• The Korean Journal of Nuclear Medicine
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• v.35 no.6
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• pp.364-370
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• 2001

Purpose: In the revascuarization of ischemic dysfunctional myocardium, stunned myocardium was reported to recover function earlier than hibernating myocardium. It was also suggested that stunning and hibernation could be discriminated by reversibility of perfusion impairment on myocardial SPECT. In this study, we investigated the time course of functional recover after CABG according to reversibility of perfusion impairment. Materials and Methods: In 92 patients with coronary artery disease, Tl-201 rest/dipyridamole stress Tc-99m-MIBI gated SPECT was performed before, 3 months after, and 17 months after CABG. Using a 20-segment model, segmental perfusion and systolic thickening were automatically quantified. Perfusion-impaired segments with abnormal thickening were classified by reversibility into reversible (REV) and irreversible (IRREV) groups. The proportions of function-recovered segments were compared between groups and also between 3 months and 17 months in each group. Results: A total of 129 segments were Included In the analysis, and 76 were REV and 53 were IRREV. At 3 months after CABG, 61 segments (80%) in REV group showed functional recovery while 28 segments (53%) in IRREV group did (p<0.001). However, at 17 months after CABG, 60 segments (79%) in REV group and 37 segments (70%) un IRREV group showed functional recovery (p=n.s.). When comparing 3 months and 17 months in each group, REV group showed no difference, while IRREV group showed significant further improvement (p<0.05). Conclusion: In viable myocardium with ischemic myocardial dysfunction, the segments with reversible perfusion impairment recover function earlier after revascularization than irreversible segments.

• The Korean Journal of Nuclear Medicine
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• v.37 no.3
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• pp.147-152
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• 2003

Purpose: We evaluated radioisotope and sex-specific differences of normal limits for left ventricle volumes (LWs) and ejection fraction (EF) using myocardial perfusion gated SPECT (g-SPECT). Materials and Methods: Rest Tl-201/post-stress Tc-99m MIBI g-SPECT measurements with acquisitions of 8-frame were evaluated for 70 patients (mean age $55{\pm}14.56%$ female) who either had < 10% pretest likelihood of CAD (n = 12) or had normal coronary angiography (EF > 50%) (n = 58). LVEF, LWs were automatically determined by quantitative gated SPECT using QGS program. Results: Similar results were obtained for mean LVEF between Tc-99m MIBI ($62%{\pm}7%$ and Tl-201 ($63%{\pm}8%$) g-SPECT measurements. In Contrast, Tl-201 g-SPECT had significantly lower LWs values ($EDV;\;74{\pm}23mL,\;ESV;\;28{\pm}14mL$) than Tc-99m MIBI g-SPECT ($EDV;\;82{\pm}25mL,\;ESV;\;32{\pm}15mL$) (p<0.05). Women had significantly lower EDV ($Tc-99m\;MIBI;\;71{\pm}18mL,\;Tl-201;\;65{\pm}17mL$), and ESV values ($Tc-99m\;MIBI;\;27{\pm}10mL,\;Tl-201;\;23{\pm}8mL$) compared with EDV ($Tc-99m\;MIBI;\;96{\pm}27mL,\;Tl-201;\;85{\pm}24mL$), and ESV Values ($Tc-99m\;MIBI;\;40{\pm}17mL,\;Tl-201;\;36{\pm}16mL$) of men (p<0.05). Women had significantly higher LV EF Values ($65%{\pm}7%$) than men ($60%{\pm}8%$) by Tl-201 gated SPECT (p<0.05). Conclusion: These data suggest significant differeuces in normal limits for LWs and EF, according to genders and radiopharmaceutical. Therefore, the evaluation of cardiac function in patients should consider radioisotope and sex-matched normal values.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.

• Journal of Mushroom
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• v.17 no.4
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• pp.211-217
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• 2019

