Reviewerly/exHarmony huggingface dataset:
Social Mental Disorder Detection Using Social Media Mining

As society becomes more technically advanced, we are more into the digital world. This has also brought numerous mental health issues for the individuals world-wide. Social networking platforms like Facebook and Twitter allows users to share their opinions and thoughts almost every day. This offer users a level of anonymity and provides users to be more uninhibited in their expressions. The objective of this paper is to propose depression detection and analysis of users based on Twitter data using sentiment analysis. Our study to date shows that such dataset that is readily available was too simplistic and most of the labelled depressive data had a word depression, which proves to be major obstacle to the development of this project, so we also aim to create our own a dataset that is designed precisely for depression identification based on tweets. We have evaluated the efficiency of this model using different approaches and the test accuracy was around 83% with test loss of 0.409 and also show that this proposed technique can significantly improve accuracy and classification error rate.
Exponential savings in agnostic active learning through abstention

We show that in pool-based active classification without assumptions on the underlying distribution, if the learner is given the power to abstain from some predictions by paying the price marginally smaller than the average loss 1/2 of a random guess, exponential savings in the number of label requests are possible whenever they are possible in the corresponding realizable problem. We extend this result to provide a necessary and sufficient condition for exponential savings in pool-based active classification under the model misspecification.
Usage of E-Resources among Library Users of Agricultural College and Research Institute, Coimbatore, Tamil Nadu: A Study

This paper attempts to explore the access and usage of electronic resources among the users of Agricultural College and Research Institute (ACRI), Coimbatore. The present study aims at focusing on the use of various electronic information resources, awareness of users, access and use of digital resources by the Library Users in ACRI, Coimbatore. A well-structured questionnaire was distributed among randomly selected 400 Library Users of ACRI, Coimbatore and the data was obtained from the 350 filled in questionnaires received. The data thus collected have been employed for the present study to provide detailed analysis and interpretation.
한국 임산부의 음주행동에 미치는 요인 분석

Objectives: Drinking alcohol during pregnancy can adversely affect the health of the pregnant woman and the fetus. Although the drinking alcohol rate of Korean women is gradually increasing, studies on the drinking alcohol rate of pregnant women during pregnancy are insufficient. In particular, few studies have been conducted on the variables that can predict drinking alcohol behavior during pregnancy. Methods: In 2017, we administered a self-report questionnaire for pregnant women less than 30 days before the due date of visiting a university hospital and a specialized hospital. We investigated the demographic and obstetric characteristics, as well as the drinking alcohol history of pregnant women. Results: The average age of 306 subjects was 33.4±4.2, and the average years of education was 15.3±1.8. In the CAGE, 17.0% responded ‘yes’ to more than two questions, and 37.6% responded if they had ever experienced a blackout or blackouts. The rate of drinking alcohol during pregnancy was 27.1%, including the period when respondents were unaware of being pregnant. And after respondents became aware of being pregnant, 7.2% experienced drinking alcohol. Significant variables explaining pregnant women who continue to drink alcohol even after knowing that they are pregnant were: the education of pregnant women (p<.001), family history of drinking alcohol (p<.05), and experiences of drinking alcohol before becoming pregnant (p<.05). Conclusion: The results of this study showed that a large number of pregnant women continued to drink alcohol during pregnancy. Thus, these results suggest that more non-drinking alcohol pregnant women should devise appropriate anti-drinking alcohol education programs for pregnant women who drink alcohol during pregnancy.
THE STUDENTS’ INTEREST IN THE SUBJECT OF WRITING IN PROFESSIONAL CONTEXTS

This paper presents the students’ interest and the most influential factors affecting the students’ interest in learning writing in professional context. The research problem in this research is: how is the students’ interest in the subject of writing in professional contexts at English Education Department UIN Alauddin Makassar. This research employed descriptive method which used quantitative and qualitative analysis to the data of the research. It was conducted in English Education Department of Tarbiyah and Teaching Science Faculty of UIN Alauddin Makassar. The subject of this research was all the students of English Department PBI 1-2 and PBI 3-4 in academic year 2017/2018. The total number of students were 85 students. The instruments used to collect the data were questionnaires, observation, and interview. The finding of this research showed that both group in PBI 1-2 and PBI 3-4 had medium level of interest in the subject of writing in professional contexts. The most influential factor affecting the students’ interest in the subject writing in professional contexts at the fourth semester of English Education Department were psychological factors including attention and intelligence, family, and university.
A Study of Availability and Recovery of URLs in Library and Information Science Scholarly Journals

