• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.29 no.3
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• pp.153-161
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• 2023

The worldwide effects of COVID-19 have led to a surge in online shopping and contactless services. The consumption pattern has caused the issues such as the environmental pollution together with the increase of plastic waste. Reducing the reliance on the petroleum based plastic use for the package and replacing it with environmentally friendly material are the simple ways in order to solve those problems. Paper is an eco-friendly product with high recyclability as the food packaging materials but has still poor barrier properties. A barrier coating on surface of the paper can be achieved with the proper packaging materials featuring water, gas and grease barrier. Polyethylene (PE) or polypropylene (PP) coatings which are generally laminated or coated to paper are widely used in food packaging applications to protect products from moisture and provide water or grease resistance. However, recycling of packaging containing PE or PP matrix is limited and costly because those films are difficult to degrade in the environment. This study investigated the recyclability of modified acrylic emulsion coating papers compared to PE and PP polymer matrixes as well as their mechanical and gas barrier properties. The results showed that PE or modified acrylic emulsion coated papers had better mechanical properties compared to the uncoated paper as a control. PE or PP coating papers showed strong oil resistance property, achieving a kit rating of 12. Those papers also had a significantly higher percentage of screen reject during the recycling process than modified acrylic coated paper which had a screen rejection rate of 6.25%. In addition an uncoated paper had similar value of a screen rejection rate. It may suggest that modified acrylic emulsion coating paper can be more easily recycled than PE or PP coating papers. The overall results of the study found that modified acrylic emulsion coating paper would be a viable alternative to suggest a possible solution to an environmental problem as well as enhancing the weak mechanical and poor gas barrier properties of the paper against moisture.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.4
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• pp.13-28
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• 2023

This study assessed the biochemical methane potential (B_u-P) of three grass species-Poa pratensis (PP), Zoysia japonica (ZJ), and Agrostis stolonifera (AS). B_u-P values were determined as 0.330 Nm³/kg-VS_added for PP, 0.297 Nm³/kg-VS_added for ZJ, and 0.261 Nm³/kg-VS_added for AS. Notably, PP exhibited superior suitability for methane production. The investigation also examined the impact of silage storage duration on PP grass clippings, revealing a 19% decline in B_u-P from an initial value of 0.269 Nm³/kg-VS_added on day 0 to 0.217 Nm³/kg-VS_added on day 180. Throughout the storage period, there were significant increases in neutral detergent fiber (NDF), acid detergent fiber (ADF), and crude protein (CP) contents, rising from 67.59%, 39.68%, and 3.02% on day 0 to 77.12%, 54.65%, and 6.24% on day 180, respectively. These findings highlight the influence of storage duration on the anaerobic digestibility of PP grass clippings. To effectively utilize grass clippings as a renewable resource for methane production, further studies considering factors such as initial moisture content, pretreatment methods, and potential effects of residual pesticides are necessary to optimize anaerobic digestion efficiency for herbaceous biomass.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.229-241
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• 2024

With the advancement of big data processing technology using cloud platforms, access, processing, and analysis of large-volume data such as satellite imagery have recently been significantly improved. In this study, the Change Detection Method, a relatively simple technique for retrieving soil moisture, was applied to the backscattering coefficient values of pre-processed Sentinel-1 synthetic aperture radar (SAR) satellite imagery product based on Google Earth Engine (GEE), one of those platforms, to estimate the surface soil moisture for six observatories within the Yongdam Dam watershed in South Korea for the period of 2015 to 2023, as well as the watershed average. Subsequently, a correlation analysis was conducted between the estimated values and actual measurements, along with an examination of the applicability of GEE. The results revealed that the surface soil moisture estimated for small areas within the soil moisture observatories of the watershed exhibited low correlations ranging from 0.1 to 0.3 for both VH and VV polarizations, likely due to the inherent measurement accuracy of the SAR satellite imagery and variations in data characteristics. However, the surface soil moisture average, which was derived by extracting the average SAR backscattering coefficient values for the entire watershed area and applying moving averages to mitigate data uncertainties and variability, exhibited significantly improved results at the level of 0.5. The results obtained from estimating soil moisture using GEE demonstrate its utility despite limitations in directly conducting desired analyses due to preprocessed SAR data. However, the efficient processing of extensive satellite imagery data allows for the estimation and evaluation of soil moisture over broad ranges, such as long-term watershed averages. This highlights the effectiveness of GEE in handling vast satellite imagery datasets to assess soil moisture. Based on this, it is anticipated that GEE can be effectively utilized to assess long-term variations of soil moisture average in major dam watersheds, in conjunction with soil moisture observation data from various locations across the country in the future.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.56-76
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• 2024

