Awareness Activation of Dance Copyrights and Research of Effectiveness Plans (무용의 저작권 인식 활성화와 실효성 방안 연구)
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- v.2
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- pp.1-38
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- 2017
Dance, as an art which expresses thoughts and emotions by movement human, is included in work that its copyright has to be protected, choreographers who are creators and dancers who are performing can exercise their rights included in copyright laws. However, artists who work in the dancing scene have lack of awareness about copyrights and the application level is low. The purpose of this thesis is to look into the current status and issues about dance copyright and to discuss activation plans and effectiveness plans for dance copyrights. The main point is to check into the level of awareness for dance copyrights with choreographers, dancers and students majoring in dance who are in charge of the art of dancing, to present issues about the necessity of the dance copyrights protection plans by analyzing interviews-in-depth and to prepare the dance copyrights protection plans which are concretely realistic. For the research methods, first, I looked into ideas and contents about copyrights through a document research and then, wanted to prepare theoretical background by reviewing actual cases of performing art copyrights related to dance. Next, I carried out surveys about awareness of copyrights with students majoring in dance, choreographers and dancers then carried out analysis of actual proof. Also, I chose three famous dancers who are actively performing in the current dancing scene and did interviews-in-depth about dance copyrights then carried out a recording analysis. I tried to complement the analysis by discussing deeper which I couldn't deal with in the previous surveys and to contemplate awareness activation of dance copyrights and plans. As a result of the research, the level of the awareness about dance copyrights through age, major, education and career was very low. The level of awareness was almost same compared to the previous research 10 years ago. 'Music', which can be an element of copyright issue in dance, was the highest in rate, and dance was recognized as an art which is combined with various elements as a combination work. The way of protection for works of choreography and performance only used data preservation and contracts and didn't register copyrights or record in dace notation. Majority of responders answered that they couldn't have any education about copyrights while they were recognizing the necessity of education and management for copyrights. The analysis of interviews-in-depth was also matched to the result of the previous surveys and a deeper discussion about the status of dance copyrights and issues was carried out. The plans of effectiveness for dance copyrights through the result of previous research are as followings. First, an advanced education is necessary above all to increase the awareness and application of copyrights in dancing scene. Long-term education like study curriculums and short-term education like special courses and seminars should be combined, and education about copyrights for dance groups, choreographers, dancers and students majoring in dance should keep on going. Second, revision of performing art works is necessary for the activation of dance copyrights, and establishing a dance copyright association to manage copyrights systematically and training dance copyright experts are necessary as well. Third, as the way of copyright protection for choreographers and dancers, an establishment for relation gain and loss about copyrights is necessary when creating dance works and performing, and registration of dance works should be activated. Also, the dancing scene should sign contracts for choreography and performance and this contract culture should be activated, and it should systematically preserve and manage choreography and performance records through basic ways. Hereby, it is considered to prepare a foundation to foster the awareness of dance copyrights and activate dance copyrights.
This Study involved the development of a survey form and the collection of data in an effort-to provide information which can be used in the improvement of nursing curricula. The data examined were the kinds courses currently being taught in the curricula of nursing education institutions throughout Korea, credits required for course completion, and year in-which courses are taken. For the purposes of this study, curricula were classified into college, nursing school and vocational school categories. Courses were directed into the 3 major categories of general education courses, supporting science courses and professional education course, and further subdirector as. follows: 1) General education (following the classification of Philip H. phoenix): a) Symbolics, b) Empirics, c) Aesthetics. 4) Synthetics, e) Ethics, f) Synoptic. 2) Supporting science: a) physical science, b) biological science, c) social science, d) behavioral science, e) Health science, f) Educations 3) Professional Education; a) basic courses, b) courses in each of the respective fields of nursing. Ⅰ. General Education aimed at developing the individual as a person and as a member of society is relatively strong in college curricula compared with the other two. a) Courses included in the category of symbolics included Korean language, English, German. Chines. Mathematics. Statics: Economics and Computer most college curricula included 20 credits. of courses in this sub-category, while nursing schools required 12 credits and vocational school 10 units. English ordinarily receives particularly heavy emphasis. b) Research methodology, Domestic affair and women & courtney was included under the category of empirics in the college curricula, nursing and vocational school do not offer this at all. c) Courses classified under aesthetics were physical education, drill, music, recreation and fine arts. Most college curricula had 4 credits in these areas, nursing school provided for 2 credits, and most vocational schools offered 10 units. d) Synoptic included leadership, interpersonal relationship, and communications, Most schools did not offer courses of this nature. e) The category of ethics included citizenship. 