Reviewerly/exHarmony huggingface dataset:
DUDS Jens Bille's Ballad Book, v. 1.1

DUDS Jens Bille’s Ballad Book belongs to a corpus of the oldest Danish ballad tradition. The corpus consists of 9 ballad books handed down from Renaissance ballad collectors (1553-1591). Jens Bille’s Ballad Book (1555-1559) contains 7 epic ballads, 22 lyrical ballads, 31 ballads of chivalry, 11 historical ballads, 6 ballads of the supernatural, 3 jocular ballads, 4 heroic ballads, and 4 hymns. The texts have partly been re-keyed from scholarly editions, partly transcribed from photographs of the manuscript (Karen Brahe E I,2). All texts are in XML format with tokenization, stanza and verse segmentation, orthographical neutralization, lemmatization, POS-tagging, and homograph discrimination. Individual text words are numbered consecutively.
A New Approach for Multi-agent Reinforcement Learning

Amhraoui, Elmehdi Masrour, TawfikThe classical approach of reinforcement learning for single agent is based on the concept of reward that comes only from the environment. By trial-and-error, the agent has to learn to maximize its total accumulated reward. Several algorithms and techniques were developed for a single agent reinforcement learning. Our purpose is to benefit from all done work in reinforcement learning of an agent and extend it to multi-agent system. we have proposed a new approach that is based on the following idea: Communication or cooperation of a team can be achieved through mutual reinforcement of agents, that means agents can give and receive rewards from other agents and not only from the environment. The goal of each agent is to maximize the global accumulated reward received from environment and from other agents. We treat the multi-agent system as a unique entity. We define, state, action of the system and the value of each state with respect to the global policy of the system.
IMPROVING STUDENTS’ READING COMPREHENSION ON RECOUNT TEXT THROUGH QUESTION ANSWER RELATIONSHIP STRATEGY (QAR)

This research aims to improve students reading comprehension on recounttext by using Question Answer Relationship (QAR) strategy. This researchis a classroom action research which was conducted in three cycles. Theparticipants of this research consist of the teacher and the students in classX IIS 3 of SMAN 1 Sungai Raya. The researcher collected the data ofstudents improvement in reading comprehension by observing the datathrough reading test, observation checklist, field note and self-assessmentforms. The result showed that students problems in comprehending recounttext had been solved by using QAR strategy. Right There and Think andSearch question improved students understanding of generic structure andlanguage features of recount text. The mean score of students readingcomprehension enhanced in each cycle. In the first cycle, the students meanscore was 57.2, it increased to 68.8 in the second cycle, and 82 in the thirdcycle. In other words, Question Answer Relationship (QAR) strategyimproved students reading comprehension of recount text.
국어 교과서의 훈민정음 관련 기술에 대한 비판적 고찰: ‘언문’의 의미와 『훈민정음』 반포를 중심으로

It is often said that ‘Enmun’ is a word that dictates Hwunmincengum. However, in the Chosun dynasty annals, the name ‘Enmun’ was generally used without derogatory meaning. Also the Chinese word ‘諺’ originally had the meaning of ‘spoken’ or ‘proverb.’ In many literatures, ‘Enmun’ was used in the sense of ‘our character,’ and we could not find the meaning of the contempt in this word. It is often said that in 1446 Hwunmincengum was distributed, and the related record is ‘訓民正 音成.’ However, ‘成’ means that the document is complete and does not mean the publication or distribution of the document. In many Korean textbooks, however, it is explained that the word ‘Enmun’ is a word despising ‘Hwunmincengum’ and in 1446 Hwunmincengum was proclaimed. But this is not true and should be corrected.
Audit Fraud Data Prediction Using Machine Learning Algorithms

Financial frauds are increasing day by day within the world. The enterprise acknowledges the problem and is just now beginning to act. In recent years, machine learning has developed and received major attention in the predictive analytics in audit analysis work. A careful reading of the financial statements will indicate whether or not the corporate is running smoothly or is in crisis. Financial statements are records of economic flows of a business. Generally, they include balance sheets, income statements, cash flow statements, statements of retained earnings, and a few different statements. During a shell, the financial statements are the mirrors of a company’s financial status. This paper contains the analysis of various classification techniques to detect fraud firms from 777 firms. 777 firms audit data taken from different sectors and apply different machine learning algorithms. Different classical algorithms like Bayes net, logistic, random forest, Naïve Bayes, J48, AdaBoost, etc., are compared in terms of their accuracy measure, FP rate, TP rate, F-measure, error rate, Mathew’s correlation coefficient (MCC), and area under the curve (AUC). Machine learning is bound to be an absolute necessity in the future because of emergence of unprecedented growth of contaminated financial fraud.
Analysis of mathematics teaching in Higher Vocational Education

