• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.1
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• pp.33-42
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• 2014

Purpose: I-131 scan using High Energy (HE) collimator is generally used. While, Medium Energy (ME) collimator is not suggested to use in result of an excessive septal penetration effects, it is used to improve the sensitivities of count rate on lower dose of I-131. This research aims to evaluate I-131 SPECT/CT image quality using by HE and ME collimator and also find out the possibility of ME collimator clinical application. Materials and Methods: ME and HE collimator are substituted as Siemens symbia T16 SPECT/CT, using I-131 point source and NEMA NU-2 IQ phantom. Single Energy Window (SEW) and Triple Energy Windows (TEW) are applied for image acquisition and images with CTAC and Scatter correction application or not, applied different number of iteration and sub set are reconstructed by IR method, flash 3D. By analysis of acquired image, the comparison on sensitivities, contrast, noise and aspect ratio of two collimators are able to be evaluated. Results: ME Collimator is ahead of HE collimator in terms of sensitivity (ME collimator: 188.18 cps/MBq, HE collimator: 46.31 cps/MBq). For contrast, reconstruction image used by HE collimator with TEW, 16 subset 8 iteration applied CTAC is shown the highest contrast (TCQI=190.64). In same condition, ME collimator has lower contrast than HE collimator (TCQI=66.05). The lowest aspect ratio for ME collimator and HE collimator are 1.065 with SEW, CTAC (+) and 1.024 with TEW, CTAC (+) respectively. Conclusion: Selecting a proper collimator is important factor for image quality. This research finding tells that HE collimator, which is generally used for I-131 scan emitted high energy ${\gamma}$-ray is the most recommendable collimator for image quality. However, ME collimator is also applicable in condition of lower dose, lower sensitive if utilizing energy window, matrix size, IR parameter, CTAC and scatter correction appropriately.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.50-60
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• 2010

For the last half a century, the personal computer and software industries have been prosperous due to the incessant evolution of computer systems. In the 21st century, the embedded system market has greatly increased as the market shifted to the mobile gadget field. While a lot of multimedia gadgets such as mobile phone, navigation system, PMP, etc. are pouring into the market, most industrial control systems still rely on 8-bit micro-controllers and simple application software techniques. Unfortunately, the technological barrier which requires additional investment and higher quality manpower to overcome, and the business risks which come from the uncertainty of the market growth and the competitiveness of the resulting products have prevented the companies in the industry from taking advantage of such fancy technologies. However, high performance, low-power and low-cost hardware and software platforms will enable their high-technology products to be developed and recognized by potential clients in the future. This paper presents such a platform for industrial embedded systems. The platform was designed based on Telechips TCC8300 multimedia processor which embedded a variety of parallel hardware for the implementation of multimedia functions. And open-source Embedded Linux, TinyX and GTK+ are used for implementation of GUI to minimize technology costs. In order to estimate the expected performance and power consumption, the performance improvement and the power consumption due to each of enabled hardware sub-systems including YUV2RGB frame converter are measured. An analytic model was devised to check the feasibility of a new application and trade off its performance and power consumption. The validity of the model has been confirmed by implementing a real target system. The cost can be further mitigated by using the hardware parts which are being used for mass production products mostly in the cell-phone market.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.147-161
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• 2010

