• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.12 s.354
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• pp.31-41
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• 2006

Internet access from mobile phones over cellular networks suffer from severe bandwidth limitations and high bit error rates over wireless access links. Tailoring TCP connections to best fit the characteristics of this bottleneck link is thus very important for overall performance improvement. In this work, we propose a simple algorithm in deciding the optimal TCP segment size to maximize the utilization of the bottleneck wireless TCP connection for mobile contents server access, taking the dynamic TCP window variation into account. The proposed algorithm can be used when the product of the access rate and the propagation time is not large. With some numerical examples, it is shown that the optimal TCP segment size becomes a constant value when the TCP window size exceeds a threshold. One can set the maximum segment size of a wireless TCP connection to this optimal segment size for mobile contents server access for maximum efficiency on the expensive wireless link.

• Journal of the Korean Society of School Health
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• v.28 no.3
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• pp.139-149
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• 2015

Purpose: This study aims to analyze the factors affecting the agenda-setting process and the formation process of school-based mental health policies by applying a policy stream model. Methods: For this purpose, Kingdon's policy stream model was used as the analytical framework. Results: First, when establishing a school-based mental health policy, the agenda was set going through unpredictable and nonlinear changes. Second, for the school-based mental health policy to be selected onto the agenda and to be developed and implemented as an actual policy, the role of policy makers was considered most important in the process. Third, the policy window for school-based mental health policy was closed around the year 2013. Finally, an analysis of the school-based mental health policy stream identified two key features. One is that the school-based mental health policy first emerged when school violence prevention policy expanded its scope into relevant neighboring policies. The other is that the school-based mental health policy has taken shape through a linear decision-making process (being put on the government's agenda, searching for an alternative, selection, and implementation) during the policy implementation period after it has been selected as an alternative policy. Conclusion: Conclusions can be summed up as follows. The school-based mental health policy needs continuous development and improvement in case the window for the policy may open in the coming future. The government's support is needed to draw policy makers' interest and participation who play the biggest role in establishing policies.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.149-156
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• 2019

The existing subtract image based intrusion detection system for CCTV digital images has a problem that it can not distinguish intruders from moving backgrounds that exist in the natural environment. In this paper, we tried to solve the problems of existing system by designing real - time intrusion detection system for CCTV digital image by combining subtract image based intrusion detection method and background learning artificial neural network technology. Our proposed system consists of three steps: subtract image based intrusion detection, background artificial neural network learning stage, and background artificial neural network evaluation stage. The final intrusion detection result is a combination of result of the subtract image based intrusion detection and the final intrusion detection result of the background artificial neural network. The step of subtract image based intrusion detection is a step of determining the occurrence of intrusion by obtaining a difference image between the background cumulative average image and the current frame image. In the background artificial neural network learning, the background is learned in a situation in which no intrusion occurs, and it is learned by dividing into a detection window unit set by the user. In the background artificial neural network evaluation, the learned background artificial neural network is used to produce background recognition or intrusion detection in the detection window unit. The proposed background learning intrusion detection system is able to detect intrusion more precisely than existing subtract image based intrusion detection system and adaptively execute machine learning on the background so that it can be operated as highly practical intrusion detection system.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.27-37
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• 2020

The Fukushima Daiichi accident in 2011 revealed some vulnerabilities of existing Nuclear Power Plants (NPPs) under extended Station Blackout (SBO) accident conditions. One of the key Severe Accident Management (SAM) strategies developed post Fukushima accident is the In-Vessel Retention (IVR) Strategy which aims to retain the structural integrity of the Reactor Pressure Vessel (RPV). RELAP/SCDAPSIM/MOD3.4 is selected to predict the thermal-hydraulic response of APR1400 undergoing an extended SBO. To assess the effectiveness of the IVR strategy, it is essential to quantify the underlying uncertainties. In this work, both the epistemic and aleatory uncertainties are considered to identify the success window of the IVR strategy. A set of in-vessel relevant phenomena were identified based on Phenomena Identification and Ranking Tables (PIRT) developed for severe accidents and propagated through the thermal-hydraulic model using Wilk's sampling method. For this work, a Systems Engineering (SE) approach is applied to facilitate the development process of assessing the reliability and robustness of the APR1400 IVR strategy. Specifically, the Kossiakoff SE method is used to identify the requirements, functions and physical architecture, and to develop a design verification and validation plan. Using the SE approach provides a systematic tool to successfully achieve the research goal by linking each requirement to a verification or validation test with predefined success criteria at each stage of the model development. The developed model identified the conditions necessary for successful implementation of the IVR strategy which maintains the vessel integrity and prevents a melt-through.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.101-107
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• 2014

With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.2
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• pp.68-73
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• 2015

Purpose The purpose of this study was to evaluate image quality change by truncated region in field of view (FOV) of attenuation correction computed tomography (AC-CT) in brain PET/CT. Materials and Methods Biograph Truepoint 40 with TrueV (Siemens) was used as a scanner. $^{68}Ge$ phantom scan was performed with and without applying brain holder using brain PET/CT protocol. PET attenuation correction factor (ACF) was evaluated according to existence of pallet in FOV of AC-CT. FBP, OSEM-3D and PSF methods were applied for PET reconstruction. Parameters of iteration 4, subsets 21 and gaussian 2 mm filter were applied for iterative reconstruction methods. Window level 2900, width 6000 and level 4, 200, width 1000 were set for visual evaluation of PET AC images. Vertical profiles of 5 slices and 20 slices summation images applied gaussian 5 mm filter were produced for evaluating integral uniformity. Results Patient pallet was not covered in FOV of AC-CT when without applying brain holder because of small size of FOV. It resulted in defect of ACF sinogram by truncated region in ACF evaluation. When without applying brain holder, defect was appeared in lower part of transverse image on condition of window level 4200, width 1000 in PET AC image evaluation. With and without applying brain holder, integral uniformities of 5 slices and 20 slices summation images were 7.2%, 6.7% and 11.7%, 6.7%. Conclusion Truncated region by small FOV results in count defect in occipital lobe of brain in clinical or research studies. It is necessary to understand effect of truncated region and apply appropriate accessory for brain PET/CT.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.663-669
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• 2014