2 credits are provided in college curricula, while vocational schools require 4 units. Nursing schools do not offer these courses. f) Courses included under synoptic were Korean history, cultural history, philosophy, Logics, and religion. Most college curricular 5 credits in these areas, nursing schools 4 credits. and vocational schools 2 units. g) Only physical education was given every Year in college curricula and only English was given in nursing schools and vocational schools in every of the curriculum. Most of the other courses were given during the first year of the curriculum. Ⅱ. Supporting science courses are fundamental to the practice and application of nursing theory. a) Physical science course include physics, chemistry and natural science. most colleges and nursing schools provided for 2 credits of physical science courses in their curricula, while most vocational schools did not offer t me. b) Courses included under biological science were anatomy, physiologic, biology and biochemistry. Most college curricula provided for 15 credits of biological science, nursing schools for the most part provided for 11 credits, and most vocational schools provided for 8 units. c) Courses included under social science were sociology and anthropology. Most colleges provided for 1 credit in courses of this category, which most nursing schools provided for 2 creates Most vocational school did not provide courses of this type. d) Courses included under behavioral science were general and clinical psychology, developmental psychology. mental hygiene and guidance. Most schools did not provide for these courses. e) Courses included under health science included pharmacy and pharmacology, microbiology, pathology, nutrition and dietetics, parasitology, and Chinese medicine. Most college curricula provided for 11 credits, while most nursing schools provide for 12 credits, most part provided 20 units of medical courses. f) Courses included under education included educational psychology, principles of education, philosophy of education, history of education, social education, educational evaluation, educational curricula, class management, guidance techniques and school & community. Host college softer 3 credits in courses in this category, while nursing schools provide 8 credits and vocational schools provide for 6 units, 50% of the colleges prepare these students to qualify as regular teachers of the second level, while 91% of the nursing schools and 60% of the vocational schools prepare their of the vocational schools prepare their students to qualify as school nurse. g) The majority of colleges start supporting science courses in the first year and complete them by the second year. Nursing schools and vocational schools usually complete them in the first year. Ⅲ. Professional Education courses are designed to develop professional nursing knowledge, attitudes and skills in the students. a) Basic courses include social nursing, nursing ethics, history of nursing professional control, nursing administration, social medicine, social welfare, introductory nursing, advanced nursing, medical regulations, efficient nursing, nursing english and basic nursing, College curricula devoted 13 credits to these subjects, nursing schools 14 credits, and vocational schools 26 units indicating a severe difference in the scope of education provided. b) There was noticeable tendency for the colleges to take a unified approach to the branches of nursing. 60% of the schools had courses in public health nursing, 80% in pediatric nursing, 60% in obstetric nursing, 90% in psychiatric nursing and 80% in medical-surgical nursing. The greatest number of schools provided 48 crudites in all of these fields combined. in most of the nursing schools, 52 credits were provided for courses divided according to disease. in the vocational schools, unified courses are provided in public health nursing, child nursing, maternal nursing, psychiatric nursing and adult nursing. In addition, one unit is provided for one hour a week of practice. The total number of units provided in the greatest number of vocational schools is thus Ⅲ units double the number provided in nursing schools and colleges. c) In th leges, the second year is devoted mainly to basic nursing courses, while the third and fourth years are used for advanced nursing courses. In nursing schools and vocational schools, the first year deals primarily with basic nursing and the second and third years are used to cover advanced nursing courses. The study yielded the following conclusions. 1. Instructional goals should be established for each courses in line with the idea of nursing, and curriculum improvements should be made accordingly. 2. Course that fall under the synthetics category should be strengthened and ways should be sought to develop the ability to cooperate with those who work for human welfare and health. 3. The ability to solve problems on the basis of scientific principles and knowledge and understanding of man society should be fostered through a strengthening of courses dealing with physical sciences, social sciences and behavioral sciences and redistribution of courses emphasizing biological and health sciences. 4. There should be more balanced curricula with less emphasis on courses in the major There is a need to establish courses necessary for the individual nurse by doing away with courses centered around specific diseases and combining them in unified courses. In addition it is possible to develop skill in dealing with people by using the social setting in comprehensive training. The most efficient ratio of the study experience should be studied to provide more effective, interesting education Elective course should be initiated to insure a man flexible, responsive educational program. 5. The curriculum stipulated in the education law should be examined.
