Reviewerly/exHarmony huggingface dataset:
Criticism of Gaya History Studies in South Korea's Pedagogical Academy - Focusing on Kim Tae-shik and Lee Young-shik

In the 19th century, with the rise of the theory of Korea in Japan, the theory of invasion first created under the name of so-called modern history is the Imna-Japanese theory. It is a claim that Yamatowa ruled or managed the southern part of the Korean Peninsula based on Gaya in the southern part of the Korean peninsula from the 4th to the 6th century AD. It is an antihumanitarian invasion theory advocated by imperialist historians based on exaggerated, embellished, fabricated, and distorted articles in 『Nihon Shoki』 compiled in the 8th century. The ideology of Yamatowa, which sought to realize the ruling system with the emperor as the apex, is contained in the Imna Nihon Headquarters Theory, which is still adhered to by most of the academic circles of Japanese ancient history. In 1945, with the collapse of the Japanese Empire, the arguments that should have been liquidated were compiled in 『Imna Heungmansa』 in 1949 by Suematsu Yasukazu, who was active in the Japanese Government-General of Korea and Gyeongseong Imperial University.&#x0D; There is no primary literature or archaeological data to prove the Imna or orthodox opinion in the academic circles of Japan and South Korea. As a result, the history of Goguryeo, Baekje, Silla, Gaya, etc., and the real history of Gojoseon and the pre-Gojoseon that gave birth to those nations were damaged, and Korean history was established as a history of identity and heteronomy. Therefore, examining the reality of Gaya history and the core logic of the theory of Imna Japan through primary literature and archaeological data is inevitably a serious task to restore the original form of Korean history.&#x0D; This study approached the reality of Gayasa based on 『Samgukyusa』 and 『Samguksagi』, and analyzed the core logics of Kim Tae-shik and Lee Youngshik, who are talked about as authorities in Gaya history research, to dismantle the basis of Imna Nihonbu theory and set a new turning point in Gay history research. Its purpose is to create
A Study on the Development of Chinese Character Idioms Application for Korean Language Learning

Not only can Chinese character idioms understand the wisdom and mindset of Korean people but they also have various values that are useful for effective communication. In order for Korean learners to communicate smoothly and naturally they must not only understand the dictionary meaning of language or the structural meaning of sentences but also have the ability to use Chinese character idioms that contain cultural backgrounds according to the situation. Therefore the more textbooks or applications that can systematically learn Chinese characters will be helpful.&#x0D; Chinese character idioms are included in middle and high-level vocabulary in Korean. It is necessary to develop a mobile-based Chinese character language application in order to allow learners to learn Chinese character language anytime and anywhere.&#x0D; Therefore in this paper as a preceding study in the development of Chinese character language applications first of all, the needs of learners and the existing Chinese character language applications were analyzed.&#x0D; Through a survey of Korean learners many of the respondents showed an active interest and willingness to learn Chinese character idioms as well as the need to learn Chinese character idioms alone. It should also be designed to reflect user needs in the composition of key features content and structure of learning information and evaluation types to be applied to Chinese character idioms applications.&#x0D; In addition problems and implications were presented to help develop Chinese character idioms applications for Korean learning by analyzing popular Chinese character language applications on the market.&#x0D; We hope that this study will help Korean language education a little and designing and implementing actual applications will remain as the next task.
Introduction to the Special Issue of Recent Advances in Computational Linguistics for Asian Languages