The electrical characteristics of RRAM with different annealing temperature and thickness have been measured and discussed. The devices with Pt/Ti top electrode of 150nm, Pt bottom electrode of 150nm, $HfO_2$ oxide thickness of 45nm and 70nm have been fabricated. The fabricated device were classified by 3 different kinds according to the annealing temperature, such as non-annealed, annealed at $500^{\circ}C$ and annealed at $850^{\circ}C$. The set and reset voltages and the variation of resistance with temperatures have been measured as electrical properties. From the measurement, it was found that the set voltages were decreased and the reset voltage were increased slightly, and thus the sensing window was decreased with increasing of measurement temperatures. It was remarkable that the device annealed at $850^{\circ}C$ showed the best performances. Although the device with thickness of 45nm showed better performances in the point of the sensing window, the resistance of 45nm devices was large relatively in the low resistive state. It can be expected to enhance the device performances with ultra thin RRAM if the defect generation could be reduced at the $HfO_2$ deposition process.

• Journal of The Korea Institute of Healthcare Architecture
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• v.27 no.3
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• pp.71-78
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• 2021

Purpose: It is important to plan the ward module at a time when the size of beds, the floor area, and the construction budget are all set prior to the hospital design. In this context this study aims (1) to derive various factors affecting the ward module, and (2) to analyze the appropriate room module according to the type. Methods: Design factors related to hospital modules are derived through precedential studies, and the types of ward elevation are classified by reviewing the drawings of 18 case hospitals. And the detailed dimensions and area of the derived elements are analyzed. Results: The X-axis modules of the ward are switched to long span structural columns of 9.9 m, 12.6 m and 13.2 m, but the ward modules still represent 6.6 m. The Y-axis module of the ward shows a dimension of 9 to 9.9m in the process of changing a multi-person room into a four-person room. Type A of curtain wall with columns located on the wall of the room and type B of curtain wall located in the center of the room are analyzed due to their variations. The square window type, which forms the elevation of the square window by exposing the columns to the elevation, and the outframe type, which protrudes from the structural columns and beams, have elevation designs limited. There are, however, no obstacles to the interior space of the hospital room, so the wall composition and furniture arrangement are expected to be free. The ward area of Curtain Wall Type A, which can secure an effective area of 5.9m*5.0m, are 52.1m². The Curtain Wall Type A, Square window type, and the outframe type are 49.8m². Implications: As part of the hospital standard module plan for economical and reasonable hospital building planning, a type was proposed in this study in conjunction with the external design. It is hoped that it be a base for standard module research linked together to the Central Treatment department, Outpatient department and underground parking lot.

• Progress in Medical Physics
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• v.9 no.3
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• pp.163-173
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• 1998

Nuclear medicine emission computed tomography(ECT) can be very useful to diagnose early stage of neuronal diseases and to measure theraputic results objectively, if we can quantitate energy metabolism, blood flow, biochemical processes, or dopamine receptor and transporter using ECT. However, physical factors including attenuation, scatter, partial volume effect, noise, and reconstruction algorithm make it very difficult to quantitate independent of type of SPECT. In this study, we quantitated the effects of attenuation and scatter using brain SPECT and three-dimensional brain phantom with and without applying their correction methods. Dual energy window method was applied for scatter correction. The photopeak energy window and scatter energy window were set to 140ke${\pm}$10% and 119ke${\pm}$6% and 100% of scatter window data were subtracted from the photopeak window prior to reconstruction. The projection data were reconstructed using Butterworth filter with cutoff frequency of 0.95cycles/cm and order of 10. Attenuation correction was done by Chang's method with attenuation coefficients of 0.12/cm and 0.15/cm for the reconstruction data without scatter correction and with scatter correction, respectively. For quantitation, regions of interest (ROIs) were drawn on the three slices selected at the level of the basal ganglia. Without scatter correction, the ratios of ROI average values between basal ganglia and background with attenuation correction and without attenuation correction were 2.2 and 2.1, respectively. However, the ratios between basal ganglia and background were very similar for with and without attenuation correction. With scatter correction, the ratios of ROI average values between basal ganglia and background with attenuation correction and without attenuation correction were 2.69 and 2.64, respectively. These results indicate that the attenuation correction is necessary for the quantitation. When true ratios between basal ganglia and background were 6.58, 4.68, 1.86, the measured ratios with scatter and attenuation correction were 76%, 80%, 82% of their true ratios, respectively. The approximate 20% underestimation could be partially due to the effect of partial volume and reconstruction algorithm which we have not investigated in this study, and partially due to imperfect scatter and attenuation correction methods that we have applied in consideration of clinical applications.

• Journal of Korea Multimedia Society
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• v.9 no.7
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• pp.927-937
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• 2006

Auto-playing programs are often used in behalf of human players in MMORPG(Massively Multi-player Online Role Playing Game). By playing automatically and continuously, it helps to speed up the game character's level-up process. However, the auto-playing programs, either software or hardware, do harm to games servers in various ways including abuse of resources. In this paper, we propose a way of detecting the auto programs by analyzing the window event sequences produced by the game players. In our proposed method, the event sequences are transformed into a set of attributes, and the Decision Tree learning is applied to classify the data represented by the set of attribute values into human or auto player. The results from experiments with several MMORPG show that the Decision Tree learning with proposed method can identify the auto-playing programs with high accuracy.