Reviewerly/exHarmony huggingface dataset:
≪釋迦如來十地修行記≫ 부사 연구

Seokgayeoraesipjisuhaenggi was written by a Buddhist monk during the Goryeo Dynasty in Korea. This literature is typical of Early Modern Chinese, and it was written during the Yuan Dynasty of China. Until now, there have been several editions of this, but here, the Nakeunbon edition has been studied as the main material. According to research so far, it was written in 1328. In terms of overall style, grammar, and vocabulary, this literature reflects the language of the Song & Yuan Dynasty.This study focused on adverbs in this literature, which were classified into eight subcategories based on some sort of criterion. These eight subcategories are ‘time adverbs’, ‘range adverbs’, ‘additional adverbs’, ‘negative adverbs’, ‘connection adverbs’, ‘degree adverbs’, ‘modality adverbs’, and ‘state/means adverbs’. Each subcategory can be divided into more detailed categories. Adverbs in each subcategory consist of ancient adverbs and Early Modern adverbs. Since this work is centered on the literary style, there are many ancient adverbs and a high percentage of appearances. Nevertheless, there are still many adverbs of Early Modern times, especially adverbs that represent the typical form of adverbs in Early Modern times. There are many one-syllable adverbs that reflect ancient times, but many two-syllable adverbs also appear. Based on all of this, we are confident that this literature is clearly a reflection of the language of the Song & Yuan Dynasty.
일제의 탄압과 박해에 대한 한국 초기 침례교의 저항 운동 고찰

The Church of Christ in Korea, which focused on individual salvation and evangelical missionary work, launched a determined resistance movement and protested against martyrdom in the face of a crisis to protect the church and faith due to its policy of extermination of the Korean people. The resistance of the Church of Christ in Korea was different from that of others. It resisted substantially and specifically(Dynamic) to protect the truth; however, the legacy of this history of resistance has not been properly identified due to the lack of evidentiary document, and proper understanding and evaluation of orally circulating evidence have not been made. The Korea Baptist Convention should rediscover the spirit of the resistance movement, which is in line with identity of the Church of Christ in Korea, which is a historical legacy. The Korean Baptist should have a historical awareness of the Church of Christ in Korea to inherit their courage, dedication, and sacrifice.
Application of Machine Learning Algorithms to build a risk score for Pancreatic Cancer using high-throughput epidemiological risk factors

Cancer is one of the most challenging diseases that medical field is facing nowadays. Its incidence numbers are continuously increasing, and they are expected to keep on doing it for the next decades. Pancreatic Cancer is one of the most enigmatic among all the known cancer types. Even though the incidence numbers for PC are not so high as the ones for other diseases, its death ratio is astonishing. Life expectancy for people diagnosed with pancreatic cancer is less than six months. These numbers set up a difficult research environment where the characteristics of a risk population have not been, yet property identified, and where there is a lack of epidemiological information that makes further investigation in early detection very problematic. For the last decades, Artificial Intelligence has been demonstrating its benefits when applied to medical researches, since it can outperform human ability to identify trends and patterns inside huge datasets. In this work, I propose a novel and robust approach to identify the characteristic of a risk population in pancreatic cancer data that has been provided by surveys and researches performed in the whole Europe. This kind of data presents noise, bias and missing values that usually straiten the capabilities of the AI methods. The proposed system uses an ensemble of techniques that brings the ability to first recover the dataset and to later identify the most informative features that can be used to determine the characteristics of a risk population, to build a risk score for the epidemiological factors of Pancreatic Cancer.
Adaptive Double Suppressed Fuzzy C-means Clustering Image Segmentation Algorithm Based on Regional Information Entropy and Fuzzy Partition

Aiming at the pixel misclassification and poor convergence performance of the suppressed fuzzy C-means clustering algorithm in image segmentation, an adaptive double suppressed fuzzy C-means clustering image segmentation algorithm based on regional information entropy and fuzzy partition is proposed. Firstly, the regional information entropy of each region is calculated by dividing and judging the region to which the pixel belongs, and the number of initial clusters is redetermined according to the actual needs; Secondly, the regional information entropy is used to construct the correction factor, and the membership matrix of different regions is first suppressed by the correction factor; Finally, the fuzzy partition matrix is combined with the distribution characteristics of the data itself to construct the adaptive selection formula of the suppression factor, and realize the second suppression of the membership matrix. The experimental results show that the proposed algorithm, compared with the related algorithms, can improve the misclassification of pixel and the convergence performance.
A Module for Industrial Safety Inspection Planning Based on Self-organization

