Reviewerly/exHarmony huggingface dataset:
TV 드라마 〈동백꽃 필 무렵〉의 성공 요인 분석 - 대본과 그 장르를 중심으로 -

After Media Law passed in July 2009, General Service Program Providers have formed in December, 2011. Due to that incident, media contents distribution channels have expanded and the audience viewing rate has fallen down generally. Shortly after openning, General Service Program Providers downsized drama part because of financial difficulties, even though drama part was the only revenue model. However, financial situation gradually recovered and by 2015, General Service Program Providers safely landed on right track. In 2019, JTBC’s drama, 〈Sky Castle〉 has reached as high as 22.3% viewing rate. It was recorded as the top viewing rate among General Service Program Providers including all the other cable channels. The formal broadcasting networks’ dramas once reached over 50% viewing rate, however they hardly can reach 20% currently. Since 2011, no drama has reached over 30% viewing rate other than 〈Descendants of the Sun〉. The drama industry faces a situation where no drama hardly reaches 20% viewing rate, and many of them get terminated airing before the final episode. Korean drama market is in the era where over 20% of viewing rate is considered as a success. The market size is limited. However, there is more supply than the demand currently. That leads to very poor production environment and the whole industry is daunted. The quality of contents downgraded over all. This market change happens much faster than the industry workers’ adaptation. There is no clear solution to this problem yet. A lot of industry people are still in the cave and repeat producing conventions. However, in 2019, KBS produced very unique soap called, 〈When Camellia Blooms〉. It has reached 23.8% viewing rate and is considered the best drama of 2019. No top stars appear in this piece and the production value is not as high as 〈Descendants of the Sun〉 and other hit dramas. 〈When Camellia Blooms〉 follows conventions but yet, the budget is not as high as other hit dramas. It just twists conventions a little bit and sucks in viewers who are very tired of conventions. This paper suggests that 〈When Camellia Blooms〉 may be a very smart and economic success model in the industry. By analyzing success factors of 〈When Camellia Blooms〉, drama industry may shorten the adaptation period and produce high quality dramas.
Spread Scheduling Strategy In Docker Container Using Meta-Heuristic Optimization

In recent time, spread scheduling plays a major role in docker swarm and it operates on a single objective in order to disseminate the containers for a service with possible nodes. However, if a node undergoes overloading or underloading, a fault-tolerant engine is always considered reliable. Such failure of nodes should be addressed in a faster manner in a cluster of nodes to carry out the operations in docker container. In this paper, we propose a new spread scheduling strategy using a meta-heuristic optimization that will solve the problem and no node will be overloaded and underloaded after failure of nodes in cluster. The study takes into consideration, the constraints associated with scheduling and clusters the priority task in the docker and enables optimal scheduling. The simulation is conducted to study the efficacy of the model in terms of various parameters that includes resource cost, execution time and energy consumption.
Bridging the Gap Between Ontology and Lexicon via Class-Specific Association Rules Mined from a Loosely-Parallel Text-Data Corpus

There is a well-known lexical gap between content expressed in the form of natural language (NL) texts and content stored in an RDF knowledge base (KB). For tasks such as Information Extraction (IE), this gap needs to be bridged from NL to KB, so that facts extracted from text can be represented in RDF and can then be added to an RDF KB. For tasks such as Natural Language Generation, this gap needs to be bridged from KB to NL, so that facts stored in an RDF KB can be verbalized and read by humans. In this paper we propose LexExMachina, a new methodology that induces correspondences between lexical elements and KB elements by mining class-specific association rules. As an example of such an association rule, consider the rule that predicts that if the text about a person contains the token Greek, then this person has the relation nationality to the entity Greece. Another rule predicts that if the text about a settlement contains the token Greek, then this settlement has the relation country to the entity Greece. Such a rule can help in question answering, as it maps an adjective to the relevant KB terms, and it can help in information extraction from text. We propose and empirically investigate a set of 20 types of class-specific association rules together with different interestingness measures to rank them. We apply our method on a loosely-parallel text-data corpus that consists of data from DBpedia and texts from Wikipedia, and evaluate and provide empirical evidence for the utility of the rules for Question Answering.
An Ancient Indian Handwritten Script Character Recognition by Using Deep Learning Algorithm