introduction Share on Introduction to the Special Issue of Recent Advances in Computational Linguistics for Asian Languages Authors: Jerry Chun-Wei Lin Western Norway University of Applied Sciences, Bergen, Norway Western Norway University of Applied Sciences, Bergen, Norway 0000-0001-8768-9709View Profile , Vicente GarcÍa DÍaz University of Oviedo, Spain University of Oviedo, Spain 0000-0003-2037-8548View Profile , Juan Antonio Morente Molinera University of Granada, Spain University of Granada, Spain 0000-0002-2729-6900View Profile Authors Info & Claims ACM Transactions on Asian and Low-Resource Language Information ProcessingVolume 22Issue 3Article No.: 62pp 1–5https://doi.org/10.1145/3588316Published:14 April 2023Publication History 0citation29DownloadsMetricsTotal Citations0Total Downloads29Last 12 Months29Last 6 weeks29 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Instalasi Ulang Penerangan Listrik di Pondok Pesantren Tarbiyatunnisa Desa Serdang Kulon Kecamatan Panongan Kabupaten Tangerang

In today's human life, presumably almost depend on electricity. Some of the things that arise if there is a disturbance in electricity, among others, there is no lighting resulting in darkness at night. Electrical installation installation standards have been regulated in the General Electrical Installation Requirements. Apart from matters relating to the security of the electrical installation network, there are other things that we must pay attention to. This is the standard intensity of illumination. The intensity of room lighting is determined in lux units. The amount of room lighting intensity has been regulated in SNI 03-6575-2001. If the lighting intensity in a room is inadequate, it will cause impaired vision problems. The purpose of this activity is to ensure that the lighting installation meets the standards for both installation safety and lighting intensity. The methods of these activities are lectures, counting and reinstalling lighting installations at the Islamic boarding school. is to calculate the amount of safety, conductor, component specifications, and component layout. In addition, the capacity and number of lamp requirements for each room are calculated. The re-installation is carried out by replacing all electrical networks using standard quality components and installing light points as needed. The conclusion of these activities is that after carrying out these activities the installation becomes safe and the lighting of each room is as needed
ANALYSIS NAIVE BAYES TO SELECTION NEW STUDENTS FOR SUPERIOR CLASS STMIK ROYAL

Abstract: Superior students represent active and intelligent students who are able to make a direct contribution to the development of the nation. To produce excellent students, one of the efforts that can be made is to foster these superior students from the start by forming a superior class. In forming a superior class, an effective selection process is needed to select students who are truly superior. This research was conducted at STMIK Royal Kisaran where the object of research was prospective new students for the superior class and the related party was the Academic and Student Administration Bureau (BAAK) because the party was directly involved in selecting prospective new students for the superior class. But the problem is, BAAK does not yet have an election process based on a method and there is no information system for selecting prospective new students for superior classes. The purpose of this study is to make predictions related to the selection of prospective new students for superior classes in the future with the Naïve Bayes Algorithm and implemented in an information system.The results of this research are that the Naïve Bayes algorithm produces an accuracy rate of 60% in the good classification category which is measured by the level of accuracy using the confusion matrix, so that the information system produced in this study also has efficient prediction results and is expected to help BAAK. Keywords: data mining; naïve bayes; superior student class. Abstrak: Mahasiswa unggulan merupakan representasi dari mahasiswa aktif dan cerdas yang mampu memberikan kontribusi langsung terhadap perkembangan bangsa. Untuk menghasilkan mahasiswa yang benar unggul salah satu upaya yang dapat dilakukan adalah dengan membina mahasiswa unggulan tersebut sejak awal dengan membentuk kelas unggulan. Dalam membentuk kelas unggulan dibutuhkan proses seleksi yang benar efektif untuk memilih mahasiswa yang benar unggul. Penelitian ini dilakukan di STMIK Royal Kisaran dimana objek penelitian merupakan calon mahasiswa baru untuk kelas unggulan dan pihak yang terkait adalah Biro Administrasi Akademik dan Kemahasiswaan (BAAK) karena pihak tersebut terlibat langsung dalam pemilihan calon mahasiswa baru untuk kelas unggulan. Namun permasalahannya, pihak BAAK belum memiliki sebuah proses pemilihan berdasarkan metode dan belum adanya sistem informasi pemilihan calon mahasiswa baru kelas unggulan. Tujuan dari penelitian ini adalah melakukan prediksi terkait pemilihan calon mahasiswa baru kelas unggulan di masa mendatang dengan Algoritma Naïve Bayes dan diimplementasikan dalam sebuah sistem informasi. Hasil penelitian ini algoritma Naïve Bayes menghasilkan tingkat akurasi sebesar 60% dengan kategori good classification yang diukur tingkat akurasinya dengan menggunakan confusion matrix, sehingga sistem informasi yang dihasilkan dalam penelitian ini juga memiliki hasil prediksi yang efisien dan diharapkan dapat membantu pihak BAAK. Kata Kunci: data mining; mahasiswa kelas unggulan; naïve bayes.
Towards a Promising Forward-looking Vision for the Student Guidance and Counseling System: King Saud University as a Model

