• Knowledge Management Research
• /
• v.24 no.4
• /
• pp.23-42
• /
• 2023

This study originated from recognition of importance of firefighters' decision-making in fire response, coupled with existing gap in research. By utilizing Q-methodology, the study aimed to categorize firefighters' subjectivity in fire response decision-making. Through this categorization, the study sought to highlight insights into the current technological and data limitations, as well as potential directions for future R&D in the field of firefighting. The findings of the study revealed that firefighters' subjectivity could be classified into three factors: "emphasis on direct information related to rescue," "emphasis on information related to the target property," and "emphasis on information related to command and coordination." The study theoretically confirmed that the subjectivity of firefighters' decision-making in fire response is partially influenced by their experiences and job. Additionally, the study's significance lay in its approach of collecting specific decision-making factors in fire response, moving beyond general theoretical models. Furthermore, from a policy perspective, the typification of decision-making factors contributed to connecting the identified data-based administrative needs from prior studies. Insights from the study emphasized the importance of leveraging on-site experience in Korea to aid decision-making, calling for the development of equipment and data collection methods that can rapidly and accurately assess on-site conditions.

• The Journal of Korean Society for Radiation Therapy
• /
• v.25 no.2
• /
• pp.167-173
• /
• 2013

Purpose: This study is to evaluate the efficacy of the CBCT and EXACTRAC the image on the spine stereotactic body radiation treatment. Materials and Methods: The study compared the accuracy of the dose distribution for changes in the real QA phantom for The shape of the body of the phantom was performed. Novalis treatment artificially set up at the center and to the right, on the Plan 1 mm, 2 mm, 3 mm in front 1 mm, 2 mm, 3 mm and upwards 1 mm, 2 mm, 3 mm and $0.5^{\circ}$ by moving side to side Exactrac error correction and error values of CBCT and plan changes on the dose distribution were recorded and analyzed. Results: Cubic Phantom of the experimental error, the error correction Exactrac X-ray 6D Translation in the direction of the 0.18 mm, Rotation direction was $0.07^{\circ}$. Translation in the direction of the 3D CBCT 0.15 mm Rotation direction was $0.04^{\circ}$. DVH dose distribution using the results of the AP evaluate the change in the direction of change was greatest when moving. Conclusion: ExacTrac image-guided radiation therapy with a common easy and fast to get pictures from all angles, from the advantage of CBCT showed a potential alternative. But every accurate information compared with CT treatment planning and treatment of patients with more accurate than the CBCT ExacTrac the location provided. Changes in the dose distribution in the experiment results show that the treatment of spinal SBRT set up some image correction due to errors at the target and enter the spinal cord dose showed that significant differences appear.

• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.1-31
• /
• 2017

Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.19-28
• /
• 2012

After the internet era, we are moving to the ubiquitous society. Nowadays the people are interested in the multimodal interaction technology, which enables audience to naturally interact with the computing environment at the exhibitions such as gallery, museum, and park. Also, there are other attempts to provide additional service based on the location information of the audience, or to improve and deploy interaction between subjects and audience by analyzing the using pattern of the people. In order to provide multimodal interaction service to the audience at the exhibition, it is important to distinguish the individuals and trace their location and route. For the location tracking on the outside, GPS is widely used nowadays. GPS is able to get the real time location of the subjects moving fast, so this is one of the important technologies in the field requiring location tracking service. However, as GPS uses the location tracking method using satellites, the service cannot be used on the inside, because it cannot catch the satellite signal. For this reason, the studies about inside location tracking are going on using very short range communication service such as ZigBee, UWB, RFID, as well as using mobile communication network and wireless lan service. However these technologies have shortcomings in that the audience needs to use additional sensor device and it becomes difficult and expensive as the density of the target area gets higher. In addition, the usual exhibition environment has many obstacles for the network, which makes the performance of the system to fall. Above all these things, the biggest problem is that the interaction method using the devices based on the old technologies cannot provide natural service to the users. Plus the system uses sensor recognition method, so multiple users should equip the devices. Therefore, there is the limitation in the number of the users that can use the system simultaneously. In order to make up for these shortcomings, in this study we suggest a technology that gets the exact location information of the users through the location mapping technology using Wi-Fi and 3d camera of the smartphones. We applied the signal amplitude of access point using wireless lan, to develop inside location tracking system with lower price. AP is cheaper than other devices used in other tracking techniques, and by installing the software to the user's mobile device it can be directly used as the tracking system device. We used the Microsoft Kinect sensor for the 3D Camera. Kinect is equippedwith the function discriminating the depth and human information inside the shooting area. Therefore it is appropriate to extract user's body, vector, and acceleration information with low price. We confirm the location of the audience using the cell ID obtained from the Wi-Fi signal. By using smartphones as the basic device for the location service, we solve the problems of additional tagging device and provide environment that multiple users can get the interaction service simultaneously. 3d cameras located at each cell areas get the exact location and status information of the users. The 3d cameras are connected to the Camera Client, calculate the mapping information aligned to each cells, get the exact information of the users, and get the status and pattern information of the audience. The location mapping technique of Camera Client decreases the error rate that occurs on the inside location service, increases accuracy of individual discrimination in the area through the individual discrimination based on body information, and establishes the foundation of the multimodal interaction technology at the exhibition. Calculated data and information enables the users to get the appropriate interaction service through the main server.

