• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.4
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• pp.283-290
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• 2022

In this study, an IoT inspection system that can be linked with a server was developed using a gas timer and ESP-01 Wi-Fi module installed on a gas valve in the home. The server environment of the gas leak IoT inspection system was installed with APM (Apache, PHP, MySQL) to collect gas pressure data by generation so that leakage checks could be performed. In order to control the gas leak IoT inspection system, the app inventory was used to manage the gas leak check value in real time. In addition, user convenience has been enhanced so that membership management, WiFi settings, and leakage check values can be checked through mobile apps. In order to manage subscribers by region, the user list was checked by logging in in in the administrator mode so that the information on whether or not the leak test was conducted and the results could be provided. In addition, when the user presses the gas leak check button, the pressure is automatically checked, and the measured value is stored in the server, and when a gas leak occurs, the leakage check is performed after alarm and repair so that it can be used if normal. In addition, in order to prevent overlapping membership, membership management can be performed based on MAC addresses.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.25-34
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• 2020

In the current medical information system, a system environment is constructed in which Biometric data generated by using IoT or medical equipment connected to a patient can be stored in a medical information server and monitored at the same time. Also, the patient's biometric data, medical information, and personal information after simple authentication using only the ID / PW via the mobile terminal of the medical staff are easily accessible. However, the method of accessing these medical information needs to be improved in the dimension of protecting patient's personal information, and provides a quick authentication system for first aid. In this paper, we implemented an automatic authentication system based on the patient's situation and evaluated its performance. Patient's situation was graded into normal and emergency situation, and the situation of the patient was determined in real time using incoming patient biometric data from the ward. If the patient's situation is an emergency, an emergency message including an emergency code is send to the mobile terminal of the medical staff, and they attempted automatic authentication to access the upper medical information of the patient. Automatic authentication is a combination of user authentication(ID/PW, emergency code) and mobile terminal authentication(medical staff's role, working hours, work location). After user authentication, mobile terminal authentication is proceeded automatically without additional intervention by medical staff. After completing all authentications, medical staffs get authorization according to the role of medical staffs and patient's situations, and can access to the patient's graded medical information and personal information through the mobile terminal. We protected the patient's medical information through limited medical information access by the medical staff according to the patient's situation, and provided an automatic authentication without additional intervention in an emergency situation. We performed performance evaluation to verify the performance of the implemented automatic authentication system.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.123-139
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• 2019

The job classification system of major job sites differs from site to site and is different from the job classification system of the 'SQF(Sectoral Qualifications Framework)' proposed by the SW field. Therefore, a new job classification system is needed for SW companies, SW job seekers, and job sites to understand. The purpose of this study is to establish a standard job classification system that reflects market demand by analyzing SQF based on job offer information of major job sites and the NCS(National Competency Standards). For this purpose, the association analysis between occupations of major job sites is conducted and the association rule between SQF and occupation is conducted to derive the association rule between occupations. Using this association rule, we proposed an intelligent job classification system based on data mapping the job classification system of major job sites and SQF and job classification system. First, major job sites are selected to obtain information on the job classification system of the SW market. Then We identify ways to collect job information from each site and collect data through open API. Focusing on the relationship between the data, filtering only the job information posted on each job site at the same time, other job information is deleted. Next, we will map the job classification system between job sites using the association rules derived from the association analysis. We will complete the mapping between these market segments, discuss with the experts, further map the SQF, and finally propose a new job classification system. As a result, more than 30,000 job listings were collected in XML format using open API in 'WORKNET,' 'JOBKOREA,' and 'saramin', which are the main job sites in Korea. After filtering out about 900 job postings simultaneously posted on multiple job sites, 800 association rules were derived by applying the Apriori algorithm, which is a frequent pattern mining. Based on 800 related rules, the job classification system of WORKNET, JOBKOREA, and saramin and the SQF job classification system were mapped and classified into 1st and 4th stages. In the new job taxonomy, the first primary class, IT consulting, computer system, network, and security related job system, consisted of three secondary classifications, five tertiary classifications, and five fourth classifications. The second primary classification, the database and the job system related to system operation, consisted of three secondary classifications, three tertiary classifications, and four fourth classifications. The third primary category, Web Planning, Web Programming, Web Design, and Game, was composed of four secondary classifications, nine tertiary classifications, and two fourth classifications. The last primary classification, job systems related to ICT management, computer and communication engineering technology, consisted of three secondary classifications and six tertiary classifications. In particular, the new job classification system has a relatively flexible stage of classification, unlike other existing classification systems. WORKNET divides jobs into third categories, JOBKOREA divides jobs into second categories, and the subdivided jobs into keywords. saramin divided the job into the second classification, and the subdivided the job into keyword form. The newly proposed standard job classification system accepts some keyword-based jobs, and treats some product names as jobs. In the classification system, not only are jobs suspended in the second classification, but there are also jobs that are subdivided into the fourth classification. This reflected the idea that not all jobs could be broken down into the same steps. We also proposed a combination of rules and experts' opinions from market data collected and conducted associative analysis. Therefore, the newly proposed job classification system can be regarded as a data-based intelligent job classification system that reflects the market demand, unlike the existing job classification system. This study is meaningful in that it suggests a new job classification system that reflects market demand by attempting mapping between occupations based on data through the association analysis between occupations rather than intuition of some experts. However, this study has a limitation in that it cannot fully reflect the market demand that changes over time because the data collection point is temporary. As market demands change over time, including seasonal factors and major corporate public recruitment timings, continuous data monitoring and repeated experiments are needed to achieve more accurate matching. The results of this study can be used to suggest the direction of improvement of SQF in the SW industry in the future, and it is expected to be transferred to other industries with the experience of success in the SW industry.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Journal of the Korean Society of Radiology
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• v.14 no.3
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• pp.245-252
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• 2020