Over the years Korean health care system has improved in delivery of quality care to the general population for many areas of the health problems. The system is now being recognized in the world as the most cost effective one. It is covered by the uniform national health insurance policy for which most people in Korea are mandatory policy holders. Genetic counseling service, however, which is well recognized as an integral part of clinical genetics service deals with diagnosis and management of genetic condition as well as genetic information presentation and family support, is yet to be delivered in comprehensive way for the patients and families in need. Two major obstacles in providing genetic counseling service in korean health care system are identified; One is the lack of recognition for the need for genetic counseling service as necessary service by the national health insurance. Genetic counseling consumes a significant time in delivery and the current very low-fee schedule for physician service makes it very difficult to provide meaningful service. Second is the critical shortage of qualified professionals in the field of medical genetics and genetic counseling who can provide the service of genetic counseling in clinical setting. However, recognition and understanding of the fact that the scope and role of genetic counseling is expanding in post genomic era of personalized medicine for delivery of quality health care, will lead to the efforts to overcome obstacles in providing genetic counseling service in korean health care system. Only concerted efforts from health care policy makers of government on clinical genetics service and genetic counseling for establishing adequate reimbursement coverage and professional communities for developing educational program and certification process for professional genetic counselors, are necessary for the delivery of much needed clinical genetic counseling service in Korea.
To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.
Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.
In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.
Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.
'Sukchunjeahdo' illustration-book, which was left by Han, Pil-gyo(韓弼敎 : 1807~1878)in the late Joseon Dynasty, includes pictorial record paintings containing government offices, Eupchi, and Feng Shui condition drawn by Gyehwa(界畵) method Sabangjeondomyobeop(四方顚倒描法) and is the rare historical material that help to understand spatial structure and landscape characteristics. Youngyuhyun(永柔縣) and Sincheongun(信川郡) town, the case sites of this study, show Feng Shui foundation structure and placement rules of government offices in the Joseon Period are applied such as 3Dan 1Myo(三壇一廟 : Sajikdan, Yeodan, Seonghwangdan, Hyanggyo), 3Mun 3Jo(三門三朝 : Oeah, Dongheon, Naeah) and Jeonjohuchim(前朝後寢) etc. by setting the upper and lower hierarchy of the north south central axis. The circulation system is the pattern that roads are segmented around the marketplace of the entrance of the town and the structure is that heading to the north along the internal way leads to the government office and going out to the main street leads to the major city. Baesanimsu(背山臨水 : Mountain in backward and water in front) foundation, back hill pine forest, intentionally created low mountains and town forest etc. showed landscape aesthetics well suited for the environmental comfort condition such as microclimate control, natural disaster prevention, psychological stability reflecting color constancy principle etc. and tower pavilions were built throughout the scenic spot, reflecting life philosophy and thoughts of contemporaries such as physical and mental discipline, satisfied at the reality of poverty, returning to nature etc. For government office landscape, shielding and buffer planting, landscape planting etc. were considered around Gaeksa(客舍), Dongheon(東軒), Naeah(內衙) backyard and deciduous tree s and flowering trees were cultivated as main species and in case of Gaeksa, tiled pavilions and pavilions topped with poke weed in tetragonal pond were introduced to Dongheon and Naeah and separate pavilions were built for the purpose of physical and mental discipline and military training such as archery. Back hill pine tree forest formed back landscape and zelkova, pear trees, willow trees, old pine trees, lotus, flowering trees etc. were cultivated as gardening trees and Feng-Shui forest with willow trees as its main species was created for landscape and practical purposes. On the other hand, various cultural landscape elements etc. were introduced such as pavilions