The present study examines the availability and recovery of web references cited in scholarly journals selected based on their high impact factor published between 2008 and 2017. A PHP script was used to crawl the Uniform Resource Locators (URL) collected from the references. A total of 5720 articles were downloaded and 237418 references were extracted. A total of 33512 URLs were checked for their availability. Further the lexical features of URLs like file extension, path depth, character length and top-level domain was determined. The research findings indicated that out of 33512 web references, 20218 contained URLs, DOIs were found in 12799 references and 495 references contained arXiv or WOS identifier. It was found that 29760 URLs were accessible and the remaining 3752 URLs were missing. Most errors were due to HTTP 404 error code (Not found error). The study also tried to recover the inaccessible URLs through Time Travel. Almost 60.55% of inaccessible URLs were archived in various web archives. The findings of the study will be helpful to authors, publishers, and editorial staff to ensure that web references will be accessible in future.
UPAYA MENINGKATKAN MINAT SISWA TERHADAP LAYANAN INFORMASI BIMBINGAN DAN KONSELING MATERI PENGARUH PERGAULAN REMAJA MELALUI MEDIA AUDIO VISUAL PADA KELAS VII SMPN 1 STM HULU SEMESTER 1 TAHUN PELAJARAN 2017/2018

This research is a Classroom Action Research (PTK) with the research subjects of all students in class VII SMPN 1 STM Hulu, totaling 33 students. Data collection was carried out by several methods, including: observation, tests and documentation. The data validation used triangulation techniques. Analysis of the data used in this study using qualitative descriptive analysis, which is a research procedure that uses descriptive data in the form of written or spoken words. The research activities carried out are planning action, action, observation and reflection. The result of this research is the use of audiovisual media in BK services, the influence of socialization between class VII students of SMPN 1 STM Hulu, this is indicated by an increase in the ability of students' interest in learning per cycle where in the initial conditions only 12 students or 38.71%, cycle I there were 18 students or 58.06%, and in cycle II there were 28 students or 90.32%, this result was in accordance with the determined indicators, namely the good and very good categories which reached 85%. From the explanation above, it can be concluded that the use of audiovisual media in BK services on the influence of adolescent socialization is proven to be able to increase student interest in class VII SMPN 1 STM Hulu semester 1 of the 2017/2018 school year
Visual Transfer for Reinforcement Learning via Wasserstein Domain Confusion

We introduce Wasserstein Adversarial Proximal Policy Optimization (WAPPO), a novel algorithm for visual transfer in Reinforcement Learning that explicitly learns to align the distributions of extracted features between a source and target task. WAPPO approximates and minimizes the Wasserstein-1 distance between the distributions of features from source and target domains via a novel Wasserstein Confusion objective. WAPPO outperforms the prior state-of-the-art in visual transfer and successfully transfers policies across Visual Cartpole and both the easy and hard settings of of 16 OpenAI Procgen environments.
A Comparison Study Based on Artificial Neural Network for Assessing PV/T Solar Energy Production

This paper aims to employ and perform a comparison study of PV/T energy data prediction systems using different ANNs techniques. Several studies focus on photovoltaic thermal (PV/T) collectors started during the 1970s till now, which aims to increase the photovoltaic efficiency and produce a hybrid system for electricity and heat production. Locations that have good meteorological stations for recording solar radiations have been studied to predict solar energy based on using artificial neural networks (ANNs). Published studies in data sets for the years 2008–2017 were collected from individual countries and evaluated using suitable evaluation factors like MSE, MAPE, R2, RSME, MBE, and MPE. Furthermore, the best models used to predict the data of global solar radiation for locations with different latitudes and climates are discussed and analysed. This study is a guide for the reader and useful for engineers, and researchers interested in ANNs applied for solar PV/T systems data generation.
Frequency lists of word-level n-grams from the GOS 1.0 corpus 1.1

Frequency lists of word-level n-grams (or word sets) were extracted from the GOS 1.0 Corpus of Spoken Slovene (http://hdl.handle.net/11356/1040) using the LIST corpus extraction tool (http://hdl.handle.net/11356/1227). The lists contain all word-level 2-, 3-, 4- and 5-grams occurring in the corpus along with their absolute and relative frequencies, percentages, distribution across the text-types included in the corpus taxonomy, and five collocation measures: Dice, t-score, MI, MI3, logDice, andsimple LL.The n-grams were extracted from lower-case word forms, word forms, and morphosyntactic tags.For large lists, shortened versions with the first 150,000 lines were also prepared to facilitate further processing in spreadsheet analysis software.Compared to the previous version (http://hdl.handle.net/11356/1271), this one includes fixes of several typos and substitutes all instances of normalized forms with the more adequate term standardized forms (as used in the SSJ project).
Adjusted JPEG Quantization Tables in Support of GPS Maps