Currently, cultivation of mushrooms using the Information and Communication Technology (ICT)-based smart farming technique is increasing rapidly. The main environmental factors for growth of mushrooms are temperature, humidity, carbon dioxide (CO₂), and light. Among all the mentioned factors, currently, only temperature has been maintained under automatic control. However, humidity and ventilation are controlled using a timer, based on technical experience.Therefore, in this study, a Pleurotus eryngii first-generation smart farm model was set up that can automatically control temperature, humidity, and ventilation. After installing the environmental control system and the monitoring device, the environmental condition of the mushroom cultivation room and the growth of the fruiting bodies were studied. The data thus obtained was compared to that obtained using the conventional cultivation method.In farm A, the temperature during the primordia formation stage was about 17℃, and was maintained at approximately 16℃ during the fruiting stage. The humidity was initially maintained at 95%, and the farm was not humidified after the primordia formation stage. There was no sensor for CO₂ management, and the system was ventilated as required by observing the shape of the pileus and the stipe. It was observed that, the concentration of CO₂ was between 700 and 2,500 ppm during the growth period. The average weight of the mushrooms produced in farm A was 125 g, and the quality was between that of the premium and the first grade.In farm B. The CO₂ sensor was in use for measurement purposes only; the system was ventilated as required by observing the shape of the pileus and the stipe. During the growth period, the CO₂ concentration was observed to be between 640 and 4,500 ppm. The average weight of the mushrooms produced in farm B was 102 g.These results indicate that the quality of the king oyster mushroom is determined by the environmental conditions, especially by the concentration of CO₂. Thus, the data obtained in this study can be used as an optimal smart farm model, where, by improving the environmental control method of farm A, better quality mushrooms were obtained.

• Horticultural Science & Technology
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• v.34 no.6
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• pp.871-877
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• 2016

Recycling nutrient solutions in closed hydroponic production systems is usually accompanied by an imbalance of nutrient solutions when concentration is controlled according to electrical conductivity (EC) levels. This study investigated whether it was possible to automatically control the concentrations of five essential elements nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg) using only N, K and Ca ion sensors. N, P, K, Ca, and Mg uptake was measured in the nutrient solution, and relationships between absorbed ions were analyzed through twice-repeated experiments in lettuce. Results confirmed that the pattern of $PO_4$ ion uptake was similar that of N, and the pattern of Mg ion uptake was similar that of Ca. $PO_4$ ion uptake was most highly correlated with N, and Mg was most highly correlated with Ca. Regression coefficients of N and $PO_4$ were significantly different at 1.04 and 0.55, respectively, but were similar between Ca and Mg at 0.35 and 0.40, respectively. Additional experiments were conducted to measure nutrient uptake in pak choi and rose plants, both to confirm the results from the first experiment in lettuce, and to assess possible application to other crops. Coefficients of determination both for N and $PO_4$, and Ca and Mg were considerably high ($R^2=0.86$) in cultured pak choi, and similar results were observed in cultured rose ($R^2=0.87$ and 0.73, respectively). Regression coefficients for cultured pak choi were 0.56 and 0.24, respectively, and for rose were 0.51 and 0.16, respectively. Although the results obtained for N and $PO_4$ were not consistent between the lettuce experiments, N and $PO_4$ have similar regression coefficients for all crops. No common coefficient was found between Ca and Mg.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.77-83
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• 2015

Frequent pattern mining, which is one of the major areas actively studied in data mining, is a method for extracting useful pattern information hidden from large data sets or databases. Moreover, frequent pattern mining approaches have been actively employed in a variety of application fields because the results obtained from them can allow us to analyze various, important characteristics within databases more easily and automatically. However, traditional frequent pattern mining methods, which simply extract all of the possible frequent patterns such that each of their support values is not smaller than a user-given minimum support threshold, have the following problems. First, traditional approaches have to generate a numerous number of patterns according to the features of a given database and the degree of threshold settings, and the number can also increase in geometrical progression. In addition, such works also cause waste of runtime and memory resources. Furthermore, the pattern results excessively generated from the methods also lead to troubles of pattern analysis for the mining results. In order to solve such issues of previous traditional frequent pattern mining approaches, the concept of representative pattern mining and its various related works have been proposed. In contrast to the traditional ones that find all the possible frequent patterns from databases, representative pattern mining approaches selectively extract a smaller number of patterns that represent general frequent patterns. In this paper, we describe details and characteristics of pattern condensing techniques that consider the maximality or closure property of generated frequent patterns, and conduct comparison and analysis for the techniques. Given a frequent pattern, satisfying the maximality for the pattern signifies that all of the possible super sets of the pattern must have smaller support values than a user-specific minimum support threshold; meanwhile, satisfying the closure property for the pattern means that there is no superset of which the support is equal to that of the pattern with respect to all the possible super sets. By mining maximal frequent patterns or closed frequent ones, we can achieve effective pattern compression and also perform mining operations with much smaller time and space resources. In addition, compressed patterns can be converted into the original frequent pattern forms again if necessary; especially, the closed frequent pattern notation has the ability to convert representative patterns into the original ones again without any information loss. That is, we can obtain a complete set of original frequent patterns from closed frequent ones. Although the maximal frequent pattern notation does not guarantee a complete recovery rate in the process of pattern conversion, it has an advantage that can extract a smaller number of representative patterns more quickly compared to the closed frequent pattern notation. In this paper, we show the performance results and characteristics of the aforementioned techniques in terms of pattern generation, runtime, and memory usage by conducting performance evaluation with respect to various real data sets collected from the real world. For more exact comparison, we also employ the algorithms implementing these techniques on the same platform and Implementation level.

