Reviewerly/exHarmony huggingface dataset:
현대소설을 활용한 언어, 문학, 문화의 통합적 한국어교육 방안 연구-윤흥길의 「장마」를 중심으로-

This study proposes an integrated Korean language education of language, literature, and culture as the standard of “Applied Research for the International Standard Curriculum of Korean Language”, using Yun Heung-gil’s modern novel “Rainy Season”(1973) as the text. “Rainy Season” has a high literary evaluation and contains not only the Korean War and the division of Korea, which is a characteristic history of Korea, but also abundantly contains the seasons, weather, family, Korean emotions, folk beliefs and religion. which is suitable for an integrated Korean language education of language, literature and culture. Specific educational plans are as follows. In the first lesson, students study a story, relationships of the characters through the movie “The Rainy Season”(1979). In the second class, students study language aspects such as vocabulary based on listening and reading of texts. In the third lesson, students study the themes that depicts the process of reconciliation and healing from ideological confrontation expressed through love for children during the Korean War, and through the beliefs of native citizens. In the fourth session, students make a presentation about the aspects of social conflict and reconciliation of homeland based on their understanding of Korean War and personal beliefs, the subject of conflict and reconciliation. Through this, students study culture in terms of intercultural exchange. (Pusan National University)
A review of methods for text detection in imagery of natural scenes

Abstract Text detection in natural scenes plays a key role in recognition and understanding of text in computer vision, while providing the basic possibilities for combining with Natural Language Processing (NLP). The ability of detection for small text and adjacent text is weak although the text detection in natural scenes has evolved from the horizontal text detection initially to the arbitrary shape text detection. Meanwhile, the environment of natural scenes is complex and changeable, which is a huge challenge for text detection. In this paper, we discuss and compare the horizontal and multi-directional detection methods based on target detection, as well as the curved and arbitrary shape detection methods based on the instance segmentation and semantic segmentation. The algorithm ideas are described and their advantages and disadvantages are analysed. Moreover, we found two research routes of curved text and arbitrary shape text detection known as Top-Down and Bottom-Up. According to the evaluations, PMTD [20] performs best in multi-directional text detection, while SPCNet [16] wins in the curve and arbitrary shape text detection.
Information Technology in Cinematography

The introduction of IT or digital technology in all spheres of human life is called the fourth industrial revolution. However, apart from the undoubted advantages, any revolution brings a number of problems. The authors investigate problems of how digital technologies help artists of the world cinema and how they influence it.
Handwritten Character Recognition Using Unique Feature Extraction Technique

One of the most arduous and captivating domains under image processing is handwritten character recognition. In this paper we have proposed a feature extraction technique which is a combination of unique features of geometric, zone-based hybrid, gradient features extraction approaches and three different neural networks namely the Multilayer Perceptron network using Backpropagation algorithm (MLP BP), the Multilayer Perceptron network using Levenberg-Marquardt algorithm (MLP LM) and the Convolutional neural network (CNN) which have been implemented along with the Minimum Distance Classifier (MDC). The procedures lead to the conclusion that the proposed feature extraction algorithm is more accurate than its individual counterparts and also that Convolutional Neural Network is the most efficient neural network of the three in consideration.
Coding with XML for Efficiencies in Cataloguing and Metadata: Practical Applications of XSD, XSLT and XQUERY

This book is about the use of Extensible Markup Language (XML) which has been widely adopted by libraries and publishers for sharing metadata about the information resources they collect, publish o...
소통적 통역 역량에 관한 연구: 연설문의 명제적 발화 및 대인적 발화 의도를 중심으로

In an era where machine translation is constantly improving with the accumulation of data, more research is needed in terms of finding the traits of human interpreters that distinguish them from their AI counterparts. This research draws attention to the need for more communicative approaches to interpreting pedagogy, focused on the retention of the speaker’s intentions in speech texts. The paper draws on the theoretical concepts that point to speaker’s intentions in communicative situations and how they are manifested in Korean speech texts. Then, the researcher analyzes the consecutive interpreting renditions made by interpreting students at a post-graduate T&I program in Korea to examine how the speaker’s intentions are delivered by novice interpreters during consecutive interpreting process using note-taking. Implications for note-taking pedagogy for consecutive interpreting from Korean to English is discussed in the final part of the paper.
SKIMMING, CARA KERJA DAN PENCEGAHAN PADA ATM

Cyber crime is done with several techniques, including Skimming. Skimming is to clone datafrom the magnetic stripe contained on the customer's ATM card but as information technologydevelops more and more sophisticated, the skimming method is also increasingly sophisticated,namely by utilizing GSM or WIFI technology so that actors can operate and or retrieve customerdata from distant areas from the ATM can even be done from other countries. To preventskimmimg, customers are expected to keep their PIN confidentially, see the condition of theATM before making a transaction and do not trust anyone who offers convenience.
Artificial Neural Networks as a Means of Restoring Passes in the Initial Data Array