The purpose of this study was intended to recognize the importance of quality control (QC) in order to reduce exposure and improve image quality by comparing the center-point (CP) of according to hospital grade and the difference between X-ray field (XF) and light field (LF) in diagnostic digital X-ray devices. XF and LF size, CP were measured in 12 digital X-ray devices at 10 hospitals located in 00 metropolitan cities. Phantom was made in different width respectively, using 0.8 mm wire after attaching to the standardized graph paper on transparent plastic plate and marked as cross wire in the center of the phantom. After placing the phantom on the table of the digital X-ray device, the images were obtained by shooting it vertically each field of survey. All images were acquired under the same conditions of exposure at distance of 100cm between the focus-detector. XF and LF size, CP error were measured using the picture archiving communication system. data were expressed as mean with standard error and then analyzed using SPSS ver. 22.0. The difference in field between the XF and LF size was the smallest in clinic, followed by university hospitals, hospitals and general hospitals. Based on the university hospitals with the least CP error, there was a statistically significant difference in CP error between university hospitals and clinics (p=0.024). Group less than 36-month after QC had fewer statistical errors than 36-month group (0.26 vs. 0.88, p=0.036). The difference between the XF and LF size was the lowest in clinic and CP error was the lowest in university hospital. Moreover, hospitals with short period of time after QC have fewer CP error and it means that introduction of timely QC according to the QC items is essential.

• Korean Security Journal
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• no.21
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• pp.155-175
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• 2009

RFID that provide automatic identification by reading a tag attached to material through radio frequency without direct touch has some specification, such as rapid identification, long distance identification and penetration, so it is being used for distribution, transportation and safety by using the frequency of 125KHz, 134KHz, 13.56MHz, 433.92MHz, 900MHz, and 2.45GHz. Also it is one of main part of Ubiquitous that means connecting to net-work any time and any place they want. RFID is expected to be new growth industry worldwide, so Korean government think it as prospective field and promote research project and exhibition business program to linked with industry effectively. RFID could be used for access control of person and vehicle according to section and for personal certify with password. RFID can provide more confident security than magnetic card, so it could be used to prevent forgery of register card, passport and the others. Active RFID could be used for protecting operation service using it's long distance date transmission by application with positioning system. And RFID's identification and tracking function can provide effective visitor management through visitor's register, personal identification, position check and can control visitor's movement in the secure area without their approval. Also RFID can make possible of the efficient management and prevention of loss of carrying equipments and others. RFID could be applied to copying machine to manager and control it's user, copying quantity and It could provide some function such as observation of copy content, access control of user. RFID tag adhered to small storage device prevent carrying out of item using the position tracking function and control carrying-in and carrying-out of material efficiently. magnetic card and smart card have been doing good job in identification and control of person, but RFID can do above functions. RFID is very useful device but we should consider the prevention of privacy during its application.