• Fiber Technology and Industry
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• v.2 no.4
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• pp.490-508
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• 1998

One of the latest fields of research in the area of output devices is tactual display devices [13,31]. These tactual or haptic devices allow the user to receive haptic feedback output from a variety of sources. This allows the user to actually feel virtual objects and manipulate them by touch. This is an emerging technology and will be instrumental in enhancing the realism of wearable augmented environments for certain applications. Tactual displays have previously been used for scientific visualization in virtual environments by chemists and engineers to improve perception and understanding of force fields and of world models populated with the impenetrable. In addition to tactual displays, the use of wearable audio displays that allow sound to be spatialized are being developed. With wearable computers, designers will soon be able to pair spatialized sound to virtual representations of objects when appropriate to make the wearable computer experience even more realistic to the user. Furthermore, as the number and complexity of wearable computing applications continues to grow, there will be increasing needs for systems that are faster, lighter, and have higher resolution displays. Better networking technology will also need to be developed to allow all users of wearable computers to have high bandwidth connections for real time information gathering and collaboration. In addition to the technology advances that make users need to wear computers in everyday life, there is also the desire to have users want to wear their computers. In order to do this, wearable computing needs to be unobtrusive and socially acceptable. By making wearables smaller and lighter, or actually embedding them in clothing, users can conceal them easily and wear them comfortably. The military is currently working on the development of the Personal Information Carrier (PIC) or digital dog tag. The PIC is a small electronic storage device containing medical information about the wearer. While old military dog tags contained only 5 lines of information, the digital tags may contain volumes of multi-media information including medical history, X-rays, and cardiograms. Using hand held devices in the field, medics would be able to call this information up in real time for better treatment. A fully functional transmittable device is still years off, but this technology once developed in the military, could be adapted tp civilian users and provide ant information, medical or otherwise, in a portable, not obstructive, and fashionable way. Another future device that could increase safety and well being of its users is the nose on-a-chip developed by the Oak Ridge National Lab in Tennessee. This tiny digital silicon chip about the size of a dime, is capable of 'smelling' natural gas leaks in stoves, heaters, and other appliances. It can also detect dangerous levels of carbon monoxide. This device can also be configured to notify the fire department when a leak is detected. This nose chip should be commercially available within 2 years, and is inexpensive, requires low power, and is very sensitive. Along with gas detection capabilities, this device may someday also be configured to detect smoke and other harmful gases. By embedding this chip into workers uniforms, name tags, etc., this could be a lifesaving computational accessory. In addition to the future safety technology soon to be available as accessories are devices that are for entertainment and security. The LCI computer group is developing a Smartpen, that electronically verifies a user's signature. With the increase in credit card use and the rise in forgeries, is the need for commercial industries to constantly verify signatures. This Smartpen writes like a normal pen but uses sensors to detect the motion of the pen as the user signs their name to authenticate the signature. This computational accessory should be available in 1999, and would bring increased peace of mind to consumers and vendors alike. In the entertainment domain, Panasonic is creating the first portable hand-held DVD player. This device weight less than 3 pounds and has a screen about 6' across. The color LCD has the same 16:9 aspect ratio of a cinema screen and supports a high resolution of 280,000 pixels and stereo sound. The player can play standard DVD movies and has a hour battery life for mobile use. To summarize, in this paper we presented concepts related to the design and use of wearable computers with extensions to smart spaces. For some time, researchers in telerobotics have used computer graphics to enhance remote scenes. Recent advances in augmented reality displays make it possible to enhance the user's local environment with 'information'. As shown in this paper, there are many application areas for this technology such as medicine, manufacturing, training, and recreation. Wearable computers allow a much closer association of information with the user. By embedding sensors in the wearable to allow it to see what the user sees, hear what the user hears, sense the user's physical state, and analyze what the user is typing, an intelligent agent may be able to analyze what the user is doing and try to predict the resources he will need next or in the near future. Using this information, the agent may download files, reserve communications bandwidth, post reminders, or automatically send updates to colleagues to help facilitate the user's daily interactions. This intelligent wearable computer would be able to act as a personal assistant, who is always around, knows the user's personal preferences and tastes, and tries to streamline interactions with the rest of the world.