As broadcasting and communication are converged recently, communication is jointed to TV. TV viewing has brought about many changes. The IPTV (Internet Protocol Television) provides information service, movie contents, broadcast, etc. through internet with live programs + VOD (Video on demand) jointed. Using communication network, it becomes an issue of new business. In addition, new technical issues have been created by imaging technology for the service, networking technology without video cuts, security technologies to protect copyright, etc. Through this IPTV network, users can watch their desired programs when they want. However, IPTV has difficulties in search approach, menu approach, or finding programs. Menu approach spends a lot of time in approaching programs desired. Search approach can't be found when title, genre, name of actors, etc. are not known. In addition, inserting letters through remote control have problems. However, the bigger problem is that many times users are not usually ware of the services they use. Thus, to resolve difficulties when selecting VOD service in IPTV, a personalized service is recommended, which enhance users' satisfaction and use your time, efficiently. This paper provides appropriate programs which are fit to individuals not to save time in order to solve IPTV's shortcomings through filtering and recommendation-related system. The proposed recommendation system collects TV program information, the user's preferred program genres and detailed genre, channel, watching program, and information on viewing time based on individual records of watching IPTV. To look for these kinds of similarities, similarities can be compared by using ontology for TV programs. The reason to use these is because the distance of program can be measured by the similarity comparison. TV program ontology we are using is one extracted from TV-Anytime metadata which represents semantic nature. Also, ontology expresses the contents and features in figures. Through world net, vocabulary similarity is determined. All the words described on the programs are expanded into upper and lower classes for word similarity decision. The average of described key words was measured. The criterion of distance calculated ties similar programs through K-medoids dividing method. K-medoids dividing method is a dividing way to divide classified groups into ones with similar characteristics. This K-medoids method sets K-unit representative objects. Here, distance from representative object sets temporary distance and colonize it. Through algorithm, when the initial n-unit objects are tried to be divided into K-units. The optimal object must be found through repeated trials after selecting representative object temporarily. Through this course, similar programs must be colonized. Selecting programs through group analysis, weight should be given to the recommendation. The way to provide weight with recommendation is as the follows. When each group recommends programs, similar programs near representative objects will be recommended to users. The formula to calculate the distance is same as measure similar distance. It will be a basic figure which determines the rankings of recommended programs. Weight is used to calculate the number of watching lists. As the more programs are, the higher weight will be loaded. This is defined as cluster weight. Through this, sub-TV programs which are representative of the groups must be selected. The final TV programs ranks must be determined. However, the group-representative TV programs include errors. Therefore, weights must be added to TV program viewing preference. They must determine the finalranks.Based on this, our customers prefer proposed to recommend contents. So, based on the proposed method this paper suggested, experiment was carried out in controlled environment. Through experiment, the superiority of the proposed method is shown, compared to existing ways.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Journal of Life Science
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• v.19 no.11
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• pp.1529-1537
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• 2009

To elucidate further the antitumor effects of a natural L-arginine analogue, L-canavanine, the mechanism underlying apoptogenic activity of L-canavanine and its modulation by protein tyrosine kinase $p56^{lck}$ was investigated in human Jurkat T cells. When the cells were treated with 1.25 to 2.5 mM L-canavanine for 36 h, several apoptotic events including mitochondrial membrane potential (${\Delta\Psi}m$) loss, activation of caspase-9, -3, -8, and -7, poly (ADP-ribose) polymerase (PARP) degradation, and DNA fragmentation were induced without alteration in the levels of Fas or FasL. These apoptotic changes were more significant in $p56^{lck}$-deficient Jurkat clone JCaM1.6 than in $p56^{lck}$-positive Jurkat clone E6.1. The L-canavanine-induced apoptosis observed in $p56^{lck}$-deficient JCaM1.6 cells was significantly reduced by introducing $p56^{lck}$ gene into JCaM1.6 cells by stable transfection. Treatment of JCaM1.6/lck cells with L-canavanine caused a transient 1.6-fold increase in the kinase activity of $p56^{lck}$. Both FADD-positive wild-type Jurkat T cell clone A3 and FADD-deficient Jurkat T cell clone I2.1 exhibited a similar susceptibility to the cytotoxicity of L-canavanine, excluding involvement of Fas/FasL system in triggering L-canavanine-induced apoptosis. The L-canavanine-induced apoptotic sub-$G_1$ peak and activation of caspase-3, -8, and -7 were abrogated by pan-caspase inhibitor (z-VAD-fmk), whereas L-canavanine-induced activation of caspase-9 was not affected. These results demonstrated that L-canavanine caused apoptosis of Jurkat T cells via the loss of ${\Delta\Psi}m$, and the activation of caspase-9, -3, -8, and -7, leading to PARP degradation, and that the $p56^{lck}$ kinase attenuated the ${\Delta\Psi}m$ loss and activation of caspases, and thus contributed as a negative regulator to L-canavanine-induced apoptosis.

• Applied Chemistry for Engineering
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• v.9 no.3
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• pp.457-461
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• 1998