Higher Vocational Mathematics teaching; method; probe
Analysis of Development Time of New Drugs Developed by Korean Domestic Companies

There are more than 30 new drugs developed by Korean companies, but empirical research on the new drug development process is insufficient. This study aimed to compare the development time for new drugs developed by Korean companies with previous studies on foreign companies. This study defined and analyzed each milestone of the drug development process through a public data source for new drugs approved from 1999 to 2019. The development time before initial human testing was 2.8 years and the time for each clinical development phase were 1.4 year, 2.4 year and 3.1 year, respectively. The result was similar with the previous studies in other countries. In addition, as in the case of previous research, the development time has increased in recent years.
Research Guides: Vanderbilt Television News Archive Tutorials : Media Account

A how to guide for account creation, finding content, ordering news episodes or segments, creating a Media Account, and receiving content in the Media Account.
Evaluating Single Image Dehazing Methods Under Realistic Sunlight Haze

Haze can degrade the visibility and the image quality drastically, thus degrading the performance of computer vision tasks such as object detection. Single image dehazing is a challenging and ill-posed problem, despite being widely studied. Most existing methods assume that haze has a uniform/homogeneous distribution and haze can have a single color, i.e. grayish white color similar to smoke, while in reality haze can be distributed non-uniformly with different patterns and colors. In this paper, we focus on haze created by sunlight as it is one of the most prevalent type of haze in the wild. Sunlight can generate non-uniformly distributed haze with drastic density changes due to sun rays and also a spectrum of haze color due to sunlight color changes during the day. This presents a new challenge to image dehazing methods. For these methods to be practical, this problem needs to be addressed. To quantify the challenges and assess the performance of these methods, we present a sunlight haze benchmark dataset, Sun-Haze, containing 107 hazy images with different types of haze created by sunlight having a variety of intensity and color. We evaluate a representative set of state-of-the-art image dehazing methods on this benchmark dataset in terms of standard metrics such as PSNR, SSIM, CIEDE2000, PI and NIQE. This uncovers the limitation of the current methods, and questions their underlying assumptions as well as their practicality.
Mechanisms of Realistic Facial Expressions for Anthropomorphic Social Agents

Three-dimensional facial animation has been extensively studied, but the achievement of realistic, human-like performance has not yet been decided. This article discusses various approaches for generating animated facial expressions controlled by speech. Combining the considered approaches for both facial animation, and the identification of emotions and the creation of micro-facial expressions in one system, we get a solution suitable for tasks such as game video, avatars of virtual reality or any scenario in which a speaker, speech or language is not known in advance.
Class-specific differential detection improves the inference accuracy of diffractive optical neural networks

We report new design strategies to increase the inference accuracy of Diffractive Deep Neural Networks (D2NNs). Using a differential detection scheme that is combined with the joint-training of multiple D2NNs, each specialized on a single object-class, D2NN-based all-optical classification systems numerically achieve blind-testing accuracies of 98.52%, 91.48% and 50.82% for MNIST, Fashion-MNIST and grayscale CIFAR-10 datasets, respectively. Furthermore, using three independently-trained D2NNs that project their light onto a common output plane enables the system to achieve 98.59%, 91.06% and 51.44%, respectively. Through these systematic improvements, the reported blind-inference performance sets the state-of-the-art for an all-optical neural network design.
Bounding Box Alignment Based Pedestrian Crossing Collision Avoidance Using Convolution Neural Networks

Pedestrian detection is a challenging task for autonomous vehicles in the urban environment. A pedestrian in videos has variety of appearances such as body and occluded position. The shift problem in detecting pedestrian causes the loss of parts such as legs and head. To address such a problem, we propose partition oriented convolution neural networks (CNN) based method for pedestrian recognition using saliency map and boundary box framework in this paper. The proposed method consists of two frameworks: person-detection and alignment. We use saliency map along with weights in the detection framework to remove false detections such as lamp posts and trees. The alignment network employs confidence map for better prediction of pedestrian alignment. The method is implemented and analysed on various data sets, CALTECH, INRIA and ETH. It is observed that the proposed method has better accuracy and low false positives than the existing methods
Evaluation of UM-LDAPS Prediction Model for Daily Ahead Forecast of Solar Power Generation

Daily ahead forecast is necessary for the electricity balance between load and supply due to the variability renewable energy. Numerical weather prediction is usually employed to produce the solar irradiance as well as electric power forecast for more than 12 hours forecast horizon. UM-LDAPS model is the numerical weather prediction operated by Korea Meteorological Administration and it generates the 36 hours forecast of hourly total irradiance 4 times a day. This study attempts to evaluate the model performance against the in situ measurements at 37 ground stations from January to May, 2013. Relative mean bias error, mean absolute error and root mean square error of hourly total irradiance are averaged over all ground stations as being 8.2%, 21.2% and 29.6%, respectively. The behavior of mean bias error appears to be different; positively largest in Chupoongnyeong station but negatively largest in Daegu station. The distinct contrast might be attributed to the limitation of microphysics parameterization for thick and thin clouds in the model.
PKM PERGURUAN TINGGI DI DALAM PEMBUATAN DAN MANAJEMEN SISTEM REPOSITORY PUBLIKASI PERGURUAN TINGGI

