• Cartoon and Animation Studies
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• s.41
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• pp.455-486
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• 2015

The 3D printing technology, which started from the patent registration in 1986, was a technology that did not attract attention other than from some companies, due to the lack of awareness at the time. However, today, as expiring patents are appearing after the passage of 20 years, the price of 3D printers have decreased to the level of allowing purchase by individuals and the technology is attracting attention from industries, in addition to the general public, such as by naturally accepting 3D and to share 3D data, based on the generalization of online information exchange and improvement of computer performance. The production capability of 3D printers, which is based on digital data enabling digital transmission and revision and supplementation or production manufacturing not requiring molding, may provide a groundbreaking change to the process of manufacturing, and may attain the same effect in the character merchandise sector. Using a 3D printer is becoming a necessity in various figure merchandise productions which are in the forefront of the kidult culture that is recently gaining attention, and when predicting the demand by the industrial sites related to such character merchandise and when considering the more inexpensive price due to the expiration of patents and sharing of technology, expanding opportunities and sectors of employment and cultivating manpower that are able to engage in further creative work seems as a must, by introducing education courses cultivating manpower that can utilize 3D printers at the education field. However, there are limits in the information that can be obtained when seeking to introduce 3D printers in school education. Because the press or information media only mentions general information, such as the growth of the industrial size or prosperous future value of 3D printers, the research level of the academic world also remains at the level of organizing contents in an introductory level, such as by analyzing data on industrial size, analyzing the applicable scope in the industry, or introducing the printing technology. Such lack of information gives rise to problems at the education site. There would be no choice but to incur temporal and opportunity expenses, since the technology would only be able to be used after going through trials and errors, by first introducing the technology without examining the actual information, such as through comparing the strengths and weaknesses. In particular, if an expensive equipment introduced does not suit the features of school education, the loss costs would be significant. This research targeted general users without a technology-related basis, instead of specialists. By comparing the strengths and weaknesses and analyzing the problems and matters requiring notice upon use, pursuant to the representative technologies, instead of merely introducing the 3D printer technology as had been done previously, this research sought to explain the types of features that a 3D printer should have, in particular, when required in education relating to the development of figure merchandise as an optional cultural contents at cartoon-related departments, and sought to provide information that can be of practical help when seeking to provide education using 3D printers in the future. In the main body, the technologies were explained by making a classification based on a new perspective, such as the buttress method, types of materials, two-dimensional printing method, and three-dimensional printing method. The reason for selecting such different classification method was to easily allow mutual comparison of the practical problems upon use. In conclusion, the most suitable 3D printer was selected as the printer in the FDM method, which is comparatively cheap and requires low repair and maintenance cost and low materials expenses, although rather insufficient in the quality of outputs, and a recommendation was made, in addition, to select an entity that is supportive in providing technical support.

• Tuberculosis and Respiratory Diseases
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• v.44 no.4
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• pp.729-741
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• 1997

Background : We have recently reported that airway epithelial cells can produce RANTES and IL-8 in response to the stimulation of tubercle bacilli suggesting a certain role of airway epithelial cells in the pathogenesis of pulmonary tuberculosis. The pathogenesis of tuberculosis is determined by several factors including phagocytosis, immunological response of host, and virulence of tubercle bacilli. Interestingly, there have been reports suggesting that difference in immunological response of host according to the virulence of tubercle bacilli may be related with the pathogenesis of tuberculosis. We, therefore, studied the expressions and productions of RANTES and IL-8 in airway epithelial cells in response to tubercle bacilli(H37Rv, virulent strain and H37Ra, avirulent strain), in order to elucidate the possible pathophysiology of pulmonary tuberculosis. Methods : Peripheral blood monocytes were isolated from normal volunteers. Peripheral blood monocytes (PBM) were stimulated with LPS($10{\mu}g/ml$), H37Rv, or H37Ra($5{\times}10^5$ bacilli/well) along with normal control for 24 hours. A549 cells were stimulated with supernatants of cultured PBM for 24 hours. ELISA kit was used for the measurement of $TNF{\alpha}$ and IL-$1{\beta}$ production in supernatants of cultured PBM and for the measurement of RANTES and IL-8 in supernatants of cultured A549 cells. Northern blot analysis was used for the measurement of RANTES and IL-8 mRNA expression in cultured A549 cells. Results : $TNF{\alpha}$ and IL-$1{\beta}$ productions were increased in cultured PBM stimulated with LPS or tubercle bacilli(H37Rv or H37Ra) compared with the control. There was, however, no difference in $TNF{\alpha}$ and IL-$1{\beta}$ production between cultured PBM stimulated with H37Rv and H37Ra. RANTES and IL-8 expressions and productions were also increased in cultured A549 cells stimulated with LPS or tubercle bacilli compared with the control. RANTES and IL-8 mRNA expressions were significantly increased in cultured A549 cells stimulated with H37Ra-conditioned media(CM) compared with A549 cells stimulated with H37Rv-CM (p<0.05). However, there was no difference in RANTES and IL-8 productions between A549 cells stimulated with H37Rv-CM and H37Ra-CM. Conclusion : Airway epithelial cells can produce the potent chemokines such as RANTES and IL-8, in response to the stimulation of tubercle bacilli. These results suggest that airway epithelial cells may play a certain role in the pathogenesis of pulmonary tuberculosis. However, the role of airway epithelial cells in the pathogenesis of tuberculosis according to the virulence of tubercle bacilli was not clear in this study.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Tuberculosis and Respiratory Diseases
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• v.44 no.1
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• pp.25-43
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• 1997