Handwritten character recognition is one of the most popular and widely used techniques in Pattern Recognition and Image processing. The Difficulty level about the handwritten character recognition is increasing when the handwritten characters are the ancient script of any region. This offline handwritten character manual identification and analysis is a time consuming and lengthy process. During manual recognition process, there might have possibilities of human errors. This human error might change the meaning of existing ancient document content. Hence accurate analysis and transliteration/translation is an essential requirement for keeping ancient document alive. In this research paper, the ancient script called MODI script has used for handwritten characters identification. The overall recognition mechanism has presenting by a Classification algorithm which is a highly accurate Convolutional Neural Network (CNN) algorithm. The current paper is categorized into four sections. The First section describes the introductory part of the current research work along with Ancient MODI script and Deep learning model called AlexNet. The second section which is proposed system work like preparation of dataset, preprocessing, and data augmentation. The Next section is the Experimental arrangement and result of the proposed research work.The last section is the conclusive remark of proposed system.
Participación juvenil en la escuela secundaria en Buenos Aires durante el COVID-19

The article analyzes youth experiences in relation to participation and citizenship in educational institutions in secondary school in Buenos Aires, Argentina, during the COVID-19 pandemic. In a context of changes in student sociability, the ways of intervening in public discussion were also reconfigured. The methodological approach combined a mixed approach, organizing focus groups and individual interviews, following a semi-structured guide and applying a survey through a google form. The work analysis the pre-pandemic student politicization processes as well as the demands and actions in the new scenario.
SMART AGRICULTURE SYSTEM WITH INTERNET-OF-THINGS (IOT)“An In-depth Analysis of Global Online Retail Sales Using the Classical Apriori Algorithm”

In today's retail and product sales world, firms rely heavily on customer behavior information to make business decisions. Also, e-commerce giants and other businesses rely on this data to improve customer service and increase profits. Customer service is being improved by vendors, who will no longer waste time searching for products and instead share and promote the peripheral or the product which is most commonly purchased with the primary product. For example, we utilized an apriori algorithm to determine whether or not it was possible to purchase a B-post in conjunction with an A-post. It offers a number of advantages. Shopping on a portal or at a store for a short period of time enhances the rating of the portal and the site's performance.
국내에서의 지진현장경보 기술 고도화 및 적용

Purpose: This study aims to derive a PGV prediction equation and to enhance the application of the Onsite EEW technology which has developed through previous studies. Method: The prediction equation for the Onsite EEW derived from earthquake data M≥3.0 and MMI≥II over the past four years. Local seismic risk is estimated using M and PGV deduced from P wave properties. Result: The improved PGV prediction equation estimated the MMI with an average accuracy of 94.8% and the Tc : Pd method also showed valid performance for alerting local seismic risks. Conclusion: Onsite EEW technology is successfully applied to Korea, and becomes to reduce the blind zone to about 14km.
Differences On Students’ Learning Outcomes With High And Low Achievement Motivation

This research aims to examine the difference of students’ learning outcomes as an effect of achievement motivation in writing an English Essay through film-assisted inquiry-based learning method. It was a quasi-experimental research non-equivalent control group design which implemented into two different parallel classes. They are experimental group and control group, in which seventy two students were accepted as subject surveyed through cluster random sampling technique. Data of students’ learning outcomes collected through pre-test and post-test. While data of students’ achievement motivation level collected through questionnaire. The data of pre-test was taken before treatment, used to determine students’ variance, whereas post-test data was taken after treatment entirely finished to examine students’ learning outcomes differences. Data analysis using SPSS 22 with ANOVA Factorial 2x2 (two- way ANOVA. The hypothesis testing was conducted in 5% of significance level. The result of data analysis indicates that the p-value of t-counted is 0.000 lower than 0.05(˂0.05). It can be interpreted that there is a significant difference of learning outcomes between the students who have a high achievement motivation and those who have low one in writing an English essay through film-assisted inquiry-based learning method. Moreover, the students with high achievement motivation have better achievement than the students with low achievement motivation.
Measure-Rewind-Measure: Tighter Quantum Random Oracle Model Proofs for One-Way to Hiding and CCA Security.

We introduce a new technique called ‘Measure-Rewind-Measure’ (MRM) to achieve tighter security proofs in the quantum random oracle model (QROM). We first apply our MRM technique to derive a new security proof for a variant of the ‘double-sided’ quantum One-Way to Hiding Lemma (O2H) of Bindel et al. [TCC 2019] which, for the first time, avoids the square-root advantage loss in the security proof. In particular, it bypasses a previous ‘impossibility result’ of Jiang, Zhang and Ma [IACR eprint 2019]. We then apply our new O2H Lemma to give a new tighter security proof for the Fujisaki-Okamoto transform for constructing a strong (\({\mathsf {IND}}{\text {-}}{\mathsf {CCA}}\)) Key Encapsulation Mechanism (KEM) from a weak (\({\mathsf {IND}}{\text {-}}{\mathsf {CPA}}\)) public-key encryption scheme satisfying a mild injectivity assumption.
Tackling Domain-Specific Winograd Schemas with Knowledge-Based Reasoning and Machine Learning