The paper considers the application of the principles of self-organization for the automation of the business process of industrial safety inspection (ISI). Self-organization refers to the process of ordering elements (components) in an information system due to internal factors, without specific external influence. Self-organization is parametric and structural in nature. The architecture of the system as a whole and the main aspects of the main module, namely, scheduler, which provides self-organization of an open multicomponent information system of the ISI, are described. An ontological model of the object of expertise, the task, the method, and the operation that implements it, as the basis of self-organization, is proposed. The model and algorithms for implementing the scheduler are detailed. In particular, the algorithms of the main operations are described: the formation of the task description, the methodology for solving the problem, and the “intelligent” task execution. It also lists the principles of formation and describes the main local rules of the knowledge base of the scheduler, which are responsible for describing the methodology, the decision process, the coordination of expert opinions, and self-learning. A conceptual description of the implementation of the scheduler based on the components of the software platform is given. Some results of application of the considered approach for the problem of technical diagnostics of ISI are given: fragments of the generated software, forms of the user interface demonstrating the description of the object of expertise, local rules, methods and results of self-organization.
Hybridization of Metaheuristic and Population-Based Algorithms with Neural Network Learning for Function Approximation

This paper attempts to improve the learning representation of radial basis function neural network (RBFNN) through metaheuristic algorithm (MHA) and evolutionary algorithm (EA). Next, the ant colony optimization (ACO)-based and genetic algorithm (GA)-based approaches are employed to train RBFNN. The proposed hybridization of ACO-based and GA-based approaches (HAG) algorithm incorporates the complementarity of exploration and exploitation abilities to reach resolution optimization. The property of population diversity has higher chance to search the global optimal instead of being restricted to local optimal extremely in two benchmark problems. The experimental results have shown that ACO-based and GA-based approaches can be integrated intelligently and develop into a hybrid algorithm which aims for receiving the best precise learning expression among relevant algorithms in this paper. Additionally, method assessment results for two benchmark continuous test function experiments and show that the proposed HAG algorithm outperforms relevant algorithms in term of preciseness for learning of function approximation.
An Asymptotic Analysis of Minibatch-Based Momentum Methods for Linear  Regression Models

Momentum methods have been shown to accelerate the convergence of the standard gradient descent algorithm in practice and theory. In particular, the minibatch-based gradient descent methods with momentum (MGDM) are widely used to solve large-scale optimization problems with massive datasets. Despite the success of the MGDM methods in practice, their theoretical properties are still underexplored. To this end, we investigate the theoretical properties of MGDM methods based on the linear regression models. We first study the numerical convergence properties of the MGDM algorithm and further provide the theoretically optimal tuning parameters specification to achieve faster convergence rate. In addition, we explore the relationship between the statistical properties of the resulting MGDM estimator and the tuning parameters. Based on these theoretical findings, we give the conditions for the resulting estimator to achieve the optimal statistical efficiency. Finally, extensive numerical experiments are conducted to verify our theoretical results.
The COVID-19 Outbreak

The coronavirus disease (nCoV-2019) pandemic has brought about significant disturbance to people and businesses globally. It has exposed the lapses in global healthcare and has raised serious questions around modern science and its ability. COVID-19, which has been declared a global pandemic by the World Health Organization (WHO), has left several challenges to the twenty-first century, raising serious doubts around the technological, engineering, and scientific advances made through the collective efforts of human civilization. The virus has the potential to transmit and spread across huge masses of people at an alarmingly high rate. Therefore, quarantine and lockdown have been mandated all across the world, to prevent the virus from being disseminated. Unfortunately, this decision to alleviate the situation also had repercussions. Because of the lockdown in the entire world, businesses have either shut down or have come to an untimely halt. Many employees have been laid off from organizations, who themselves have suffered to generate the revenue in parity with what they used to prior to the outbreak of the virus. Small vendors and small businesses like barbers, vegetable sellers, etc. and daily earners are in an implacable position as they have lost their means to daily bread and butter. Many workers who migrated to metropolitan cities are compelled to travel back to their hometown, which also proved to be a daunting task as a result of the lockdown and temporary termination of travel services. The world has faced major economic loss. Methods to overcome this adverse situation are extensively explored. One of the most significant aspects of the large businesses in the modern era is the supply chain, which is the entire network that enables the product right from its onset to reach the final buyer. Blockchain technology provides an efficient and secure method for supply chain management in industry. This paper presents a secure blockchain-based model for the supply chain orchestration. The proposed model is based on a blockchain ecosystem framework where all stakeholders can join and augment business activities. Immutability, transparency, and automation are the biggest benefits of blockchain.
Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation  for Few-shot Learning