Introduction : The outcome and incidence of acute respiratory distress syndrome (ARDS) could be variable related to the varied definitions used for ARDS by researchers. The purpose of the national survey was to define the risk factors of ARDS and investigate the prognostic indicies related to mortality of ARDS in Korea according to the definition of ARDS determined by the American-European Concensus Conference on 1992 year. Methods : A Multicenter registry of 48 University or University-affliated hospital and 18 general hospital s equipped with more than 400 patient's beds conducted over 13 months of patients with acute respiratory distress syndrome using the same registry protocol. Results : 1. In the 12 months of the registry, 167 patients were enrolled at the 24 hospitals. 2. The mean age was 56.5 years (${\pm}17.2$ years) and there was a 1.9:1 ratio of males to females. 3. Sepsis was the most common risk factors (78.1%), followed by aspiration (16.6%), trauma (11.6%), and shock (8.5%). 4 The overall mortality rate was 71.9%. The mean duration was 11 days (${\pm}13.1$ days) from the diagnosis of ARDS to the death. Respiratory insufficiency appeared to be a major cause in 43.7% of the deaths followed by sepsis (36.1%), heart failure (7.6%) and hepatic failure (6.7%). 5. There were no significant differences in mortality based on sex or age. No significant difference in mortality in infectious versus noninfectious causes of ARDS was found. 6. There were significant differences in the pulse rate, platelet numbers, serum albumin and glucose levels, the amounts of 24 hour urine, arterial pH, $Pa0_2$, $PaCO_2$, $Sa0_2$, alveolar-arterial oxygen differences, $PaO_2/FIO_2$, and PEEP/$FI0_2$ between the survivors and the deaths on study days 1 through 6 of the first week after enrollment. 7. The survivors had significantly less organ failure and lower APACHE III scores at the time of diagnosis of ARDS (P<0.05). 8. The numbers of organ failure (odd ratio 1.95, 95% confidence intervals:1.05-3.61, P=0.03) and the score of APACHE III (odd ratio 1.59, 95% confidence interval:1.01-2.50, P=0.04) appeared to be independent risk factors of the mortality in the patients with ARDS. Conclusions : The mortality was 71.9% of total 167 patients in this investigation using the definition of American-European Consensus Conference on 1992 year, and the respiratory insufficiency was the leading cause of the death. In addition, the numbers of organ failure and the score of APACHE III at the time of diagnosis of ARDS appeared to be independent risk factors of the mortality in the patients with ARDS.

• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.2
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• pp.84-89
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• 2013