We for the first time made a successful longest continuous sectional observation in the East Sea by an underwater glider during 95 days from September 18 to December 21 2020 in the Korea along the 106 Line (129.1 °E ~ 131.5 °E at 37.9 °N) of the regular shipboard measurements by the National Institute of Fishery Science (NIFS) and obtained twelve hydrographic sections with high spatiotemporal resolution. The glider was deployed at 129.1 °E in September 18 and conducted 88-days flight from September 19 to December 15 2020, yielding twelve hydrographic sections, and then recovered at 129.2 °E in December 21 after the last 6 days virtual mooring operation. During the total traveled distance of 2550 km, the estimated deviation from the predetermined zonal path had an average RMS distance of 262 m. Based on these high-resolution long-term glider measurements, we conducted a comparative study with the bi-monthly NIFS measurements in terms of spatial and temporal resolutions, and found distinguished features. One is that spatial features of sub-mesoscale such as sub-mesoscale frontal structure and intensified thermocline were detected only in the glider measurements, mainly due to glider's high spatial resolution. The other is the detection of intramonthly variations from the weekly time series of temperature and salinity, which were extracted from glider's continuous sections. Lastly, there were deviations and bias in measurements from both platforms. We argued these deviations in terms of the time scale of variation, the spatial scale of fixed-point observation, and the calibration status of CTD devices of both platforms.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.28-41
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• 2024

The carbon balance serves as a valuable indicator of a plant's physiological status under diverse environmental conditions. We investigated the photosynthetic and respiratory responses of the Asian surfgrass Phyllospadix iwatensis along the northeast coast of the Korean peninsula in response to changing water temperature (ranging from 5℃ to 30℃) to estimate the seasonal whole-plant carbon balance through a series of incubation experiments. The maximum gross photosynthetic rate (P_max) showed a significant difference among the temperature treatments, while there was no significant difference in photosynthetic efficiency (α). The maximum gross photosynthetic rate of P. iwatensis reached its peaks at 20℃ treatment (101.65 μmol O₂ g^-1 DW h^-1) but decreased rapidly at 30℃. The saturation irradiance (I_k), compensation irradiance (I_c), and respiration rate (R) of P. iwatensis exhibited significant differences among the temperature treatments. The saturation irradiance increased up to 20-25℃ (121.59-124.50 μmol photons m^-2 s^-1) and sharply decreased at 30℃. The compensation irradiance and respiration rate increased steadily with rising water temperature. The ratio of P_max to R (P_max:R ratio) was the highest at 5℃ but dramatically decreased at 30℃. The whole-plant carbon balance, calculated based on photosynthetic parameters, respiration rates, and biomass, exhibited distinct seasonal variation, increasing during winter and spring and decreasing during summer and fall, which is consistent with the highest in situ growth in spring and severely limited growth at the highest water temperature conditions. Phyllospadix iwatensis displayed a negative carbon balance during late summer, fall, and winter, but demonstrated a positive carbon balance during spring and early summer. Our findings suggest that the rising seawater temperatures associated with climate change may lead to significant alterations in the seagrass ecosystem functioning along the rocky shores of the Korean east coast.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Tuberculosis and Respiratory Diseases
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• v.42 no.3
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• pp.351-360
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• 1995

