gt;Twitter is increasingly being used as a real-time human-sensor network during natural disasters, detecting, tracking and documenting events. Current wildfire models currently largely omit social media data, representing a shortcoming in current models, as valuable and timely information is transmitted via this channel. By including this data as a real-time data source, we aim to help disaster managers make more informed, socially driven decisions, by detecting and monitoring online social media sentiment over the course of a wildfire event. This monitoring model is coupled to a real-time forecasting of wildfire dynamics.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Real-time forecasting of wildfire dynamics, which has attracted increasing attention recently in fire safety science, is extremely challenging due to the complexities of the physical models and the geographical features. Running physics-based simulations for large-scale wildfires can be computationally difficult. We propose a novel algorithm scheme, which combines reduced-order modelling (ROM), recurrent neural networks (RNN), data assimilation (DA) and error covariance tuning for real-time forecasting/monitoring of the burned area. An operating cellular automata (CA) simulator is used to compute a data-driven surrogate model for forecasting fire diffusions. A long-short-term-memory (LSTM) neural network is used to build sequence-to-sequence predictions following the simulation results projected/encoded in a reduced-order latent space.&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We implement machine learning in a wildfire prediction model, using social media and geophysical data sources with sentiment analysis to predict wildfire instances and characteristics with high accuracy. The geophysical data is satellite data provided by the Global Fire Atlas, and social data is provided by Twitter. In doing this, we perform our own data collection and analysis, comparing regional differences in online social sentiment expression.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The performance of the proposed algorithm has been tested in recent massive wildfire events in California.&amp;lt;/p&amp;gt;
A Phase-based Distributed Morphology Approach to Honorific (Non)suppletion in Korean

This paper provides a formal analysis of the suppletion of the verb root √EXIST. It argues that the suppletive exponents are subject to the Phase Impenetrability Condition (Chomsky 2000). The root √EXIST has two suppletive exponents: the honorific exponent /kyey/ and the negative exponent /eps/. We focus on the different morphophonological realizations, /iss-(u)-si/ and /kyey-si/, from seemingly the same morphological concatenation of √EXIST-HON- (and /eps-(u)-si/ and /an-kyey-si/ from NEG- √EXIST-HON-). By examining two √EXIST constructions in the affirmative and negative contexts, we propose that the two postsyntactic operations, i.e., feature copying and fusion, are engaged in the realization of √EXIST as /kyey/ and /eps/, with the overall analysis of contextual allomorphy couched in Choi & Harley (2019), Chung (2007, 2009), Kim & Chung (2015), and Kim & Chung (2017). We further argue that these two morphological operations take place under the interaction among the elements limited in the same phase/spell-out domain and in a stepwise fashion observing the Phase Impenetrability Condition.
A New Hybridization of Bilateral and Wavelet Filters for Noisy De-Noisy Images

In this work we propose, a hybrid noise reduction algorithm that is a combination of a spatial field binary filter and a hybrid wave field threshold function.These two methods are used to stop Gaussian noise.The hybrid filter is a nonlinear filter that deals with spatial averaging of non-uniform edges.We found it to be an effective technique for image reduction.Determining filter parameters for the mixed filter is important to avoid large differences in results, besides the issue of acceleration velocity.This hybrid model, binary filtering, and Wavelet Thresholding have tried standard images, such as normal eyes, MRI, Roya Face, Ultrasound, X-Ray, and Rawa.Different Gaussian noise was added with different standard deviations σ = 10, 20, 35, 40, and 50.The peak-to-noise ratio (PSNR) signal, MSE, VIF, IQI, and the proposed model MSE between pixels were used as quantitative measures of performance of the relative noise reduction algorithms and then were compared to the models.
Less Labels, More Modalities: A Self-Training Framework to Reuse Pretrained Networks

Remote sensing largely benefits from recent advances in deep learning. Beyond traditional color imagery, remote sensing data often features some extra bands (e.g. multi or hyperspectral imagery) or multiple sources, leading to the so-called multimodal scenario. While multimodal data can lead to better performances, it also requires to design specific deep networks, to collect specifically-annotated datasets, and to perform full retraining of the models. However, a major drawback of deep learning is the large number of annotations that is required to ensure such a training phase. Besides, for some given task and modality combination, annotated data might not be available, thus requiring a tedious labeling phase. In this paper, we show how to benefit from additional modalities without requiring additional labels. We propose a self-training framework that allows us to add a modality to a pretrained model in order to improve its performance. The main features of our framework are the generation of pseudo-labels that act as annotations on the new modality, but also the generation of a pseudo-modality corresponding to the labeled monomodal dataset. Experiments on the ISPRS Potsdam dataset, where we complement color orthophotography with a digital surface model, shows the relevance of our approach, especially for land cover classes that can take advantage of the two modalities.
DISCIPLINARY PARADIGM OF JOHN LOCKE

In this article, an attempt is made to describe John Locke's views on discipline. His autobiography and pedagogical views are briefly presented. In the context of John Locke's disciplinary paradigm, answers have been sought to the questions: When should child discipline begin? What rewards and punishments should the educator use in this process? What are the prizes given for? Is it necessary and in which cases to use corporal punishment? What is the role of parents in disciplining children?
The status quo and development trend of talent cultivation in academic journal studies in China: A case study of Master's and Doctoral theses

Background: This paper aims to investigate the situation of discipline construction in the field of academic publishing in China, including the transfer of talents to the academic publishing and its impact on the research and development of the academic publishing in the future. Methods: This research conducted a comparative analysis of the quantity of Master’s and Doctoral theses on academic journal studies in terms of relevant educational institutes, disciplines, high-frequency keywords, and research hotspots. Result: It was found that the number of Master’s and Doctoral theses on academic journal studies has increased since 2004 and remained steady during 2016–2021; among the 26 research institutes in which more than 10 Master’s and Doctoral theses in this field were published, information science, library science, communication, and journalism constituted the main disciplines of academic journal studies in China, and the theses published in these disciplines accounted for 34.4% of the total. The research hotspots included open access, editing and publishing, bibliometrics, etc. until 2015, and bibliometric analysis from 2016–2021. With bibliometric analysis, in the past ten and more years, 849 excellent graduates have been engaged in the academic journal studies. Some research institutes have made significant contributions to this field, cultivated a great number of talents, and introduced them to this field, promoting the development of the academic publishing. Conclusion: The number of Master’s and Doctoral theses focusing on academic journal studies has grown rapidly, leading to a picture of diversified prosperity in schools, majors, and fields of study. Universities and research institutes in China should establish a special research direction of academic journal studies to give impetus to the academic publishing industry.
Employee Management System for Nigerian Universities

The proposed Employee Management System is a web application that uses MYSQL Server as its database and acts as a bridge between users and the database, which houses all of the data. Its purpose is to enable the administrator to collect and save personnel information and records. The application also performs the leave management system task, which keeps track of all of the organization's employees' leave, allows for easy retrieval of information without the need for human intervention, and allows managers to manage their employees' leave and mark their leave dates. Furthermore, it will abolish the paper/file system, which will solve the current system's problems. Finally, it is revealed that this system would not only automate the entire procedure, but it will also save time for the administrator, which can be put to better use for his institute.