The vesicle system of DPPC(dipalmitoylphosphaticylcholine)/Chol(Cholesterol) has been modified by incorporating various mole fractions of flourinated surfactant($C_8F_{17}(CH_2)_2OCO-CH_2CH(SO_3Na)COO(CH_2)_2C_8F_{17}$. Sodium bis(1H,1H,2H,2H-heptadecaflurododecyl)-2-sulfosuccinate, FS)/fluorinated fatty acid salt ($C_7F_{15}COONH_4$, ammoniumpentadecaflurooctyrate, FFS), and their physicochemical properties have been investigated in an attempt to enhance the stability of phospholipid vesicle system. The ${\zeta}$-potential measurement by use of Zetamaster sub-micron Particle Electrophoresis Analyzer (Malvern Co.) showed that a charged homogeneous DPPC/Chol/FS vesicle has been formed owing to the incorporated FFS effect on the membrane, playing a role as a cosurfactant in the bilayer between DPPC and FS components. With increase in the concentration of FFS, it was found that the particle size and also surface charge of the DPPC/Chol/FS vesicle decreased. The stability of DPPC/Chol/FS/FFS liposome was found to be enhanced significantly compared to that of DPPC/Chol/FS according to the dispersity change as a function of time. The release rate of dye molecule of Methylene Blue from the DPPC/Chol/FS/FFS vesicle was determined to be slower than that of DPPC/Chol/FS system, and it may be attributed to the increase in microviscosity of the hydrophobic region in the bilayer. The affinfinity of DPPC/Chol/FS/FFS vesicles to albumin was found to be slightly lowered compared to that of DPPC/Chol/FS. Based on these findings, it was confirmed that a more stable and homogeneous vesicle system of DPPC/Chol/FS could be prepared by addition of FFS, acting as a cosurfactant in the aggregate formation.

• Journal of Bio-Environment Control
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• v.25 no.2
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• pp.89-94
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• 2016

This study was conducted to determine the optimum nutrient solution, pH, irrigation interval, light intensity and planting density to growth of common ice plant (Mesembryanthemum crystallinum L.) in a closed-type plant production system. Three-band radiation type fluorescent lamps with a 12-h photoperiod were used. Nutrient film technique systems with three layers were used for the plant growth system. Environmental conditions, such as air temperature, relative humidity and $CO_2$ concentration were controlled by an ON/OFF operation. Treatments were comparison of the nutrient solution of Horticultural Experiment Station in Japan (NHES) and the nutrient solution of Jeju National University (NJNU), pH 6.0 and 7.0, irrigation interval 5 min and 10 min, light intensity 90 and $180{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, and within-row spacing 10 cm, 15 cm, 20 cm and 25 cm with between-row spacing 15 cm. Optimum macronutrients were composed N 7.65, P 0.65, K 4.0, Ca 1.6 and Mg $1.0mM{\cdot}L^{-1}$. There were no significant interactions between pH 6.0 and 7.0 about shoot fresh weight and shoot dry weight of common ice plant. Irrigation interval 5 min and 10 min was also the same result. Shoot fresh weight and shoot dry weight were highest at $180{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$. Shoot fresh weight and shoot dry weight were decreased according to increasing the planting density. From the above results, we concluded that optimum nutrient solution, optimum levels of pH, irrigation interval, light intensity and planting density were 6.0-7.0 and 10 min, $180{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$ and $15{\times}15cm$, respectively for growth of common ice plant in a closed-type plant production system.

• Korean Journal of Ecology and Environment
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• v.52 no.4
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• pp.293-305
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• 2019

In this study we investigated the effect of a floating photovoltaic (FPV) system in Cheongpung Lake on water quality. The FPV with a tilt angle of 33° covered ca. 0.04% of surface area (97 ㎢) of Chungju Lake. The water qualities of the whole lake before and after installation of FPV were first compared. DO, BOD, TOC, and Chl-a of the whole lake were increased, while conductivity decreased after installation period at the significance level of 0.05. This change was probably due to the increased influx of nutrients by 40% resulting from increased precipitation during the same period. We also measured water quality parameters on May and Nov. 2017 at the FPV center (FPVC) and nearby control sites, and compared water quality. The result showed that the FPVC and nearby sites were not significantly different (p>0.05), demonstrating that the FPV does not cause a decline of water quality. The water temperature, light intensity, and phytoplankton community were also measured. The water temperature was not different between the sites, while the light intensity decreased to 27~50%. Despite reduced light intensity at FPVC, the phytoplankton standing crops and the number of species were not significantly different (p>0.05). However, in the early November samples, standing crops was significantly higher in FPVC than control with periphytic diatoms belonging to Aulacoseira genus being dominant. This may be due to the temporal water body behavior or local retention of current by FPV system. This study may provide a measure of future installation of a FPV system.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.80-87
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• 2011