Abstract The article presents an algorithm for restoration of the original data table using GRNN artificial neural network and the results of the algorithm in testing and empirical data. The given article also deals with calculations of the relative error for different data types with different percentages of passes. The quality of the analyzed data resulting from the passive experiment, as well as the reliability of the analysis results depends on one of the most important factors: the presence of these missing values. The distortion of the original data or incompleteness may distort the result in the general modeling process. Gaps in the original data table may be associated with a complete lack of data (raw data incompleteness) and contradictions arising from the data. And this kind of problem can occur not only with the values of a single attribute, but also with the values of a certain set of attributes especially in those cases when it comes to the large dimension of the factor space.
LibGuides: Science Library Displays: Home

A guide that has information about the displays in the science library as well as original content created for displays.
Artificial Neural Network paradigm for cost-effective networks

This paper is going to deal with the introduction for the artificial neural network and the neural network, then the characteristics of Artificial Neural Network, Applications of neural networks, Benefits and the types of learning such as supervised, unsupervised, and Reinforcement learning in supervised it is classified into 2 types as classification, regression, in unsupervised there are mainly two types such as clustering and association. An example of pattern recognition, Bayesian Network, Building the Bayesian network, types of ANN that are the feedback and feed-forward architectures, three important components of ANN and finally the main challenges in ANN and the solutions for the same.
Prosodic segmentation and functional correlations

This paper presents a pilot based on the NUCC corpus aimed at verifying the consistency of the Language into Act Theory (L-AcT) for the annotation of information structure in spoken Japanese. L-AcT focus on the perceptual relevance of prosodic breaks, foresees a strict correspondence between prosodic units and information units and bases the Information structure on the unit bearing the illocutionary cues (Comment). The model also foresees a language independent typology of information functions. The pilot shows that the detection of terminal breaks in speech goes hand in hand with the identification of speech acts by competent speakers. L-AcT works fine in all its basic principles and specifically for the illocutionary definition of the Comment. The main information unit types (Topic, Parenthesis and Appendix and Dialogic Units) also fit with Japanese. Information structure turns out largely language independent, for instance Japanese word order (SOV) applies within the Information unit but it does not across information units.
Comparative analysis of digital underwater video image color balance correction algorithms

Digital video image color balance correction algorithms are analyzed.The procedure of selecting the objects presented in a video sequence is proposed to be used in order to make a comparative analysis of color information: hue and saturation in HSL model, and chroma as well.The indices of color balance correction quality are substantiated.To carry out full-reference assessment, the groups of video sequences were chosen where various underwater vehicles filmed inside and outside the water can be found.The selection of underwater vehicles in images was made; the parameters of color information of the vehicles selected were estimated in the following video images: reference, source (underwater) and processed with the help of color balance correction algorithms under consideration.A comparative analysis of color correction methods for video recordings taken in aquatic environment was carried out in order to identify the best algorithm according to the criterion of the closest color information of objects presented in an underwater video image to color information of corresponding objects not being distorted by aquatic environment.The results of the comparison have shown that the usage of Gray World Assumption algorithm leads to an improvement in hue up to 6.12 times with saturation loss of 8.8 %, and the usage of White Patch Retinex algorithm -up to 4.43 times with a loss of saturation of 22.4 %.
ATHAFI: Agile Threat Hunting And Forensic Investigation

Attackers rapidly change their attacks to evade detection. Even the most sophisticated Intrusion Detection Systems that are based on artificial intelligence and advanced data analytic cannot keep pace with the rapid development of new attacks. When standard detection mechanisms fail or do not provide sufficient forensic information to investigate and mitigate attacks, targeted threat hunting performed by competent personnel is used. Unfortunately, many organization do not have enough security analysts to perform threat hunting tasks and today the level of automation of threat hunting is low. In this paper we describe a framework for agile threat hunting and forensic investigation (ATHAFI), which automates the threat hunting process at multiple levels. Adaptive targeted data collection, attack hypotheses generation, hypotheses testing, and continuous threat intelligence feeds allow to perform simple investigations in a fully automated manner. The increased level of automation will significantly boost the analyst's productivity during investigation of the harshest cases. Special Workflow Generation module adapts the threat hunting procedures either to the latest Threat Intelligence obtained from external sources (e.g. National CERT) or to the likeliest attack hypotheses generated by the Attack Hypotheses Generation module. The combination of Attack Hypotheses Generation and Workflows Generation enables intelligent adjustment of workflows, which react to emerging threats effectively.
Parallel Load Efficiency Factor Based Dynamic Load Balancing Algorithm in Cloud Environment