• Food Science and Preservation
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• v.23 no.7
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• pp.1065-1073
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• 2016

This study investigated the sensory attributes and quality characteristics of Fuji apples based on market commodity price to provide data for quality index of Fuji apples. Samples were purchased from the Garak market (Seoul Agro-Fisheries & Food Corporation) and divided into four groups depending on the price such as group A, B, C, D. There were no significant differences in their volume and weight among groups. In the soluble solid content and total free sugar, A and B group (high price) showed higher content than those of C and D (low price) group. And also, the A group and B, C, D group showed 386.29 mg% and 320.09~359.28 mg% in the total organic acid content, respectively. As an sensory evaluation results, A group and B group were evaluated higher score than those of C and D group in the uniformity of red color and glossiness of skin and unique apple sensory attributes using quantitative descriptive analysis. Consumer test showed similar to quantitative descriptive analysis results in the various sensory attributes. In the analysis results between quality characteristics and sensory attributes of Fuji apples, total acceptability was correlated positively with titratable acidity (r=0.58), soluble solid (r=0.89), soluble solid content/titratable acidity ratio (r=0.42), total free sugar (r=0.36) and total organic acid (r=0.38). Based on principal component analysis of apple's quality characteristics, apples were primary separated along the first principal component (pH, acidity, soluble solid content, total free sugar, organic acid), which accounted for 66.01% of total variance. In addition, principal component analysis of sensory evaluation revealed a total variance for the quantitative descriptive of 55. 65% and a total variance for the consumer test of 55.84%.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.59-68
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• 1998

Digital hearing aids offer many advantages over conventional analog hearing aids. With the advent of high speed digital signal processing chips, new digital techniques have been introduced to digital hearing aids. In addition, the evaluation of new ideas in hearing aids is necessarily accompanied by intensive subject-based clinical tests which requires much time and cost. In this paper, we present an objective method to evaluate and predict the performance of hearing aid systems without the help of such subject-based tests. In the hearing impairment simulation(HIS) algorithm, a sensorineural hearing impairment medel is established from auditory test data of the impaired subject being simulated. Also, the nonlinear behavior of the loudness recruitment is defined using hearing loss functions generated from the measurements. To transform the natural input sound into the impaired one, a frequency sampling filter is designed. The filter is continuously refreshed with the level-dependent frequency response function provided by the impairment model. To assess the performance, the HIS algorithm was implemented in real-time using a floating-point DSP. Signals processed with the real-time system were presented to normal subjects and their auditory data modified by the system was measured. The sensorineural hearing impairment was simulated and tested. The threshold of hearing and the speech discrimination tests exhibited the efficiency of the system in its use for the hearing impairment simulation. Using the HIS system we evaluated three typical hearing aid algorithms.

• Journal of Korean Society of Forest Science
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• v.94 no.6
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• pp.496-503
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• 2005

This study was conducted to investigate the influences of sapflow flux on soil water tensions and soil moisture content at the Abies holophylla plots in Gwangneung, Gyeonggido, from September to October 2004. The Abies holophylla had been planted in 1976 and thinning and pruning were carried out in 1996 and 2004. Sapflow flux was measured by the heat pulse method, and soil water tension was measured by tensiometer at hillslope and streamside. Time domain reflectometry probes (TDR) were positioned horizontally at the depth of 10, 30 and 50 cm to measure soil moisture content. All of data were recorded every 30 minutes with the dataloggers. The sapflow flux responded sensitively to rainfall, so little sapflow was detected in rainy days. The average daily sapflow flux of sample trees was 10.16l, a maximum was 15.09l, and a minimum was 0.0l. The sapflow flux's diurnal changes showed that sapflow flux increased from 9 am and up to 0.74 l/30 min. The highest sapflow flux maintained by 3 pm and decreased almost 0.0 l/30 mm after 7 pm. The average soil water tensions were low ($-141.3cmH_2O$, $-52.9cmH_2O$ and $-134.2cmH_2O$) at hillslope and high ($-6.1cmH_2O$, $-18.0cmH_2O$ and $-3.7cmH_2O$) at streamside. When the soil moisture content decreased after rainfall, the soil water tension at hillslope responded sensitively to the sapflow flux. The soil water tension decreased as the sapflow flux increased during the day time, whereas increased during the night time when the sapflow flux was not detected. On the other hand, there was no significant relationship between soil water tension and sapflow flux at streamside. Soil moisture content at hillslope decreased continuously after rain, and showed a negative correlation to sapflow flux like a soil water tension at hillslope. As considered results above, it was confirmed that the response of soil moisture tension to sapflow flux at hillslope and streamside were different.