Purpose: Patients' movement during long image acquisition time for the fusion image of PET-CT (Positron Emission Tomography-Computed Tomography) results in unconformity, and greatly affects the quality of the image and diagnosis. The arm support fixtures provided by medical device companies are not manufactured considering the convenience and safety of the patients; the arm and head movements (horizontal and vertical) during PET/CT scan cause defects in the brain fundus images and often require retaking. Therefore, this study aims to develop patient-compensation device that would minimize the head and arm movements during PET/CT scan, providing comfort and safety, and to reduce retaking. Materials and Methods: From June to July 2012, 20 patients who had no movement-related problems and another 20 patients who had difficulties in raising arms due to shoulder pain were recruited among the ones who visited nuclear medicine department for PET Torso scan. By using Patient Holding System (PHS), different range of motion (ROM) in the arm ($25^{\circ}$, $27^{\circ}$, $29^{\circ}$, $31^{\circ}$, $33^{\circ}$, $35^{\circ}$) was applied to find the most comfortable angle and posture. The manufacturing company was investigated for the permeability of the support material, and the comfort level of applying bands (velcro type) to fix the patient's head and arms was evaluated. To find out the retake frequency due to movements, the amount of retake cases pre/post patient-compensation were analyzed using the PET Torso scan data collected between January to December 2012. Results: Among the patients without movement disorder, 18 answered that PHS and $29^{\circ}$ arm ROM were the most comfortable, and 2 answered $27^{\circ}$ and $31^{\circ}$, respectively. Among the patients with shoulder pain, 15 picked $31^{\circ}$ as the most comfortable angle, 2 picked $33^{\circ}$, and 3 picked $35^{\circ}$. For this study, the handle was manufactured to be adjustable for vertical movements. The material permeability of the patient-compensation device has been verified, and PHS and the compensation device were band-fixed (velcro type) to prevent device movements. A furrow was cut for head fixation to minimize the head and neck movements, fixing bands were attached for the head, wrist, forearm, and upper arm to limit movements. The retake frequency of PET Torso scan due to patient movements was 11.06% (191 cases/1,808 patients) before using the movement control device, and 2.65% (48 cases/1,732 patients) after using the device; 8.41% of the frequency was reduced. Conclusion: Recent change and innovation in the medical environment are making expensive medical image scans, and providing differentiated services for the customers is essential. To secure patient comfort and safety during PET/CT scans, ergonomic patient-compensation devices need to be provided. Therefore, this study manufactured a patientcompensation device with vertically adjustable ergonomic ROM according to the patient's body shape and condition during PET Torso scan. The defects in the basal ganglia images due to arm movements were reduced, and retaking was decreased.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.45-58
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• 2014

The Korean Culture Contents spread out to Worldwide, because the Korean wave is sweeping in the world. The contents stand in the middle of the Korean wave that we are used it. Each country is ongoing to keep their Culture industry improve the national brand and High added value. Performing contents is important factor of arousal in the enterprise industry. To improve high arousal confidence of product and positive attitude by populace is one of important factor by advertiser. Culture contents is the same situation. If culture contents have trusted by everyone, they will give information their around to spread word-of-mouth. So, many researcher study to measure for person's arousal analysis by statistical survey, physiological response, body movement and facial expression. First, Statistical survey has a problem that it is not possible to measure each person's arousal real time and we cannot get good survey result after they watched contents. Second, physiological response should be checked with surround because experimenter sets sensors up their chair or space by each of them. Additionally it is difficult to handle provided amount of information with real time from their sensor. Third, body movement is easy to get their movement from camera but it difficult to set up experimental condition, to measure their body language and to get the meaning. Lastly, many researcher study facial expression. They measures facial expression, eye tracking and face posed. Most of previous studies about arousal and interest are mostly limited to reaction of just one person and they have problems with application multi audiences. They have a particular method, for example they need room light surround, but set limits only one person and special environment condition in the laboratory. Also, we need to measure arousal in the contents, but is difficult to define also it is not easy to collect reaction by audiences immediately. Many audience in the theater watch performance. We suggest the system to measure multi-audience's reaction with real-time during performance. We use difference image analysis method for multi-audience but it weaks a dark field. To overcome dark environment during recoding IR camera can get the photo from dark area. In addition we present Multi-Audience Engagement Index (MAEI) to calculate algorithm which sources from sound, audience' movement and eye tracking value. Algorithm calculates audience arousal from the mobile survey, sound value, audience' reaction and audience eye's tracking. It improves accuracy of Multi-Audience Engagement Index, we compare Multi-Audience Engagement Index with mobile survey. And then it send the result to reporting system and proposal an interested persons. Mobile surveys are easy, fast, and visitors' discomfort can be minimized. Also additional information can be provided mobile advantage. Mobile application to communicate with the database, real-time information on visitors' attitudes focused on the content stored. Database can provide different survey every time based on provided information. The example shown in the survey are as follows: Impressive scene, Satisfied, Touched, Interested, Didn't pay attention and so on. The suggested system is combine as 3 parts. The system consist of three parts, External Device, Server and Internal Device. External Device can record multi-Audience in the dark field with IR camera and sound signal. Also we use survey with mobile application and send the data to ERD Server DB. The Server part's contain contents' data, such as each scene's weights value, group audience weights index, camera control program, algorithm and calculate Multi-Audience Engagement Index. Internal Device presents Multi-Audience Engagement Index with Web UI, print and display field monitor. Our system is test-operated by the Mogencelab in the DMC display exhibition hall which is located in the Sangam Dong, Mapo Gu, Seoul. We have still gotten from visitor daily. If we find this system audience arousal factor with this will be very useful to create contents.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Korean Journal of Psychosomatic Medicine
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• v.4 no.2
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• pp.269-276
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• 1996