• Radiation Oncology Journal
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• v.22 no.1
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• pp.33-39
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• 2004

Purpose : A tumor registry system for the patients treated by radiotherapy at Samsung Medical Center since the opening of a hospital at 1994 was employed. In this study, the tumor registry system was introduced and the validity of the tumor registration was analyzed. Materials and Methods: The tumor registry system was composed of three parts: patient demographic, diagnostic, and treatment Information. All data were input in a screen using a mouse only. Among the 10,000 registered cases in the tumor registry system until Aug, 2002, 199 were randomly selected and their registration data were compared with the patients' medical records. Results : Total input errors were detected on 15 cases (7.5%). There were 8 error items In the part relating to diagnostic Information: tumor site 3, pathology 2, AJCC staging 2 and performance status 1. In the part relating to treatment information there were 9 mistaken items: combination treatment 4, the date of initial treatment 3 and radiation completeness 2. According to the assignment doctor, the error ratio was consequently variable. The doctors who 010 no double-checks showed higher errors than those that 010 (15.6%:3.7%). Conclusion: Our tumor registry had errors within 2% for each Item. Although the overall data qualify was high, further improvement might be achieved through promoting sincerity, continuing training, periodic validity tests and keeping double-checks. Also, some items associated with the hospital Information system will be input automatically In the next step.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.482-488
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• 2014

This paper aims to analyze user's emotion automatically by analyzing Twitter, a representative social network service (SNS). In order to create sentiment analysis models by using machine learning techniques, sentiment labels that represent positive/negative emotions are required. However it is very expensive to obtain sentiment labels of tweets. So, in this paper, we propose a sentiment analysis model by using self-training technique in order to utilize "data without sentiment labels" as well as "data with sentiment labels". Self-training technique is that labels of "data without sentiment labels" is determined by utilizing "data with sentiment labels", and then updates models using together with "data with sentiment labels" and newly labeled data. This technique improves the sentiment analysis performance gradually. However, it has a problem that misclassifications of unlabeled data in an early stage affect the model updating through the whole learning process because labels of unlabeled data never changes once those are determined. Thus, labels of "data without sentiment labels" needs to be carefully determined. In this paper, in order to get high performance using self-training technique, we propose 3 policies for updating "data with sentiment labels" and conduct a comparative analysis. The first policy is to select data of which confidence is higher than a given threshold among newly labeled data. The second policy is to choose the same number of the positive and negative data in the newly labeled data in order to avoid the imbalanced class learning problem. The third policy is to choose newly labeled data less than a given maximum number in order to avoid the updates of large amount of data at a time for gradual model updates. Experiments are conducted using Stanford data set and the data set is classified into positive and negative. As a result, the learned model has a high performance than the learned models by using "data with sentiment labels" only and the self-training with a regular model update policy.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.99-106
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• 2020

Changam, Lee Samman(1770~1845), who created his own handwriiting to be referred to as the three great writers of the late Joseon Dynasty, invented as the original 'Haengunyusu Typeface' and developed Calligraphy spirit of DonggugJinche in Honam province. He ultimately pursued the state of tonglyeong by raising the personality of 'writing is the person's personality' and the attitude of learning the old. Through the book chang-amseogyeol, he basically polished Haeseo of Han Dynasty and Wi Dynasty and emphasized that Haengseo and Choseo are done automatically when muscle strength and bone strength are established. And since calligraphy originated from 'nature', it goes through the 'Beobcheongwijin' spirit. After doing so, expressed the state of tonglyeong of " mubeob-ibeob ", the stage of reaching. In addition, Changam showed the aesthetic that you can get the novelty by pursuing the philosophy of 'Wu' and the 'beauty of Stupid and Lacking' based on LaoTzu and ChuangTzu. This is a philosophy that follows nature's logic to reveal nature's nature. And it is an aesthetic that protects his 'True Wu' without knowing and greedy. On the other hand, Changam promoted natural and vital beauty through force in the method of using the brush. He suggested the 'Push and Hard' of the Han dynasty, pushing it with force using this power properly. In particular, the feeling of an IlunMujeog brush in 『Changam Calligraphy-The cloud stays Poem』 overflows with the vitality and bizarre and strange dynamism of the spirit and typeface as eum-yang harmonizes with each other. In addition, the beauty of Push and Hard containing polyeoghamse is misaligned, but it has achieved a natural aesthetic without invading. This work demonstrates the real look of Changam choseo. In addition, the beauty of Push and Hard containing polyeoghamse is misaligned, but it has achieved a natural aesthetic without invading. Changam proves the real look of "Haedong's best Chose Maestro".