Cloud Computing can be described as any where any time storage and it is able to provide on demand services like server, storage, software etc. to the users over internet. Cloud consists of multiple virtual machines which includes several facilities like computation and storage. The foremost aim of cloud computing is to provide systematic and well regulated access to distant and geographical resources. The efficient discharge of task scheduling computing is one of the primary factors. This paper deals with the subject of dynamic load balancing for task scheduling in cloud environment. Satisfactory results can be obtained by implementing the proposed algorithm by considering distribution of tasks on the basis of types (nature), processing efficiency and load efficiency factor. In this paper, algorithm has been implemented by taking into account cloud VM groups, configuration and nature of tasks which determines that resources have been utilized efficiently. The result has been compared and shows better results in terms of average turnaround time, average response time, average waiting time and cost efficiency ratio than existing load balancing algorithms [1, 2].
Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data

We focus on the problem of unsupervised cell outlier detection and repair in mixed-type tabular data. Traditional methods are concerned only with detecting which rows in the dataset are outliers. However, identifying which cells are corrupted in a specific row is an important problem in practice, and the very first step towards repairing them. We introduce the Robust Variational Autoencoder (RVAE), a deep generative model that learns the joint distribution of the clean data while identifying the outlier cells, allowing their imputation (repair). RVAE explicitly learns the probability of each cell being an outlier, balancing different likelihood models in the row outlier score, making the method suitable for outlier detection in mixed-type datasets. We show experimentally that not only RVAE performs better than several state-of-the-art methods in cell outlier detection and repair for tabular data, but also that is robust against the initial hyper-parameter selection.
Earth’s Oldest Rocks (2nd Edition). Martin van Kranendonk, Vickie Bennett, and Elis Hoffmann, Editors

Book Review| March 01, 2020 Earth’s Oldest Rocks (2nd Edition). Martin van Kranendonk, Vickie Bennett, and Elis Hoffmann, Editors Peter A. Cawood Peter A. Cawood School of Earth Atmosphere and Environment Monash University Clayton, Victoria 3800, Australia January 23, 2020 Search for other works by this author on: GSW Google Scholar Economic Geology (2020) 115 (2): 473. https://doi.org/10.5382/econgeo.115.2.br02 Article history first online: 09 Mar 2020 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Tools Icon Tools Get Permissions Search Site Citation Peter A. Cawood; Earth’s Oldest Rocks (2nd Edition). Martin van Kranendonk, Vickie Bennett, and Elis Hoffmann, Editors. Economic Geology 2020;; 115 (2): 473. doi: https://doi.org/10.5382/econgeo.115.2.br02 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search nav search search input Search input auto suggest search filter All ContentBy SocietyEconomic Geology Search Advanced Search Earth’s Oldest Rocks (2nd Edition). Martin van Kranendonk, Vickie Bennett, and Elis Hoffmann, Editors. 2018. Elsevier. 1112 Pp. Paperback ISBN 978-0-444639011; eBook ISBN 978-0-444639028. Price: $US225. Earth’s Oldest Rocks focuses on the first 1.5 billion years of our planet’s history, covering the period from its accretion from the solar nebula to a time when plate tectonics is thought to be the modus operandi controlling Earth evolution. This record is spatially and temporally incomplete with the first 500 million years, the Hadean Eon, largely limited to a few zircon grains and some small rock outcrops. The rock record becomes more... You do not currently have access to this article.
Generating Arabic Stop-Word for Hadith

Stop-words or (function words) play a great role in performing various functions in sentences, but are still typically inadequate to use for retrieval. They consist of several elements such as common nouns, pronouns and prepositions. With that, there are several Arabic particles available in the online Khoja and Abu EL-Khair stoplist taken from various websites. Arabic stop-words’ main problem lies in accepting the prefixes and suffixes’ attachment. In the current paper, a new methodology for generating a general stop-word list has been proposed and applied on hadiths. In detail, hadith is defined as words, acts, deeds, traditions, silent approvals and character of Prophet Muhammad S.A.W. (peace be upon him). The current paper aims at examining the effect of removing stopwords from verification of hadiths. The problem is that the previously generated stop-word lists have been on Modern Standard Arabic (MSA), which is the most commonly used language in hadiths. A stop-word list of Hadith and a corpus-based list has been created to be used in the process of hadith verification. The effectiveness and success of Hadith verification when using the newly generated lists along with earlier generated lists of MSA, combining the Hadith lists have been compared with the MSA lists. The Hadith verification has been performed using sequential pattern mining. Lastly, the experiments have demonstrated that the general lists comprising hadith words showed a better performance compared to using the lists of MSA stopwords.
Nonlinear image encryption and authentication based on phase truncation and reservation in the cylindrical diffraction domain