The Winograd Schema Challenge (WSC) is a commonsense reasoning task that requires background knowledge. In this paper, we contribute to tackling WSC in four ways. Firstly, we suggest a keyword method to define a restricted domain where distinctive high-level semantic patterns can be found. A thanking domain was defined by keywords, and the data set in this domain is used in our experiments. Secondly, we develop a high-level knowledge-based reasoning method using semantic roles which is based on the method of Sharma [Sharma, 2019]. Thirdly, we propose an ensemble method to combine knowledge-based reasoning and machine learning which shows the best performance in our experiments. As a machine learning method, we used Bidirectional Encoder Representations from Transformers (BERT) [Jacob Devlin et al., 2018; Vid Kocijan et al., 2019]. Lastly, in terms of evaluation, we suggest a robust accuracy measurement by modifying that of Trichelair et al. [Trichelair et al., 2018]. As with their switching method, we evaluate a model by considering its performance on trivial variants of each sentence in the test set.
IMPLEMENTATION OF EDUCATION BUSINESS MANAGEMENT IN BANDAR LAMPUNG

The educational institution of Al-Kautsar High School Lampung is an independent institution and carries out several business units. Researchers, in this case, research to find out about the implementation of business management education in Al-Kautsar High School. The type of research used is qualitative. They are collecting data using observation, interviews, and documentation and testing the validity of the data using source triangulation techniques. The results showed that Al-Kautsar High School is an educational institution capable of becoming an independent academic institution. This can be proven by business applications such as canteen, AK water, tutoring, outbound, and umrah. The income from these business units is used to repair, add, and maintain facilities and infrastructure. Private educational institutions have benefited from the implementation of these efforts.
A deep learning object tracking accelerator

Since the current nerual network accelerator couldn't efficiently accelerate the post-processing of object tracking, a dedicated object trackeris proposed. A neural network architecture is introduced to extract the features of the input feature map. At the meanwhile, it generates thebounding box confidence and position offset sets. Adedicated acceleration module is designed for the anchor regression, penalty calculation and extraction.By synchronizing the data between the neural network accelerator and the dedicated module, a new pipelined structure is proposed to execute the feature extraction and anchor regression in parallel. Therefore, the end-to-end processing of the object tracking is efficiently achieved. The accelerator consumes an area of 3.64 mm2 under the SMIC 40nm process, and achieves 5.71 Tops/W energy efficiency. Experimental results show that, compared with the current accleration solutions, the object tracking accelerator achieves 1.53 times acceleration, and it could realize real-time video processing(31fps). For the post-processing task of the tracking, the processing speeds of the proposed dedicated module is improved by 3.2 times than the RISC processor.
Auditing and Compilations Sharing With Sensitive Information Bidding for Secured Cloud Storage

The compilations are gets stored in the cloud nowadays. To maintain the compilations very secretly they can create a secured key for their compilations storage. The compilations can be bidden in their own devices from others. But in the cloud the compilations can be hacked by the hackers. The hackers can fetches the details of the particular person. To prevent these sort of compilations fetching from the hackers they follows the compilations hiding system in the cloud. The compilations which is get upload in the cloud is bidden to others. When there is the need of the extraction of the compilations it can be visible to others. This compilations hiding technology system can be implemented in the cloud storage. To protect it from the external user.
The role of traditions and culture in aesthetic education

The article analyzes the role of family in aesthetic education based on folk traditions. A justification of the importance of aesthetic education of children and young people in the general system of spiritual and moral education was given. It is considered the structure of the concept of “aesthetic education,” the specifics of family education in Chechnya, the significance of folk art for aesthetic education. The article describes the main forms of folk art which have a leading role in the aesthetic education of children and young people.
The Application Of E-Learning Strategies In Palestinian Universities

The dynamism and complexity of the external environment of an organizationrequires interdependent decisions. Hence, this type of problem requires a means ortool that presents the results of multiple decisions in a simple and logical manner thatfacilitates the understanding and evaluation of alternatives and the selection of thebest ones. Therefore, in this research, I used both the effect diagram and the decisiontree models, because it is important to have a clear graphic representation that focuseson areas of uncertainty to represent the problem. Through this research, try to answerthe following questions: What is the reality of the problem that we suffer from inPalestine? What is the role of decision analysis models and their philosophy insolving the decision problem? What is the logical relationship between decisionanalysis models in solving the problem?Initially, the effect diagram for the researchdecision problem was constructed to capture the various uncertainties, then it wasmoved to a decision tree. The decision tree is analyzed by reversing the direction ofthe drawing after its completion by finding the expected value for each alternative,comparing the values, choosing the best and placing them next to the final decisionpoint. Based on these values, the best alternative was determined. The decision tree inthe research helped exclude and delete the bad alternatives in order to reach theappropriate decision.The Palestinian government’s decision to provide the Ministry ofEducation with an amount of money to invest in the education sector to introduce elearningstrategies as a standardized approved curriculum in universities. The Ministerof Education formed a working group, in order to optimize the use of e-learningstrategies in Palestine. What is required is to draw an effect chart and decision tree toclarify the best path to achieve material values in the application of optimal e-learningstrategies and intangible values in preparing a technological society in which ageneration of learners harness technological progress in education and achieve anaccumulation of technically prepared human fortune. What is required here is to makea decision analysis of the problem and take the right decision,The Minister ofEducation (decision maker) clarifies the goal and grants facilities to obtain financialsupport for directors of education directorates to support an integrated work planproduced by the work team and agree to prepare, plan, evaluate and then implementit. The results obtained: Modernizing the infrastructure of the Internet at a high flowspeed and providing the sources of devices, equipment and necessary subscriptions inproportion to the needs of teachers and learners and their material capabilities with theprovision of technical and technical support and the use of an expert and the paymentof 7 million dollars.
Implementation for manipulator motion planning using MATLAB/Simulink