• Progress in Medical Physics
• /
• v.25 no.2
• /
• pp.79-88
• /
• 2014

The dose distributions within the real volumes of tumor targets and critical organs during internal target volume-based intensity-modulated radiation therapy (ITV-IMRT) for liver cancer were recalculated by applying the effects of actual respiratory organ motion, and the dosimetric features were analyzed through comparison with gating IMRT (Gate-IMRT) plan results. The ITV was created using MIM software, and a moving phantom was used to simulate respiratory motion. The doses were recalculated with a 3 dose-volume histogram (3DVH) program based on the per-field data measured with a MapCHECK2 2-dimensional diode detector array. Although a sufficient prescription dose covered the PTV during ITV-IMRT delivery, the dose homogeneity in the PTV was inferior to that with the Gate-IMRT plan. We confirmed that there were higher doses to the organs-at-risk (OARs) with ITV-IMRT, as expected when using an enlarged field, but the increased dose to the spinal cord was not significant and the increased doses to the liver and kidney could be considered as minor when the reinforced constraints were applied during IMRT plan optimization. Because the Gate-IMRT method also has disadvantages such as unsuspected dosimetric variations when applying the gating system and an increased treatment time, it is better to perform a prior analysis of the patient's respiratory condition and the importance and fulfillment of the IMRT plan dose constraints in order to select an optimal IMRT method with which to correct the respiratory organ motional effect.

• The Journal of Korean Society for Radiation Therapy
• /
• v.26 no.2
• /
• pp.289-295
• /
• 2014

Purpose : Cone Beam Computed Tomography(CBCT) in Image Guided Radiation Therapy(IGRT), Set-up error can be reduced but exposure dose of the patient due to CBCT will increase. Through this study, we are to evaluate by making a scenario with the implementation period of CBCT as every other day. Materials and Methods : Of prostate cancer patients, 9 patients who got a Intensity Modulated Radiation Therapy(IMRT) with CBCT in IGRT were analyzed. Based on values corrected by analyzing set-up error by using CBCT every day during actual treatment, we created a scenario that conducts CBCT every other day. After applying set-up error values of the day not performing CBCT in the scenario to the treatment planning system(Pinnacle 9.2, Philips, USA) by moving them from the treatment iso-center during actual treatment, we established re-treatment plan under the same conditions as actual treatment. Based on this, the dose distribution of normal organs and Planning Target Volume(PTV) was compared and analyzed. Results : In the scenario that performs CBCT every other day based on set-up error values when conducting CBCT every day, average X-axis : $0.2{\pm}0.73mm$, Y-axis : $0.1{\pm}0.58mm$, Z-axis : $-1.3{\pm}1.17mm$ difference was shown. This was applied to the treatment planning to establish re-treatment plan and dose distribution was evaluated and as a result, Dmean : -0.17 Gy, D99% : -0.71 Gy of PTV difference was shown in comparison with the result obtained when carrying out CBCT every day. As for normal organs, V66 : 1.55% of rectal wall, V66 : -0.76% of bladder difference was shown. Conclusion : In case of a CBCT perform every other day could reduce exposure dose and additional treatment time. And it is thought to be able to consider the application depending on the condition of the patient because the difference in the dose distribution of normal organs, PTV is not large.