A nonlinear image encryption and authentication strategy based on phase truncation and reservation (PTR) in cylindrical diffraction domain is proposed. First, the cylindrical diffraction spectrum of the input image is sparsely sampled. Then, its sparse presentation is disintegrated into phase part and real-valued amplitude part with the help of the PTR, both of which are essential for decryption and authentication. The decrypted image reveals little information of the original input image visually. Finally, a nonlinear correlation is resorted to authenticate the decrypted image with the input image. In the proposed strategy, the parameters of cylindrical diffraction are utilized to enhance its security. The cylindrical diffraction has the nonlinear characteristics, while the PTR outputs real-valued cyphertext, which further breaks the linearity. Furthermore, the percentage of extracted pixels in sparse sampling needs not to be identified purposely. Numerical simulations demonstrate the feasibility and effectiveness of the proposed scheme.
IMPACT OF FINANCIAL INCLUSION ON PERFORMANCE OF BANKS IN NIGERIA

The re-lunch of financial inclusion in 2012 by the central bank of Nigeria has made Nigerian banks to embrace several innovative ideas towards providing better quality services to their customers.  These innovations are expected to impact on the performance of the banks as suggested by theoretical literature. This study is therefore conducted to provide some empirical explanation on the impact of financial inclusion instruments on performance of Nigerian banks. Data were collected from World Bank database, Central Bank of Nigeria Statistical Bulletin, and annual reports of deposit money banks. The data were analysed with Fixed Effect Regression Model. The Regression analysis was conducted after carrying out the Breusch-Pagan Lagragian Multiplier (BP-LM) test to determine the suitability of either the fixed effect or random effect model.  The findings revealed positive and significant impact of Automated Teller Machines, Bank embranchment, and point of sale terminals on bank performance at both 1% and 5% levels of significance. However, the result on the number of bank account is not significant. The study concludes that improvement in the quality of financial services will attract more customers to the bank and boost their performance. It is thus recommended that more ATMs, POS and Branches be put in place for better inclusive finance.
Identification of High School Student's Career Preference with the Logistics Model

The aim of education is to develop students' potential according to their interests and talents.Students' potential and talent need to be detected early so that schools can direct students to choose majors in the university or higher education and eventually select careers that suit their interests and talents.Holland's Personality Theory is the most frequently used theory to study the phenomenon of career preference.The focus of this research is to analyze the career preference of high school students based on Holland's Personality Type.For the analysis, the researchers applied multinomial logistic regression analysis with consideration to the nominal data scale of Holland students' personality types, namely realistic, investigative, artistic, social, enterprising, and conventional.Based on the results of the analysis, it can be concluded that majority of the students have enterprising and artistic personality types.Further, the factors that significantly influence the differences in Holland's Personality Type are the student's major in high school, gender, parents' educational background, parents' income, and parents' occupation.
ORGANIZATION OF GENERIC STRUCTURE IN RECOUNT TEXTS WRITTEN BY THE UNDERGRADUATE STUDENTS

Learning the target language is actually a process of trial and error. It means that the process of language learning always deals with making mistakes. The mistakes happen when the learners use both spoken and written language, such as text. As known, there are twelve types of text, one of them is recount text. This paper aims to describe the organization of generic structure (orientation, sequence of events, and reorientation) in recount texts written by the participants. This study used error analysis as the design. The data were taken from 15 recount texts, written by the fourth semester students of English Department at STKIP PGRI Ponorogo. The technique of collecting data used was written test composition. The data were analyzed by following the error analysis theory. The result of the study showed that the organization of generic structure in recount texts was less satisfying, especially in the organization of reorientation aspect. Statistically, the mistakes found in the organization of generic structure were 8 texts without the appropriate reorientation aspect (equal to 53%) and 3 texts without the chronological sequence of events (equal to 20%). In case of orientation aspect, the whole texts provided the adequate orientation.
Research Guides: Perpetual Access (PA): How Do I Request PA Information for a Title?

This guide provides information on what Perpetual Access is, and how it is being utilized at USC Libraries for Collection Management.
Are There Bots even in FIFA World Cup 2018 Tweets?

Social media is an important communication medium in these days. Twitter is famous as microblogging service. It has been reported that social bots have been used in Twitter widely. In this research, we aim to understand whether bots are selective in the topics they participate or not. To this end, we explore tweets on FIFA World Cup. Our analysis indicate that there are bot activities even in tweets related to soccer (football) events but not just political topics.