Aspect Based Sentiment Analysis (ABSA), which analyzes sentiment based on aspects that appear in the text, is drawing attention because it can be used in various business industries. ABSA is a study that analyzes sentiment by aspects for multiple aspects that a text has. It is being studied in various forms depending on the purpose, such as analyzing all targets or just aspects and sentiments. Here, the aspect refers to the property of a target, and the target refers to the text that causes the sentiment. For example, for restaurant reviews, you could set the aspect into food taste, food price, quality of service, mood of the restaurant, etc. Also, if there is a review that says, "The pasta was delicious, but the salad was not," the words "steak" and "salad," which are directly mentioned in the sentence, become the "target." So far, in ABSA, most studies have analyzed sentiment only based on aspects or targets. However, even with the same aspects or targets, sentiment analysis may be inaccurate. Instances would be when aspects or sentiment are divided or when sentiment exists without a target. For example, sentences like, "Pizza and the salad were good, but the steak was disappointing." Although the aspect of this sentence is limited to "food," conflicting sentiments coexist. In addition, in the case of sentences such as "Shrimp was delicious, but the price was extravagant," although the target here is "shrimp," there are opposite sentiments coexisting that are dependent on the aspect. Finally, in sentences like "The food arrived too late and is cold now." there is no target (NULL), but it transmits a negative sentiment toward the aspect "service." Like this, failure to consider both aspects and targets - when sentiment or aspect is divided or when sentiment exists without a target - creates a dual dependency problem. To address this problem, this research analyzes sentiment by considering both aspects and targets (Target-Aspect-Sentiment Detection, hereby TASD). This study detected the limitations of existing research in the field of TASD: local contexts are not fully captured, and the number of epochs and batch size dramatically lowers the F1-score. The current model excels in spotting overall context and relations between each word. However, it struggles with phrases in the local context and is relatively slow when learning. Therefore, this study tries to improve the model's performance. To achieve the objective of this research, we additionally used auxiliary loss in aspect-sentiment classification by constructing CNN(Convolutional Neural Network) layers parallel to existing models. If existing models have analyzed aspect-sentiment through BERT encoding, Pooler, and Linear layers, this research added CNN layer-adaptive average pooling to existing models, and learning was progressed by adding additional loss values for aspect-sentiment to existing loss. In other words, when learning, the auxiliary loss, computed through CNN layers, allowed the local context to be captured more fitted. After learning, the model is designed to do aspect-sentiment analysis through the existing method. To evaluate the performance of this model, two datasets, SemEval-2015 task 12 and SemEval-2016 task 5, were used and the f1-score increased compared to the existing models. When the batch was 8 and epoch was 5, the difference was largest between the F1-score of existing models and this study with 29 and 45, respectively. Even when batch and epoch were adjusted, the F1-scores were higher than the existing models. It can be said that even when the batch and epoch numbers were small, they can be learned effectively compared to the existing models. Therefore, it can be useful in situations where resources are limited. Through this study, aspect-based sentiments can be more accurately analyzed. Through various uses in business, such as development or establishing marketing strategies, both consumers and sellers will be able to make efficient decisions. In addition, it is believed that the model can be fully learned and utilized by small businesses, those that do not have much data, given that they use a pre-training model and recorded a relatively high F1-score even with limited resources.