This paper sheds light on analyzing the reality of the student guidance and counseling system in the university environment towards a forward-looking vision to activate this system at King Saud University as a model. The descriptive approach was used to define the roles and objectives of guidance and counseling in the university educational system. A set of theoretical frameworks and guidelines were analyzed to activate the guidance and counseling system in order to build a forward-looking vision for King Saud University that takes into account the development of the intellectual, physical, social and psychological structure of student. Numerical data were analyzed using the questionnaire tool for a random sample targeting faculty members and counselors at King Saud University as a case study. The results of the study showed that there is a gap between the objectives of the guidance and counseling programs and the reality of practice at the university. The study recommended the need to develop the student guidance and counseling system at King Saud University so that it is part of an integrated framework for the various units and programs of the university.
MOBILE LEGEND GAME PREDICTION USING MACHINE LEARNING REGRESSION METHOD

Abstract: A research institute explains that with 83.7 million people using the Internet, Indonesia is among the top 20 internet users globally. Various individual or group activities require an internet network, one of which is playing games, for developments in the gaming sector, especially the MOBA (Massive Online Battle Arena) genre game, is being hotly discussed. There are various kinds of MOBA genre games, one of which is the Mobile Legends game. Many E-Sport Mobile Legends teams, especially in Asia, make this phenomenon a business space to generate large profits. In this study, the researcher recommends a good machine learning algorithm to predict the outcome of Mobile Legends matches. Of the 600 match history data analyzed, this study recommends the Artificial Neural Network (ANN) and Random Forest (RF) algorithms as the right algorithms to predict the outcome of the match. Prediction results from each algorithm can reach 82% and 80% accuracy. These findings can help the E-sports analysis team build their match strategy. Keywords: artificial neural networ; machine learning; mobile legend; prediction; random forest Abstrak: Sebuah lembaga penelitian menjelaskan bahwa dengan 83,7 juta penduduk yang menggunakan Internet, Indonesia termasuk di dalam 20 besar pengguna internet secara global. Berbagai aktivitas individu atau kelompok membutuhkan jaringan internet, salah satunya adalah bermain game, untuk perkembangan pada sektor game khususnya game bergenre MOBA (Massive Online Battle Arena) sedang hangat diperbincangkan. Ada berbagai macam game bergenre MOBA, salah satunya game Mobile Legends. Banyak tim E-Sport Mobile Legends khususnya di asia menjadikan fenomena ini sebagai ruang bisnis untuk menghasilkan keuntungnya yang besar. Dalam penelitian ini, peneliti merekomendasikan algoritma pembelajaran mesin yang baik untuk memprediksi hasil pertandingan Mobile Legends. Dari 600 data riwayat pertandingan yang dianalisis, penelitian ini merekomendasikan algoritma Artificial Neural Network (ANN) dan Random Forest (RF) sebagai algoritma yang tepat untuk memprediksi hasil pertandingan. Hasil prediksi dari masing-masing algoritma dapat mencapai 82% dan akurasi 80%. Temuan ini dapat membantu tim analisis E-sports membangun strategi pertandingan mereka. Kata kunci: artificial neural network; machine learning; mobile legend; prediksi; random forest
Maimai Chart Generation Model Based on Machine Learning Algorithms