Tracing the research outcome such as journal article, proceeding and book are a must currently due to all credits and academic promotions should be able to be tracked online. One facility that is developed to facilitate the tracer function of these publications is a repository. The community service program is aimed to increase and gain the knowledge and experience of staff and lecturers in Sekolah Tinggi Ilmu Kesehatan (STIK) Tamalatea, Makassar on design and management of publication repository system in their institution. This community service program is based on the current situation in STIK where there is no repository system yet in their institution. This program consists of three main courses: 1) Introduction of credit points for academic promotion, 2) Design of repository system for institution publications, and 3) Management of repository system for institution publications. During the program, all participants of 20 persons showed enthusiasm and actively for discussion. To quantitatively the participants' performance, a simple knowledge test before and after the program was conducted. As a result, about 83,33 % knowledge of participants on the course is improved. This community service program is significantly improved participants' knowledge and positively constructed the potential cooperation between two institutions in the future.
Exploring the training methods for effective employee's performance in IT organisations in India: a SEM approach

In the dynamic phase of the market, all organisations have a variety of opportunities to grab and number of challenges to satisfy. The purpose of this study is to shed more light into the relationship of perceived training effectiveness, with various variable factors like performance appraisal, skill development, leadership etc. based on empirical research, conducted in IT organisations. A structured instrument was developed based on the review of the literature of the theme of research for data collection from the employees of top 5 IT organisations (as per NASSCOM 2016-2017). The present research provides an exclusive theoretical model that demonstrates the impact of on-the-job and off-the-job training in work efficiency, work quantity and work quality. It is concluded that if an organisation wants to increase their employee's performance they need to have a balance between on the job training and off the job training.
Analysis of the Period Recovery Error Bound

The recovery problem is the problem whose input is a corrupted text T that was originally periodic, and where one wishes to recover its original period. The algorithm’s input is T without any information about either the period’s length or the period itself. An algorithm that solves this problem is called a recovery algorithm. In order to make recovery possible, there must be some assumption that not too many errors corrupted the initial periodic string. This is called the error bound. In previous recovery algorithms, it was shown that a given error bound of n/((2+e)p) can lead to O(log_{1+e} n) period candidates, that are guaranteed to include the original period, where p is the length of the original period (unknown by the algorithm) and e > 0 is an arbitrary constant.This paper provides the first analysis of the relationship between the error bound and the number of candidates, as well as identification of the error parameters that still guarantee recovery. We improve the previously known upper error bound on the number of corruptions, n/((2+e)p), that outputs O(log_{1+e} n) period candidates. We show how to (1) remove e from the bound, (2) relax the error bound to allow more errors while keeping the candidates set of size O(log n). It turns out that this relaxation on the previously known upper bound is quite challenging. To achieve this result we provide what, to our knowledge, is the first known non-trivial lower bound on the Hamming distance between two periodic strings. This proof leads to an error bound, that produces a family of period candidates of size 2log₃ n. We show that this result is tight and further provide a compact representation of the period candidates. We call this representation the canonic period seed.In addition to providing less restrictive error bounds that guarantee a smaller candidate set, we also provide a hierarchy of more restrictive upper error bounds that asymptotically reduces the size of the potential period candidate set.
Tarski's Undefinability Theorem and Diagonal Lemma

We prove the equivalence of the semantic version of Tarski's theorem on the undefinability of truth with a semantic version of the Diagonal Lemma, and also show the equivalence of syntactic Tarski's Undefinability Theorem with a weak syntactic diagonal lemma. We outline two seemingly diagonal-free proofs for these theorems from the literature, and show that syntactic Tarski's theorem can deliver Godel-Rosser's Incompleteness Theorem.
Vehicle Classification Using Point Cloud a Deep Learning

AI and machine learning have grown exponentially over the last couple of years. Today, many problems can be solved or improved using this technology. For instance, neural networks have proven to be ...
Recursive Additive Complement Networks for Cell Membrane Segmentation in Histological Images