Background: Pressure support(PS) is becomimg a widely accepted method of mechanical ventilation either for total unloading or for partial unloading of respiratory muscle. The aim of the study was to find out if PS exert different effects on respiratory mechanics in synchronized intermittent mandatory ventilation(SIMV) and continuous positive airway pressure (CPAP) modes. Methods: 5, 10 and 15 cm $H_2O$ of PS were sequentially applied in 14 patients($69{\pm}12$ yrs, M:F=9:5) and respiratory rate (RR), tidal volume($V_T$), work of breathing(WOB), pressure time product(PTP), $P_{0.1}$, and $T_1/T_{TOT}$ were measured using the CP-100 pulmonary monitor(Bicore, USA) in SIMV and CPAP modes respectively. Results: 1) Common effects of PS on respiratory mechanics in both CPAP and SIMV modes As the level of PS was increased(0, 5, 10, 15 cm $H_2O$), $V_T$ was increased in CPAP mode($0.28{\pm}0.09$, $0.29{\pm}0.09$, $0.31{\pm}0.11$, $0.34{\pm}0.12\;L$, respectively, p=0.001), and also in SIMV mode($0.31{\pm}0.15$, $0.32{\pm}0.09$, $0.34{\pm}0.16$, $0.36{\pm}0.15\;L$, respectively, p=0.0215). WOB was decreased in CPAP mode($1.40{\pm}1.02$, $1.01{\pm}0.80$, $0.80{\pm}0.85$, $0.68{\pm}0.76$ joule/L, respectively, p=0.0001), and in SIMV mode($0.97{\pm}0.77$, $0.76{\pm}0.64$, $0.57{\pm}0.55$, $0.49{\pm}0.49$ joule/L, respectively, p=0.0001). PTP was also decreased in CPAP mode($300{\pm}216$, $217{\pm}165$, $179{\pm}187$, $122{\pm}114cm$ $H_2O{\cdot}sec/min$, respectively, p=0.0001), and in SIMV mode($218{\pm}181$, $178{\pm}157$, $130{\pm}147$, $108{\pm}129cm$ $H_2O{\cdot}sec/min$, respectively, p=0.0017). 2) Different effects of PS on respiratory mechanics in CP AP and SIMV modes By application of PS (0, 5, 10, 15 cm $H_2O$), RR was not changed in CPAP mode($27.9{\pm}6.7$, $30.0{\pm}6.6$, $26.1{\pm}9.1$, $27.5{\pm}5.7/min$, respectively, p=0.505), but it was decreased in SIMV mode ($27.4{\pm}5.1$, $27.8{\pm}6.5$, $27.6{\pm}6.2$, $25.1{\pm}5.4/min$, respectively, p=0.0001). $P_{0.1}$ was reduced in CPAP mode($6.2{\pm}3.5$, $4.8{\pm}2.8$, $4.8{\pm}3.8$, $3.9{\pm}2.5\;cm$ $H_2O$, respectively, p=0.0061), but not in SIMV mode($4.3{\pm}2.1$, $4.0{\pm}1.8$, $3.5{\pm}1.6$, $3.5{\pm}1.9\;cm$ $H_2O$, respectively, p=0.054). $T_1/T_{TOT}$ was decreased in CPAP mode($0.40{\pm}0.05$, $0.39{\pm}0.04$, $0.37{\pm}0.04$, $0.35{\pm}0.04$, respectively, p=0.0004), but not in SIMV mode($0.40{\pm}0.08$, $0.35{\pm}0.07$, $0.38{\pm}0.10$, $0.37{\pm}0.10$, respectively, p=0.287). 3) Comparison of respiratory mechanics between CPAP+PS and SIMV alone at same tidal volume. The tidal volume in CPAP+PS 10 cm $H_2O$ was comparable to that of SIMV alone. Under this condition, the RR($26.1{\pm}9.1$, $27.4{\pm}5.1/min$, respectively, p=0.516), WOB($0.80{\pm}0.85$, 0.97+0.77 joule/L, respectively, p=0.485), $P_{0.1}$($3.9{\pm}2.5$, $4.3{\pm}2.1\;cm$ $H_2O$, respectively, p=0.481) were not different between the two methods, but PTP($179{\pm}187$, $218{\pm}181 cmH_2O{\cdot}sec/min$, respectively, p=0.042) and $T_1/T_{TOT}$($0.37{\pm}0.04$, $0.40{\pm}0.08$, respectively, p=0.026) were significantly lower in CPAP+PS than in SIMV alone. Conclusion: PS up to 15 cm $H_2O$ increased tidal volume, decreased work of breathing and pressure time product in both SIMV and CPAP modes. PS decreased respiration rate in SIMV mode but not in CPAP mode, while it reduced central respiratory drive($P_{0.1}$) and shortened duty cycle ($T_1/T_{TOT}$) in CPAP mode but not in SIMV mode. By 10 em $H_2O$ of PS in CPAP mode, same tidal volume was obtained as in SIMV mode, and both methods were comparable in respect to RR, WOB, $P_{0.1}$, but CPAP+PS was superior in respect to the efficiency of the respiratory muscle work (PTP) and duty cycle($T_1/T_{TOT}$).

• Journal of Oral Medicine and Pain
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• v.32 no.2
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• pp.157-175
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• 2007