The ability to continuously expand knowledge over time and utilize it to rapidly generalize to new tasks is a key feature of human linguistic intelligence. Existing models that pursue rapid generalization to new tasks (e.g., few-shot learning methods), however, are mostly trained in a single shot on fixed datasets, unable to dynamically expand their knowledge; while continual learning algorithms are not specifically designed for rapid generalization. We present a new learning setup, Continual Learning of Few-Shot Learners (CLIF), to address the challenges of both learning settings in a unified setup. CLIF assumes a model learns from a sequence of diverse NLP tasks arriving sequentially, accumulating knowledge for improved generalization to new tasks, while also retaining performance on the tasks learned earlier. We examine how the generalization ability is affected in the continual learning setup, evaluate a number of continual learning algorithms, and propose a novel regularized adapter generation approach. We find that catastrophic forgetting affects generalization ability to a less degree than performance on seen tasks; while continual learning algorithms can still bring considerable benefit to the generalization ability.
PRODUKSI MAGOT MENGGUNAKAN MANUR AYAM SEBAGAI PAKAN UNGGAS

The purpose of this study was to examine how the production of Maggot BSF (Black Solder Faly) in chicken manure media. This research was carried out in the BSF maggot cage in Jurit Village, East Lombok, in August-December 2020, the experiment consisted of Chicken Manure which was the main feed for maggots. Then, its growth was observed. The results of this study indicate that the growth of maggots (BSF) is good with chicken manure/manure feed, so that farmers can make good use of the chicken manure. In addition to the sufficient availability of chicken manure, it also does not compete with human needs, so that people in Jurit village are very easy. get chicken manure from local cages, because of the many studies that we have tried the most available and do not need to be purchased for magot feed, namely chicken manure, so that magot/BSF can grow well. The conclusion of this study is the conclusion of this study that the production of BSF maggot using Chicken Manure is good, so that farmers no longer need to look for sources of maggot feed, such as fruit waste, vegetable waste and other waste. take advantage of the manure/menus of the chickens they raise, thereby reducing the expenditure of purchasing feed for both animal feed and magot feed itself.Keywords: Magot BSF, Chicken Menu, Production, Feed
Bacteriophage MS2를 이용한 소독제 효력시험 확립에 관한 연구

In virucidal efficacy testing, the chemical inactivation cannot be determined for all viruses due to the difficulties or the inability to culture sufficiently or the risk of exposure to the viruses. Therefore, disinfectants against these viruses could be evaluated by different methods and surrogate viruses are used as alternative. In this study we developed a method for efficacy testing of veterinary disinfectants using one of the candidate surrogate viruses, bacteriophage MS2, as part of the research on the selection of surrogate viruses for efficiency of efficacy testing of veterinary disinfectants. This method is based on the Animal and Plant Quarantine Agency (APQA) guidelines for efficacy testing of veterinary disinfectants. Bacteriophage and disinfectant are reacted in suspension in accordance with the APQA guidelines and then a newly established double agar layer method is applied for the efficacy test. The double agar layer method is summarized as follows: 1) The bottom agar with 1.5% agar is boiled and cooled before poured into petri dishes at volume of 20 mL, and dried under bio-logical safety cabinet. 2) The top agar with 0.7% agar is boiled and kept at 50℃ before E. coli culture was seeded. 3) The serially diluted bacteriophage MS2-disinfectant mixtures 0.05 mL and E. coli host 0.01 mL (OD600 0.2~0.3) are mixed with 5 mL of top agar and incubate them at 50℃ for 5 min for reaction. 4) The resulting mixture is poured over top of a bottom agar plate and rocked sufficiently to ensure that the top agar covers the entire surface of the bottom agar. 5) The double agar layer is then placed under biological safety cabinet to allow the agar layer to solidify and subsequently incubated at 37℃ for 24 hr. 6) Following incubation, the plates may be inspected for plaques and record results.
3·1운동기 인천지역 시위의 양상과 특징

The objective of this article is to examine factual details and characteristics of the March 1st movement in Incheon. The protests that began in March 1st 1919 was a massive country-wide movement that broke out in protest of the Japanese rule and its policy. In order to understand the true nature of the March 1st movement, a comprehensive review of individual areas and the movements they showed is duly required. The region examined in this article is no other than Incheon. Today, Incheon is a crucial hub in important activities, a gateway to Seoul and also a focal point in international traffic connecting countless cities and regions worldwide. It was also a region that was considered very important in 1876 by Japan and other countries when it was opened up for the first time to the outer world. It was the first Korean city where railroads were constructed, and where foreign missionaries were very much active. Attempted in this article is a statistical survey of all the activities demonstrated within Incheon-bu, Bucheon-gun and Gang’hwa-gun areas (local units that existed back in 1919, which now compose the Incheon Metropolitan City area), based upon the established by the National Institute of Korean History. The entire movement in this region is analyzed by dates, people and locations. Incheon was where people could experience the Japanese colonial policy firsthand, and easily feel the authorities’ intention to reinforce their colonial ruling. It was also a region where the influence of Christianity was quite strong. The spreading of Christian beliefs was apparently hugely instrumental in the protests’ spreading. Incheon also witnessed the foundation of many schools, and it was no coincidence that it was the students’ protest that started it all in this region.
An Implementation of the “Guess Who?” Game Using CLIP