Image quality manipulating in JPEG is done by quantization tables. JPEG has two quantization tables – one table for the luminance information and one table for the chrominance information. These quantization tables have been designed in support of images with few sharp changes; however, typically most GPS image maps have many sharp changes and as a result, the images are not optimally compressed. The designers of the quantization tables have presumed that sharp changes in the colors will rarely occur. Therefore, they divide the values that represent sharp changes in the frequency space by large numbers and divide other values by smaller numbers. As a result, when there are sharp changes in an image, the proportional allocation for each kind of data in the compressed image is inappropriate and results in an inefficient compression. In this paper the standard quantization tables have been modified as to handle the different kinds of GPS image map data appropriately. Consequently, the experimental results show that images with sharp changes are compressed more efficiently when making use of the new quantization tables.
CNS Diseases Monitoring Using Wearable Devices. Monitoring Techniques based on Inertial Platforms for Patients Affected by Central Nervous System Diseases

Central nervous system (CNS) diseases are a broad category of neurological disorders causing the reduction of motor capabilities. CNS diseases represent one of the major public health challenges: to help with their management, it is important for both doctors and patients to understand how their disease changes over time. The last decade has seen an increasing diffusion of wireless inertial platforms for medical and rehabilitation purposes. This thesis presents simple, wearable-based methods and algorithms oriented towards the monitoring of patients affected by CNS disorders. Applications range from the detailed analysis of particular diseases performed in supervised environments (e.g. hospital and clinics), to a more general evaluation of the physical performances, potentially adaptable to any movement disorder. Several analysis algorithms as well as a dedicated wearable platform were specifically designed to provide medical staff with objective and simple-to-use monitoring tools.
LEVEL INCREASING OF TEACHERS` PROFESSIONAL TRAINING AS PEDAGOGICAL CONDITION OF PROVIDING GRADUATE PROFESSIONAL TRAINING FOR PENITENTIARY OFFICERS OF UKRAINE

The process of professional competence formation, which is the result of readiness for quasi-professional service of penitentiary officers, depends on many factors and conditions, where one of the main pedagogical conditions is the professionalism and innovativeness of the teacher's activity.The purpose of the article is identifying the directions of the level increasing of teachers` professional training, as one of the main pedagogical conditions for the professional competence formation of future penitentiary officers in the traditional training system.In the course of study the author identified the directions to the level increasing of teachers` professional training, as a special pedagogical condition for providing professional training for officers of the State Criminal and Executive Service of Ukraine: development of integrative courses of educational disciplines; development of pedagogical facilitation and professional self-improvement; development of teachers` academic mobility; development of teachers` special skills, modern communication and leadership skills, ability to apply certain preventative tools for emotional burnout.Keywords: pedagogical condition, professional competences formation, pedagogical facilitation, teachers` academic mobility, professional competence, professional development.
Study of Emotional Intelligence and Neuro-Fuzzy System

The chapter illustrates the study of recognition of human emotional states and shows the basic idea that how signal processing can apply for the same. The focus is on enhancing requirements of the current voice command and speaking technologies with consideration of emotional states, so that the interaction with computers and smart devices may become more human. The work is based on a comprehensive literature survey and referential study of Emotional Intelligence which illustrates its connection with emotional state recognition domain.
AI Enabled Face Mask Detector

Covid-19 pandemic is causing a global health crisis. To battle against the virus everyone should wear a face mask. The face mask detector in this study is developed with a machine learning algorithm called MobileNetV2 which is an image classification method. The steps to build the model are collecting the data, pre-processing, split the data, testing the model and implement the model.
The application of the Analytic Hierarchy Process method to the selection of dominant factors for adolescents who are prone to insecurity

Teens are often stressed, worried, and overly insecure as a result of their high expectations. The feelings that occur during adolescent development can create and increase feelings of insecurity in their lives, which has a negative impact. Adolescents with an excessive sense of insecurity can suffer from mental disruption, which can lead to serious mortality. Of course, these factors can have a negative impact on adolescents' mental health. Adolescents' minds and psyches can be disrupted by mental illness. The goal of this study is to identify the dominant factor among a number of factors that can lead to insecurity when using the Decision Support System (DSS) technique. Analytical Hierarchy Process is the DSS method used (AHP). The data used in this study was gathered through observations and interviews with adolescents using a random questionnaire. Six factors were derived from observations and interviews: social environmental factors (A1), family environmental factors (A2), social media factors (A3), insecure factors (A4), trauma factors (A5), and education and work factors (A6). The results of the AHP method show that the main factors for adolescents who are easily insecure are social environmental factors (first), social media factors (second), and family environmental factors (third) (third).
Spectral assessment of organic matter with different composition using reflectance spectroscopy&amp;#160;