Autonomous underwater vehicles (AUVs) present the important advantage of being able to approach the seafloor more closely than surface vessel surveys can. To collect bathymetric data, bottom material information, and sub-surface images, multibeam echosounder, sidescan sonar (SSS) and subbottom profiler (SBP) equipment mounted on an AUV are powerful tools. The 3000m class AUV URASHIMA was developed by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC). After finishing the engineering development and examination phase of a fuel-cell system used for the vehicle's power supply system, a renovated lithium-ion battery power system was installed in URASHIMA. The AUV was redeployed from its prior engineering tasks to scientific use. Various scientific instruments were loaded on the vehicle, and experimental dives for science-oriented missions conducted from 2006. During the experimental cruise of 2007, high-resolution acoustic images were obtained by SSS and SBP on the URASHIMA around the northern Kumano Basin off Japan's Kii Peninsula. The map of backscatter intensity data revealed many debris objects, and SBP images revealed the subsurface structure around the north-eastern end of our study area. These features suggest a structure related to the formation of the latest submarine fan. However, a strong reflection layer exists below ~20 ms below the seafloor in the south-western area, which we interpret as a denudation feature, now covered with younger surface sediments. We continue to improve the vehicle's performance, and expect that many fruitful results will be obtained using URASHIMA.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.207-228
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• 2007

Measuring Information Technology(IT) organizations' activities have been limited to mainly measure financial indicators for a long time. However, according to the multifarious functions of Information System, a number of researches have been done for the new trends on measurement methodologies that come with financial measurement as well as new measurement methods. Especially, the researches on IT Balanced Scorecard(BSC), concept from BSC measuring IT activities have been done as well in recent years. BSC provides more advantages than only integration of non-financial measures in a performance measurement system. The core of BSC rests on the cause-and-effect relationships between measures to allow prediction of value chain performance measures to allow prediction of value chain performance measures, communication, and realization of the corporate strategy and incentive controlled actions. More recently, BSC proponents have focused on the need to tie measures together into a causal chain of performance, and to test the validity of these hypothesized effects to guide the development of strategy. Kaplan and Norton[2001] argue that one of the primary benefits of the balanced scorecard is its use in gauging the success of strategy. Norreklit[2000] insist that the cause-and-effect chain is central to the balanced scorecard. The cause-and-effect chain is also central to the IT BSC. However, prior researches on relationship between information system and enterprise strategies as well as connection between various IT performance measurement indicators are not so much studied. Ittner et al.[2003] report that 77% of all surveyed companies with an implemented BSC place no or only little interest on soundly modeled cause-and-effect relationships despite of the importance of cause-and-effect chains as an integral part of BSC. This shortcoming can be explained with one theoretical and one practical reason[Blumenberg and Hinz, 2006]. From a theoretical point of view, causalities within the BSC method and their application are only vaguely described by Kaplan and Norton. From a practical consideration, modeling corporate causalities is a complex task due to tedious data acquisition and following reliability maintenance. However, cause-and effect relationships are an essential part of BSCs because they differentiate performance measurement systems like BSCs from simple key performance indicator(KPI) lists. KPI lists present an ad-hoc collection of measures to managers but do not allow for a comprehensive view on corporate performance. Instead, performance measurement system like BSCs tries to model the relationships of the underlying value chain in cause-and-effect relationships. Therefore, to overcome the deficiencies of causal modeling in IT BSC, sound and robust causal modeling approaches are required in theory as well as in practice for offering a solution. The propose of this study is to suggest critical success factors(CSFs) and KPIs for measuring performance for IT organizations and empirically validate the casual relationships between those CSFs. For this purpose, we define four perspectives of BSC for IT organizations according to Van Grembergen's study[2000] as follows. The Future Orientation perspective represents the human and technology resources needed by IT to deliver its services. The Operational Excellence perspective represents the IT processes employed to develop and deliver the applications. The User Orientation perspective represents the user evaluation of IT. The Business Contribution perspective captures the business value of the IT investments. Each of these perspectives has to be translated into corresponding metrics and measures that assess the current situations. This study suggests 12 CSFs for IT BSC based on the previous IT BSC's studies and COBIT 4.1. These CSFs consist of 51 KPIs. We defines the cause-and-effect relationships among BSC CSFs for IT Organizations as follows. The Future Orientation perspective will have positive effects on the Operational Excellence perspective. Then the Operational Excellence perspective will have positive effects on the User Orientation perspective. Finally, the User Orientation perspective will have positive effects on the Business Contribution perspective. This research tests the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares approach to Structural Equation Modeling(or PLS Path Modeling) for analyzing multiple IT BSC CSFs. The PLS path modeling has special abilities that make it more appropriate than other techniques, such as multiple regression and LISREL, when analyzing small sample sizes. Recently the use of PLS path modeling has been gaining interests and use among IS researchers in recent years because of its ability to model latent constructs under conditions of nonormality and with small to medium sample sizes(Chin et al., 2003). The empirical results of our study using PLS path modeling show that the casual effects in IT BSC significantly exist partially in our hypotheses.