This study was conducted through an interview process in which questionnaires were administered to 293 people. The questionnaires related to the behaviors of oral hygiene care, and disease history related to halitosis, and status of halitosis, halitosis measurement, oral examination, and caries activity tests such as the snyder test, Salivary flow rate test, and Salivary buffering capacity test. Our sample was taken from 293 rural residents within the period from 4th to 21st of January 2006. This was done in order to provide basic data to prepare both policies of halitosis prevention and a device to efficiently measure halitosis status and investigate the factors related therein. The major findings of this study results are as follows: 1. As for frequency of tooth brushing, twice a day occupied the greatest portion at 46.1 % Women exceeded men in frequency of tooth brushing. Tongue brushing everyday produced a 25.6 % result among subjects and The use of auxiliary oral hygiene devices occupied 9.2 %. 2. As for degree of usual self-awareness of halitosis: 62.5 %. This result also demonstrate that the severest time of self-awareness in regards to halitosis is wake up time in the morning. The time period produced the highest portion of 72.7 % in times of self-awareness. In terms of the area in which halitosis was observed, gum resulted in 23.0 %. As for types of halitosis, fetid smell was the most frequent at 37.2 %. 3. As for the result of halitosis measurement, values of OG less than 50 ppm occupied 54.3 % and $50{\sim}100ppm$ occupied 41.6 %. As for $NH_3$ values, $20{\sim}60ppm$ showed the highest value range of 52.6 %. 4. As for OG per disease history related to halitosis, values of OG were significantly high in the ranges of $50{\sim}100ppm$ within family history groups of food impaction by dental caries, diabetes mellitus and halitosis. As for values of $NH_3$, there showed a significant difference in respiratory system disease groups. 5 Value range of OG per ordinary halitosis self-awareness degree: values ranging less than 50 ppm were recorded at 55.9 % from the group realizing not aware of smell. 57.5 % from groups only realizing sometimes, while values range of $50{\sim}100ppm$ were recorded at 52.0 % from groups always aware of smell. 63.6 % from groups always strongly aware of smell. Meanwhile as for the values ranges of $NH_3$, $20{\sim}60ppm$. they occupied high portions for all groups of exams. 6. Values of OG per oral examination: the more pulp-exposed teeth and food impaction and the higher the tongue plaque index, values of OG increased within the range of $50{\sim}100ppm$. As for values of $NH_3$, the more prosthetic teeth and the higher the tongue plaque index, this value increased significantly, and the values increased up to no less than 60 ppm for groups of mandibular partial denture. 7. Within the realm of caries activity test: as for the Snyder test, high activity was highest by 43.0 % wherewith the higher the activity of acidogenic bacteria the higher the OG values. As for the salivary flow rate test, the number of cases below 8.0 ml showed the highest tendency by 62.5 %. The larger the salivary flow rate the more decreased OG values distribution. As for the salivary buffering capacity test, $6{\sim}10$ drops of 0.1N lactic acid showed the overwhelming trend by 58.7 % whereby the higher the salivary buffering capacity the greater distribution occupancy ratio of OG values below 50 ppm which is scentless to on ordinary person. 8. As for the correlation between oral environment and halitosis, OG showed the positive correlation with pulp exposed teeth, filled teeth, present teeth, tongue plaque index, and food impaction, while the negative correlation with salivary flow rate and prosthetic teeth. $NH_3$ showed a positive correlation with prosthetic teeth and frequency of tooth brushing, while decayed teeth was negative correlation. 9. As for the multiple regression analysis result, there have been selected female, pulp exposed teeth, prosthetic teeth, food impaction, salivary flow rate, tongue plaque index and severe activities in the Snyder test as factors affecting OG wherein explanatory power on it was 45.1 %. There have been selected females, pulp exposed teeth, tongue plaque index, and prosthetic teeth as factors affecting on $NH_3$ wherein explanatory power on it was 6.6 %. With the aforementioned results in mind, the status of halitosis among rural residents is considered to bare a close relation with oral environments and other factors related to halitosis such as the Snyder test from caries activity test, and salivary flow rate test. For the prevention of halitosis of residents in rural areas, we have to focus on correct tooth brushing methods and tongue brushing, with using auxiliary oral hygiene devices to remove fur of tongue plaque and food impaction. Also, when the cause and ingredients of halitosis are diverse and complex, in order to analyze exactly the factors of individual halitosis development, we need continuous and systematic study in order to provide rural residents with programs of oral hygiene education and encourage the use of dental hygienists in public health centers.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.3
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• pp.234-240
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• 2007

Purpose: In this study we propose a block-iterative method for reconstructing Compton scattered data. This study shows that the well-known expectation maximization (EM) approach along with its accelerated version based on the ordered subsets principle can be applied to the problem of image reconstruction for Compton camera. This study also compares several methods of constructing subsets for optimal performance of our algorithms. Materials and Methods: Three reconstruction algorithms were implemented; simple backprojection (SBP), EM, and ordered subset EM (OSEM). For OSEM, the projection data were grouped into subsets in a predefined order. Three different schemes for choosing nonoverlapping subsets were considered; scatter angle-based subsets, detector position-based subsets, and both scatter angle- and detector position-based subsets. EM and OSEM with 16 subsets were performed with 64 and 4 iterations, respectively. The performance of each algorithm was evaluated in terms of computation time and normalized mean-squared error. Results: Both EM and OSEM clearly outperformed SBP in all aspects of accuracy. The OSEM with 16 subsets and 4 iterations, which is equivalent to the standard EM with 64 iterations, was approximately 14 times faster in computation time than the standard EM. In OSEM, all of the three schemes for choosing subsets yielded similar results in computation time as well as normalized mean-squared error. Conclusion: Our results show that the OSEM algorithm, which have proven useful in emission tomography, can also be applied to the problem of image reconstruction for Compton camera. With properly chosen subset construction methods and moderate numbers of subsets, our OSEM algorithm significantly improves the computational efficiency while keeping the original quality of the standard EM reconstruction. The OSEM algorithm with scatter angle- and detector position-based subsets is most available.