Chart generation for rhythm games is a demanding task that requires specialized design knowledge. In the past, there were several models proposed to generate charts by AI for different rhythm games. However, no full model has yet been designed for Maimai DX. In this paper, the author presents a model with high modularity. The main research approach is based on prior models and fits existing algorithms into the model presented by the author. The main purpose of this paper is to propose a possible chart generation model for Maimai DX and to propose improvements for future iterations. The model is designed by blocks, and each block is composed of specific goals and algorithms. The design is characterized by a high degree of modularity in the model, which provides space for future iterations because parts can be easily replaced.
Comprehensive Analysis for Intelligent Recommendation on Mobile Applications

With the development of mobile devices and mobile apps, corresponding app recommendation analysis has received increasing focus in recent years. Such recommendation analysis covers aims including app evaluation, API-based app development, customer investigation, app security, etc. Meanwhile, various types of recommendation techniques are exploited in the app recommendation analysis, which continually improves the development of this direction. However, there is still a lack of a systematical study providing an overall development picture for these app recommendation efforts. Thus, it faces an obstacle for related researchers following this direction of work, and correspondingly is not conducive to the future development. To overcome the problem, in this paper, we take the first step to systematically investigate this direction of efforts. To this end, we summary the main works and techniques used in more than 35 important works in this direction. To better understand the development routines, we have analyzed the characteristics of these works from two perspectives, i.e., technology and research scenario. We have obtained some interesting conclusions within this research direction, and put forward some work suggestions according to the overall research.
Remover: Region-Based Inpainting Algorithm

The existing method does not seem to be a killer application that combines image segmentation and inpainting to do image processing tasks for ordinary people. Therefore, we propose a region-based inpainting method, namely Remover. Remover is a method that can analyze the content of images, perform automatic image segmentation tasks with or without manual intervention, and inpainting the segmented part to achieve unwanted objects appearing to have been removed from an image without affecting the content of the image. With the help of open-source code and technical support. Remover stands as an Ubuntu desktop application. The code is under development and will be available at https://github.com/WPCJATH/remover soon.
PakParse: Machine Translation from Text to Pakistan Sign Language for Effective Communication with Deaf People

The People around the world use different languages to communicate with each other. But there are many individuals who cant listen or speak. These people use gesture-based language for their communication which is called Sign Language. There is no universal Sign Language in world so it changes region wise. As Sign language cant be written and sign video approach is also expensive (in terms of create, store and manage), thats why sign animation through 3D avatar is best option. Recently Pakistan got its own Sign Language called Pakistan Sign Language (PSL). As a noteworthy population of deaf people live in country, there is no machine translator for PSL which can facilitate deaf in their communication and education. This work proposed a machine translator for Pakistan Sign Language called PakParse, which takes text (English &amp; Urdu) as input, and animate corresponding signs by 3D avatar.
An error based adaptive learning rate stochastic gradient descent algorithm in convolutional neural network

If the learning rate of convolutional neural network (CNN) is set improperly, the efficiency and accuracy of the algorithm will be greatly affected. To solve this problem, a learning rate adaptive algorithm is proposed to improve the traditional SGD: based on parameter prediction, the historical training error is used to update the learning rate. Under the condition of given initial learning rate, experiments on classical data sets prove the effectiveness of the above algorithms, and the adaptive learning rate stochastic gradient descent algorithm can keep the convergence of the network. Training accuracy is relatively stable; Shorter training time; And improve the learning accuracy.
Blockchain Technology-based Construction Project Management System --A Case from Xiongan construction funds management blockchain system