CLIP (Contrastive Language-Image Pretraining) is an efficient method for learning computer vision tasks from natural language supervision that has powered a recent breakthrough in deep learning due to its zero-shot transfer capabilities. By training from image-text pairs available on the internet, the CLIP model transfers non-trivially to most tasks without the need for any data set specific training. In this work, we use CLIP to implement the engine of the popular game “Guess who?”, so that the player interacts with the game using natural language prompts and CLIP automatically decides whether an image in the game board fulfills that prompt or not. We study the performance of this approach by benchmarking on different ways of prompting the questions to CLIP, and show the limitations of its zero-shot capabilites.
난민법상 강제송환금지 규정에 대한 소고

The nation has repeatedly revised the current Refugee Act, enacted on February 10, 2012, implemented on July 1, 2013, and has sought to find social and national issues for refugees that have been discussed or discussed so far, as well as improvement in social realities and norms on some refugee laws. First of all, the Enforcement Decree of the Act was enacted on June 12, 2013 (July 1, 2013) and the Enforcement Rules of the same Act (the Act was enacted on June 28, 2013 (July 1, 2013). In general, the Immigration Act consists of the Basic Act on Korean and Foreign Affairs, the Employment of Foreign Workers Act, the Multicultural Family Support Act, the Marriage Arbitration Act, the Refugee Act, the Immigration Control Act and the Nationality Act. Among these immigration laws, it is the Refugee Act that has recently been legislated and enforced. The nation has so far seen a rise in the influx of immigrants of various types, including foreign workers, students studying abroad and marriage visas. Similarly, there were not so many applicants for refugees before 1994, and until 2010, there were not many applicants for refugee status, nor were there many administrative or administrative resources required for such work. The pattern has changed since 2010, when their numbers have been on the rise considerably, especially since 2015. Furthermore, the number of applicants has increased to such a degree that the number of professional administrators who examine refugee applications is far short. However, the public is concerned about the possibility that even serious risk factors in the nations stability and social order could be latent. As such, the nation should strive to secure national security and maintain social order by improving the legal policy or system on some problematic refugees, and gain public trust through efficient national refugee policies. It is also a normative reality that it has to be followed either on the domestic and international legal systems for applicants for refugees or on a humanitarian level. Under the constitutional value order, the nation should seek a harmonized legal and criminal alternative to international laws, such as the Refugee Convention, or Koreas current refugee law. Considering the foreign policy and refugee policies by international politics and economy, the government should improve and supplement the lack of refugee law in accordance with domestic political and economic situations. In this regard, this research paper looked at the social perception and problems of refugees, and looked at them from a practical perspective and the social realities of refugee law. In addition, even with regard to the provisions of the current ban on forced repatriation under the Refugee Act, there is a need for forced repatriation out of the country for maintaining public order and ensuring national security pursuant to Article 33 paragraph 2 of the Refugee Convention, and there is a need to clarify the scope of the reason for repatriation. After all, the nation and society will have to pursue refugee policies, seeking ways to resolve social problems and normative values for refugees in harmony.
Levantamento bibliométrico da prevalência da ansiedade e depressão por meio do Covid-19

Objective: To identify the prevalence and incidence of depressive symptoms and anxiety disorder caused by the Covid-19 pandemic. Methods: A systematic review was carried out through a retrospective study. As for the search strategy, a search was performed in the PubMed database in July 2021, using the following descriptors: with covid 19”, depression, anxiety, incidence, prevalence, no: “Review”, “qualitative studies”, “theoretical study”, “qualitative study”. Results: Based on the searches performed, 55 articles were found, 45 articles were excluded and 10 articles were selected for systematic evaluation. The articles were presented in reverse chronological order, all studies were carried out in 2021. Final considerations: Greater dissemination of the mental health protection measures and practices recommended by WHO is considered necessary, together with society and professional mental health associations. Active collaboration between the health entities that issue these standards and the scientific institutions that must support the defined guidelines to effectively benefit patients in daily care is essential.