This project was a service-cum-research effort with a quasi-experimental study design to examine the health benefits of an integrated Family Planning (FP)/Maternal & Child health (MCH) Service approach that provides crucial factors missing in the present on-going programs. The specific objectives were: 1) To test the effectiveness of trained nurse/midwives (MW) assigned as change agents in the Health Sub-Center (HSC) to bring about the changes in the eight FP/MCH indicators, namely; (i)FP/MCH contacts between field workers and their clients (ii) the use of effective FP methods, (iii) the inter-birth interval and/or open interval, (iv) prenatal care by medically qualified personnel, (v) medically supervised deliveries, (vi) the rate of induced abortion, (vii) maternal and infant morbidity, and (viii) preinatal & infant mortality. 2) To measure the integrative linkage (contacts) between MW & HSC workers and between HSC and clients. 3) To examine the organizational or administrative factors influencing integrative linkage between health workers. Study design; The above objectives called for quasi-experimental design setting up a study and control area with and without a midwife. An active intervention program (FP/MCH minimum 'package' program) was conducted for a 2 year period from June 1982-July 1984 in Seosan County and 'before and after' surveys were conducted to measure the change. Service input; This study was undertaken by the Soonchunhyang University in collaboration with WHO. After a baseline survery in 1981, trained nurses/midwives were introduced into two health sub-centers in a rural setting (Seosan county) for a 2 year period from 1982 to 1984. A major service input was the establishment of midwifery services in the existing health delivery system with emphasis on nurse/midwife's role as the link between health workers (nurse aids) and village health workers, and the referral of risk patients to the private physician (OBGY specialist). An evaluation survey was made in August 1984 to assess the effectiveness of this alternative integrated approach in the study areas in comparison with the control area which had normal government services. Method of evaluation; a. In this study, the primary objective was first to examine to what extent the FP/MCH package program brought about changes in the pre-determined eight indicators (outcome and impact measures) and the following relationship was first analyzed; b. Nevertheless, this project did not automatically accept the assumption that if two or more activities were integrated, the results would automatically be better than a non-integrated or categorical program. There is a need to assess the 'integration process' itself within the package program. The process of integration was measured in terms of interactive linkages, or the quantity & quality of contacts between workers & clients and among workers. Intergrative linkages were hypothesized to be influenced by organizational factors at the HSC clinic level including HSC goals, sltrurture, authority, leadership style, resources, and personal characteristics of HSC staff. The extent or degree of integration, as measured by the intensity of integrative linkages, was in turn presumed to influence programme performance. Thus as indicated diagrammatically below, organizational factors constituted the independent variables, integration as the intervening variable and programme performance with respect to family planning and health services as the dependent variable: Concerning organizational factors, however, due to the limited number of HSCs (2 in the study area and 3 in the control area), they were studied by participatory observation of an anthropologist who was independent of the project. In this observation, we examined whether the assumed integration process actually occurred or not. If not, what were the constraints in producing an effective integration process. Summary of Findings; A) Program effects and impact 1. Effects on FP use: During this 2 year action period, FP acceptance increased from 58% in 1981 to 78% in 1984 in both the study and control areas. This increase in both areas was mainly due to the new family planning campaign driven by the Government for the same study period. Therefore, there was no increment of FP acceptance rate due to additional input of MW to the on-going FP program. But in the study area, quality aspects of FP were somewhat improved, having a better continuation rate of IUDs & pills and more use of effective Contraceptive methods in comparison with the control area. 2. Effects of use of MCH services: Between the study and control areas, however, there was a significant difference in maternal and child health care. For example, the coverage of prenatal care was increased from 53% for 1981 birth cohort to 75% for 1984 birth cohort in the study area. In the control area, the same increased from 41% (1981) to 65% (1984). It is noteworthy that almost two thirds of the recent birth cohort received prenatal care even in the control area, indicating that there is a growing demand of MCH care as the size of family norm becomes smaller 3. There has been a substantive increase in delivery care by medical professions in the study area, with an annual increase rate of 10% due to midwives input in the study areas. The project had about two times greater effect on postnatal care (68% vs. 33%) at delivery care(45.2% vs. 26.1%). 4. The study area had better reproductive efficiency (wanted pregancies with FP practice & healthy live births survived by one year old) than the control area, especially among women under 30 (14.1% vs. 9.6%). The proportion of women who preferred the 1st trimester for their first prenatal care rose significantly in the study area as compared to the control area (24% vs 13%). B) Effects on Interactive Linkage 1. This project made a contribution in making several useful steps in the direction of service integration, namely; i) The health workers have become familiar with procedures on how to work together with each other (especially with a midwife) in carrying out their work in FP/MCH and, ii) The health workers have gotten a feeling of the usefulness of family health records (statistical integration) in identifying targets in their own work and their usefulness in caring for family health. 2. On the other hand, because of a lack of required organizational factors, complete linkage was not obtained as the project intended. i) In regards to the government health worker's activities in terms of home visiting there was not much difference between the study & control areas though the MW did more home visiting than Government health workers. ii) In assessing the service performance of MW & health workers, the midwives balanced their workload between 40% FP, 40% MCH & 20% other activities (mainly immunization). However,