Due to the large amount of funds involved, the large number of participants, and the complicated projects in the construction industry, it is difficult to improve work efficiency. The block chain technology, by which the data cannot be tampered, is decentralized, and intelligence contracts can be applied, so it provides a new way for the construction project management. This article analyzes the current situation of construction project management, points out the current problems, and discusses the application of blockchain technology in the management of construction projects. Finally, it takes the construction fund management blockchain system of Xiong'an New Area in China as an example, to discuss the application prospect of block chain technology in construction project management and the problems that remain to be solved.
A Novel Method for Text Classification Dealing with Local Data Structures and High Data Dimensionality

Text categorization involves training models and making predictions over high-dimensional feature space. With the exponential growth on the amount of text resources on the Internet, the demand and difficulty of classifying digital text documents increases over the past decades. k nearest neighbors (kNN) has been proved to possess satisfying predictive power on text classification problems. However, kNN is sensitive to local data structures and its time cost is proportional to the product of the training set size and the feature space dimensionality. This paper proposes a novel text classification method called PCA pre-processed local correlation vector kNN (PCA-Local-CorVec-kNN) that applies PCA and kNN consecutively to the text datasets and introduces local correlation vectors to the sets of nearest neighbors produced by kNN. The proposed method has lower time cost than conventional kNN because of using PCA and is robust to local data structures since correlation vectors are introduced. Problems such as imbalanced datasets, choosing different k values for different samples, weighted voting are also tackled by the proposed method.
XGBoost-Based Human Activity Recognition Algorithm using Wearable Smart Devices

With the popularity of wearable smart devices, human activity recognition (HAR) based on smart sensors has been widely applied in daily life and medical health fields. In order to balance the accuracy of HAR and the complexity of the algorithm, this paper proposes an HAR algorithm based on the extreme gradient boosting (XGBoost) method. The original data collected by sensors contains noise, thus denoising process is firstly performed. Then multi-dimensional features are extracted from the data because of the limited dimensional features, which cannot be directly utilized in the training process. After that, principal component analysis (PCA) is used to reduce the dimensionality of the data in order to alleviate the input complexity of the training model. Finally, the human activity is recognized using the XGBoost method, and the ultimate goal is to obtain the tradeoff between speed and accuracy of the HAR algorithm.
Review on 3D printers

In this paper of the report, it is all the different research in the that has been done to under-stand more about the subject of 3D printers and the health sector. In this paper all the differ-ent research that was done was information that is very closely related to subjects previously stated, although these papers are very professional and informative the focus of this part of the paper is to better show all the different gaps in the information and what it could be miss-ing that could possibly be showed in this paper that they have missed out on.
Hardware oriented bilateral filter algorithm and architecture survey

Images and videos are often interfered with and affected by various noises. To filter out noise, researchers have proposed many filtering algorithms. bilateral filtering is a nonlinear filtering technique that can retain detailed information such as image edges well while denoising. However, it is a difficult task to implement fast and high-precision bilateral filtering algorithms in hardware platforms. In this paper, for the optimization of bilateral filtering algorithms, we analyze the gradient bilateral filtering and the piecewise approximate bilateral filtering algorithm that can be implemented in hardware, respectively. Then, we analyze and compare the implementation and optimization of bilateral filtering algorithms on FPGA and VLSI hardware architectures, and finally, make suggestions for choosing the appropriate bilateral filtering algorithms and hardware architectures for different purposes.
Research on the Applications of Neural Network Algorithms in Deep Hedging

Under market completeness assumptions, hedging a portfolio of derivatives is straightforward. In view of friction, transaction costs, liquidity and other factors, a framework is presented to extend the pricing and hedging with the hedging strategy treated as a neural network. We study the deep hedging model under incomplete market constraints such as frictions, traction cost, permanent impacts on the market and illiquidity. We discuss the limitations of certain models concerning the applications in deep hedging with constraints. After which, we analyse the advantages of different models and their joint models and find that the hedging strategy is close to the Black-Scholes delta hedging strategy. An example is also given when training after designing two hedging models. The Black-Scholes delta hedging is indeed approximated by unsupervised learning.