A recursive additive complement network (RacNet) is introduced to segment cell membranes in histological images as closed lines. Segmenting cell membranes as closed lines is necessary to calculate cell areas and to estimate N/C ratio, which is useful to diagnose early hepatocellular carcinoma. The RacNet is composed of a complement network and an element-wise maximization (EWM) process and is recursively applied to the network output. The complement network complements the lacking parts of cell membranes. The network, however, has a tendency to mistakenly delete some parts of the segmented cell membranes. The EWM process eliminates this unwanted effect.Experiments carried out using unstained hepatic sections showed that the accuracy for segmenting cell membranes as closed lines was significantly improved by using the RacNet.Three imaging methods, bright-field, dark-field, and phase-contrast, were used, as unstained sections show very low contrast in the bright-field imaging commonly used in pathological diagnosis. These imaging methods are available in optical microscopes used by pathologists. Among the three methods, phase-contrast imaging showed the highest accuracy.
LibGuides: Remote Library Services for Online Learning: Books

This guide offers links and answers questions for the online learning shift taking place in response to the COVID-19 outbreak.
Pelaksanaan Gerakan Literasi Finansial pada Sekolah Menengah Atas dan Kejuruan (Studi Situs SMAN 1 Surakarta & SMKN 6 Surakarta)

Increasingly, needs require individuals to be able to manage their finances at least personal finances. In 2016 the ministry of education and culture has established a program of financial literacy movements in the school curriculum. The aim of the program is to improve the knowledge, understanding, and skills of the nation's generation when it comes to financial management. To that end, the study aims to illustrate and humanize the process of creating, implement, and factor that influences the development of high-school literacy programs (SMA) and vocational (SMK). Research is performed at SMAN 1 surakarta and it SMKN 6 Surakarta. Research sources include principals or representing, economic and accounting teachers, and students from each school. The research object is the active-literacy programme of SMAN 1 surakarta and SMKN 6 Surakarta. Research methods use qualitative work with ethnographic design. Data retrieval is done with interview techniques, observation, and documentation. Testing the validity of data involves triangulation, whereas data analysis techniques employ nonstatistical qualitative data analysis with research development of ethnographic according to spradley. Research shows that SMAN 1and SMKN 6 have created a factogenial literacy program through the four steps of initial identification, socialization, policy desensitization, and activity design. The description of the program's performance has three key sections: grade-based development or learning, culture, and society. Supporting the program's policies of the central government, good participation of schools, community support, and adequate means and infrastructure. Inhibitory factors are made up of the lack of sensitivity and discipline of a small percentage of school residents, as well as the monotonous literation activities.
Research on Discourse Management of Social Media In Western Multinational Enterprises

This paper analyzes the discourse management status quo of social media in western multinational enterprises. It points out two existing situations in the discourse management, which include successful and improper uses, and the significance of successful use -- the application of social media is conducive to promoting the openness and transparency of enterprise’s news ; the widespread use of social media has established a bridge for communication between companies and the outside world; the correct application of social media is conducive to improving the company's product quality and effectiveness; the correct application of social media can provide enterprises with excellent customer service resources as a guarantee. The paper also offers some suggestion for further improvement in the discourse management in western multinational enterprises: social media should listen carefully and humbly to everyone's feedback on their business ideas and commercial products; companies need to communicate relevant information honestly and artistically on social media and focus on the diversification of social media use.
On the list recoverability of randomly punctured codes.

We show that a random puncturing of a code with good distance is list recoverable beyond the Johnson bound. In particular, this implies that there are Reed-Solomon codes that are list recoverable beyond the Johnson bound. It was previously known that there are Reed-Solomon codes that do not have this property. As an immediate corollary to our main theorem, we obtain better degree bounds on unbalanced expanders that come from Reed-Solomon codes.
Job Satisfaction of the Teachers of the First Three Grades in the Schools Under the Supervision of First Zarqa Directorate of Education from Their Perspective

The present study aimed to explore the job satisfaction level of the teachers of the first three grades in the schools under the supervision of First Zarqa Directorate of Education from their perspective. The sample consists from 177 teachers. This study was conducted during the academic year (2017/2018). Those teachers were selected through using the simple random sampling method. They were selected from the schools under the supervision of First Zarqa Directorate of Education in Jordan. A questionnaire was used for data collection. The validity and reliability of the questionnaire were measured. It was found that the job satisfaction level of the teachers of the first three grades in the schools under the supervision of First Zarqa Directorate of Education is moderate. It was found that there isn’t any statistically significant difference - at the statistical significance level of (α ≥0.05)- between the respondents’ job satisfaction levels which can be attributed to (gender, academic achievement and experience). It was found that there is a statistically significant correlation between job satisfaction from one hand and (work environment, teachers’ relationships with the administration, moral and financial incentives & teachers’ relationships with colleagues and society members) from another hand. The researcher recommends improving the physical work environment of the teachers of the first three grades. That shall raise the job satisfaction level of those teachers. Keywords: Job satisfaction, the first three grades, First Zarqa Directorate of Education DOI: 10.7176/JEP/11-24-04 Publication date: August 31 st 2020