A theroretical study was made on the psychodynamism of somatoform disorder. Somatoform disorder is caused by a defense mechanism of somatization. Somatization is the tendency to react to stimuli(drives, defenses, and conflict between them) physically rather than psychically(Moore, 1990). Ford(1983) said it is a way of life, and Dunbar(1954) said it is the shift of psychic energy toward expression in somatic symptoms. As used by Max Shur(1955), somatization links symptom formation to the regression that may occur in response to acute and chronic conflict. In the neurotic individual psychic conflict often provokes regressive phenomena that may include somatic manifestations characteristic of an earlier developmental phase. Schur calls this resomatization. Pain is the most common example of a somatization reaction to conflict. The pain has an unconscious significance derived from childhood experiences. It is used to win love, to punish misdeeds, as well as a means to amend. Among all pains, chest pain has a special meaning. Generally speaking, 'I have pain in my chest' is about the same as 'I have pain in my mind'. The chest represent the mind, and the mind reminds us about the heart. So we have a high tendency to recognize mental pain as cardiac pain. Kellner(1990) said rage and hostility, especially repressed hostility, are important factors in somatization. In 'Psychoanalytic Observation on Cardiac Pain', psychoanalyst Bacon(1953) presented clinical cases of patients who complained of cardiac pain in a psychoanalytic session that spread from the left side of their chests down their left arms. The pain was from rage and fear which came after their desire to be loved was frustrated by the analyet. She said desires related to cardiac pain were dependency needs and aggressions. Empatic relationship and therapeutic alliances are indispensable to psychotherapy in somatoform disorder. The beginning of therapy is to discover a precipitating event from the time their symptoms have started and to help the patient understand a relation between the symptom and precipitating event. Its remedial process is to find and interpret a intrapsychic conflict shown through the symptoms of the patient. Three cases of somatoform disorder patients treated based on this therapeutic method were introduced. The firt patient, Mr. H, had been suffering from hysterical aphasia with repressed rage as ie psychodynamic cause. An interpretation related to the precipitating event was given by written communication, and he recovered from his aphasia after 3 days of the session. The second patient was a dentist in a cardiac neurosis with agitation and hypochondriasis, whose psychodynamism was caused by a fear that he might lose his father's love. His symptom was also interpreted in relation to the precipitating event. It showed the patient a child-within afraid of losing his father's love. His condition improved after getting a didactic interpretation which told him, to be master of himself, The third patient was a lady transferred from the deparment of internal medicine. She had a frequent and violent fit of chest pains, whose psychodynamic cause was separation anxiety and a rage due to the frustration of dependency needs. Her symptom vanished dramatically when she wore a holler EKG monitor and did not occur during monitoring. By this experience she found her symptom was a psychogenic one, and a therapeutic alliance was formed. later in reguar psychotherapy sessions, she was told the relaton between symptoms and precipitating events. Through this she understood that her separation anxiety was connected to the symptom and she became less terrifide when it occurred. Now she can travel abroad and take well part in social activities.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.3
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• pp.425-430
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• 2014

Foods contain various nutrients such as carbohydrates, protein, oil, vitamins, and minerals. Among them, carbohydrates, protein, and oil are the main constituents of foods. Usually, these constituents are analyzed by the Kjeldahl and Soxhlet method and so on. However, these analytical methods are complex, costly, and time-consuming. Thus, this study aimed to rapidly and effectively analyze carbohydrate, protein, and oil contents with near-infrared reflectance spectroscopy (NIRS). A total of 517 food samples were measured within the wavelength range of 400 to 2,500 nm. Exactly 412 food calibration samples and 162 validation samples were used for NIRS equation development and validation, respectively. In the NIRS equation of carbohydrates, the most accurate equation was obtained under 1, 4, 5, 1 (1st derivative, 4 nm gap, 5 points smoothing, and 1 point second smoothing) math treatment conditions using the weighted MSC (multiplicative scatter correction) scatter correction method with MPLS (modified partial least square) regression. In the case of protein and oil, the best equation were obtained under 2, 5, 5, 3 and 1, 1, 1, 1 conditions, respectively, using standard MSC and standard normal variate only scatter correction methods with MPLS regression. Calibrations of these NIRS equations showed a very high coefficient of determination in calibration ($R^2$: carbohydrates, 0.971; protein, 0.974; oil, 0.937) and low standard error of calibration (carbohydrates, 4.066; protein, 1.080; oil, 1.890). Optimal equation conditions were applied to a validation set of 162 samples. Validation results of these NIRS equations showed a very high coefficient of determination in prediction ($r^2$: carbohydrates, 0.987; protein, 0.970; oil, 0.947) and low standard error of prediction (carbohydrates, 2.515; protein, 1.144; oil, 1.370). Therefore, these NIRS equations can be applicable for determination of carbohydrates, proteins, and oil contents in various foods.