This paper presents a numerical algorithm (i.e., E47 algorithm) for solving the motion planning problem of a manipulator. We use MATLAB to simulate the motion planning problem of planar 6-DOF manipulator. Simulation results show the effectiveness of the E47 algorithm, and then we built the hardware implementation environment of the algorithm through Simulink. The algorithm was successfully deployed on the Arduino Due demo-board. The E47 algorithm can be successfully applied to the motion planning and actual control of a planar 6-DOF manipulator.
Heuristic Feature Models for Detection of Disrupted Markov Patterns

A challenge for the visual system is to go beyond immediately visible patterns to identify the scene processes that generated them. One sees the stripes, one infers the zebra. We asked observers to judge whether each of 100 binary sequences of 20 blue and yellow squares were generated by one of two generators. Each sequence was equally likely to be the outcome of a random generator with probability of repetition 0.5 ("a fair coin") or a two-state Markov generator, with a probability of repetition 0.9, tending to generate long, repeating sequences of yellow or blue. In addition for the sequences generated by the Markov generator, each square in each sequence could be independently disrupted (flipped from blue to yellow or vice versa). There were three experimental conditions with probabilities of disruption 0.1, 0.2, and 0.3, respectively. Each observer received extensive training with both generators and disruption. We first compared human performance to that of an ideal model derived from Bayesian decision theory (BDT). Ratios between the accuracy of observers and that of the BDT model were 0.83, 0.97, and 0.95 in the three conditions. Human observers were markedly suboptimal but (surprisingly) the relative advantage of the Bayesian model decreased with increasing disruption. We then compared human performance to that of several different heuristic feature models (HFMs). Each HFM based its judgment on a specific visual feature of a sequence such as the length of the longest repeating subsequence or the number of subsequences. No HFM performed as well as the Bayesian but some feature models outperformed the median human observer. Two HFMs ("length of longest subsequence" and "total number of repetition") matched the pattern of responses for roughly half the observers. Human performance is better captured by simple heuristic feature models than a model based on Bayesian decision theory.
PENINGKATAN KEMAMPUAN KONSEP BILANGAN 1-20 MELALUI PENGGUNAAN GARIS BILANGAN PADA ANAK KELOMPOK TK B DI TK ISLAM AZ-ZAHRA PALEMBANG TAHUN AJARAN 2018-2019 (Similarity)

This research is entitled Enhancing the Ability of Concepts of Numbers 1-20 Through the Use of Number Lines in Children of Kindergarten Group B in Islamic Kindergarten Az-Zahra Palembang Academic year 2018-2019”. This study aims to improve the ability of 1-20 concepts through the use of number lines on learning in B TK groups in the Islamic Kindergarten Az-Zahra Palembang. This type of research is Class Action Research. The sample in study were children of class B 3 wich numbered 20 children of class B 3 which numbered 20 children consisting of 11 men and 9 women. The result of the Pre- cycle Clculation are 20%, the result in the first cycle are 75% and the result in the second cycle are 90%. So it can be concluded that the use of number lines can increase the ability of the 1-20 number concept in B3 class children of Islamic Kindergarten Az-Zahra. With this action the average conceptual ability of number 1-20 children is 90% with interpretations developing very well (BSB)
Rocks, Minerals, & Geology of the Pacific Northwest by Leslie Moclock and Jacob Selander. A Timber Press Field Guide. Timber Press; timberpress.com. 358 pages; 2021; $27.95 plus shipping and handling (softbound).

"Rocks, Minerals, & Geology of the Pacific Northwest by Leslie Moclock and Jacob Selander. A Timber Press Field Guide. Timber Press; timberpress.com. 358 pages; 2021; $27.95 plus shipping and handling (softbound).." Rocks & Minerals, 96(5), pp. 476–477