&amp;lt;p&amp;gt;Soil surveys are critical for maintaining sustainable use of natural resources while minimizing harmful impacts to the ecosystem. A key soil attribute for many environmental parameters, such as CO2 budget, soil fertility and sustainability, is soil organic matter (SOM), and its sequestration. Soil spectroscopy is a popular method to assess SOM content rapidly in both field and laboratory domains. However, the SOM source composition differs from soil to soil and the use of spectral-based models for quantifying SOM may present limited accuracy when applying a generic approach for SOM assessment. We therefore examined the extent to which the generic approach can assess SOM contents of different origin using spectral-based models. We created an artificial big dataset composed of pure dune sand as a SOM-free background which was artificially mixed with increasing amounts of different organic matter (OM) sources obtained from commercial compost of different origins. Dune sand has high albedo and yields optimal conditions for SOM detection. This study combined two methods: partial least squares regression for the prediction of SOM content from reflectance values across the 400&amp;amp;#8211;2500 nm region, and soil spectral detection limit (SSDL) to judge the prediction accuracy. Spectral-based models to assess SOM content were evaluated with each OM source as well as with a merged dataset that contained all of the generated samples (generic approach). The latter was concluded to have limitations for assessing low amounts of SOM (&amp;lt;0.6%), even under controlled conditions. Moreover, some of the OM sources were more difficult to monitor than others; accordingly, caution is advised when different SOM sources are present in the examined population.&amp;lt;/p&amp;gt;
Discrete Cosine Transform-Domain Based Video Steganography using Multiple Object Tracking

In the current era, the need for transmission of confidential data is pivotal in all domains of technology. New methodologies are being proposed for this very purpose, each being developed on specific shortcomings of previously proposed methods. In this paper, one such method for embedding and communicating confidential information has been proposed which employs encryption and error correction algorithms to further improve the reliability and robustness of the system. First, the information is preprocessed by encrypting the text using RC4 algorithm. The encrypted text is processed using hamming codes (4,7) to improve its reliability. After the pre-processing stage, the video is processed to identify reliable motion regions using the MOT (Multiple Object Tracking) algorithm. The identified regions are used to embed the confidential text by calculating its DCT coefficients and manipulating its values to embed the information. The non-motion region is used to store the key used during the pre-processing stage. This completes the processes at the transmitter’s part. The inverse of the process-extraction and decoding is applied at the receiver’s side to retrieve the confidential piece of information being transferred. The proposed methodology further focusses on comparing the visual quality and hiding capacity achieved by adopting DCT and DWT algorithms, to determine the better of the two frequency domain techniques in steganographic applications.
MT-Telescope: An interactive platform for contrastive evaluation of MT systems

We present MT-TELESCOPE, a visualization platform designed to facilitate comparative analysis of the output quality of two Machine Translation (MT) systems.While automated MT evaluation metrics are commonly used to evaluate MT systems at a corpus-level, our platform supports fine-grained segment-level analysis and interactive visualisations that expose the fundamental differences in the performance of the compared systems.MT-TELESCOPE also supports dynamic corpus filtering to enable focused analysis on specific phenomena such as; translation of named entities, handling of terminology, and the impact of input segment length on translation quality.Furthermore, the platform provides a bootstrapped t-test for statistical significance as a means of evaluating the rigor of the resulting system ranking.MT-TELESCOPE is open source 1 , written in Python, and is built around a user friendly and dynamic web interface.Complementing other existing tools, our platform is designed to facilitate and promote the broader adoption of more rigorous analysis practices in the evaluation of MT quality.
항공서비스전공 학생들의 온라인 교육서비스품질이 학습몰입과 재 수강의도에 미치는 영향

Cabin attendants are important talents in the aviation industry, and many universities have established and trained aviation services majors in order to cultivate talents with professionalism and service minds. Therefore, in this study, an empirical study was conducted on the effect of online education service quality of students majoring in aviation service on learning immersion and re-taking. The result of this study was to present basic data that can be improved to improve the quality of online education services for students majoring in aviation service. The results of the study are as follows. First, it was found that the detailed factors of online education service quality had a positive (+) effect on the detailed factors of learning immersion. Second, the quality of online education service had a significant positive (+) effect on the degree of re-taking, and the higher the response and trust factor, the higher the re-take factor. Third, learning immersion had a significant positive (+) effect on intention reacquisition. Based on the above results, you will need to manage students using differentiated strategies online so that students majoring in aviation services can participate in classes with a positive mindset.