• Journal of Intelligence and Information Systems
• /
• v.28 no.1
• /
• pp.69-88
• /
• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Progress in Medical Physics
• /
• v.17 no.3
• /
• pp.136-143
• /
• 2006

The respiratory gating radiation therapy which Irradiates only in the stable respiratory period with analyzing the periodic motion of a reflective marker on the patient's abdomen has been applied to the precise radiation treatment in order to minimize the effect of organ motion induced by the respiration. This respiratory gating system establishes irradiation region using the amplitude-based or phase-based method. Although phase-based method Is preferred because of the stability in the real treatment conditions, it has some limits to explain the exact correlation between the marker motion and organ motion. Even when the variation of amplitude which can introduce target motion considered as an error is produced, the phase-based method has the possibility to irradiate including the error positions. In this study, the error analysis program was developed for the verification of the tumor position's variation correlated with the variation of marker's amplitude which can be occurred during a phase-based respiratory sating treatment. The analysis program was tested with a virtual treatment record file and with a record file using moving phantom which were modified considering the irregular amplitude's variation simulating the real clinical situations. In both cases, accurate discrimination of error points and error calculation were produced. When the treatment record files of a real patient were analyzed with the program, the accurate recognition and calculation of the error points were also verified. The analysis program developed in this study will be applied as a useful tool for the analysis of errors due to the irregular variation of patients' respiration during the phase-base respiratory gating radiation treatment.

• Progress in Medical Physics
• /
• v.26 no.4
• /
• pp.258-266
• /
• 2015

The modern radiotherapy technique which delivers a large amount of dose to patients asks to confirm the positions of patients or tumors more accurately by using X-ray projection images of high-definition. However, a rapid increase in patient's exposure and image information for CT image acquisition may be additional burden on the patient. In this study, by introducing structural similarity (SSIM) index that can effectively extract the structural information of the image, we analyze the differences between daily acquired x-ray images of a patient to verify the accuracy of patient positioning. First, for simulating a moving target, the spherical computational phantoms changing the sizes and positions were created to acquire projected images. Differences between the images were automatically detected and analyzed by extracting their SSIM values. In addition, as a clinical test, differences between daily acquired x-ray images of a patient for 12 days were detected in the same way. As a result, we confirmed that the SSIM index was changed in the range of 0.85~1 (0.006~1 when a region of interest (ROI) was applied) as the sizes or positions of the phantom changed. The SSIM was more sensitive to the change of the phantom when the ROI was limited to the phantom itself. In the clinical test, the daily change of patient positions was 0.799~0.853 in SSIM values, those well described differences among images. Therefore, we expect that SSIM index can provide an objective and quantitative technique to verify the patient position using simple x-ray images, instead of time and cost intensive three-dimensional x-ray images.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.40 no.5
• /
• pp.312-321
• /
• 2003

In this paper, we implement robot which are ability to recognize obstacles and moving automatically to destination. we present two results in this paper; hardware implementation of image processing board and software implementation of visual feedback algorithm for a self-controlled robot. In the first part, the mobile robot depends on commands from a control board which is doing image processing part. We have studied the self controlled mobile robot system equipped with a CCD camera for a long time. This robot system consists of a image processing board implemented with DSPs, a stepping motor, a CCD camera. We will propose an algorithm in which commands are delivered for the robot to move in the planned path. The distance that the robot is supposed to move is calculated on the basis of the absolute coordinate and the coordinate of the target spot. And the image signal acquired by the CCD camera mounted on the robot is captured at every sampling time in order for the robot to automatically avoid the obstacle and finally to reach the destination. The image processing board consists of DSP (TMS320VC33), ADV611, SAA7111, ADV7l76A, CPLD(EPM7256ATC144), and SRAM memories. In the second part, the visual feedback control has two types of vision algorithms: obstacle avoidance and path planning. The first algorithm is cell, part of the image divided by blob analysis. We will do image preprocessing to improve the input image. This image preprocessing consists of filtering, edge detection, NOR converting, and threshold-ing. This major image processing includes labeling, segmentation, and pixel density calculation. In the second algorithm, after an image frame went through preprocessing (edge detection, converting, thresholding), the histogram is measured vertically (the y-axis direction). Then, the binary histogram of the image shows waveforms with only black and white variations. Here we use the fact that since obstacles appear as sectional diagrams as if they were walls, there is no variation in the histogram. The intensities of the line histogram are measured as vertically at intervals of 20 pixels. So, we can find uniform and nonuniform regions of the waveforms and define the period of uniform waveforms as an obstacle region. We can see that the algorithm is very useful for the robot to move avoiding obstacles.