• Journal of KIISE:Databases
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• v.34 no.6
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• pp.483-492
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• 2007

Time series of conventional prediction techniques uses the model which is generated from the training step. This model is applied to new input data without any change. If this model is applied directly to stream data, the rate of prediction accuracy will be decreased. This paper proposes an stream data prediction technique using sliding window and regression. This technique considers the characteristic of time series which may be changed over time. It is composed of two steps. The first step executes a fractional process for applying input data to the regression model. The second step updates the model by using its information as new data. Additionally, the model is maintained by only recent data in a queue. This approach has the following two advantages. It maintains the minimum information of the model by using a matrix, so space complexity is reduced. Moreover, it prevents the increment of error rate by updating the model over time. Accuracy rate of the proposed method is measured by RME(Relative Mean Error) and RMSE(Root Mean Square Error). The results of stream data prediction experiment are performed by the proposed technique IMQR(Incremental Multiple Quadratic Regression) is more efficient than those of MLR(Multiple Linear Regression) and SVR(Support Vector Regression).

• Journal of Radiation Protection and Research
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• v.36 no.1
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• pp.28-34
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• 2011

The measurement-based verification for intensity modulated radiation therapy (IMRT) is a time-and labor-consuming procedure. Instead, this study aims to develop a MU fluence reconstruction method for IMRT QA. Total actual fluences from treatment planning system (TPS, Eclipse 8.6, Varian) were selected as a reference. Delivered leaf positions according to MU were extracted by the dynalog file generated after IMRT delivery. An in-house software was develop to reconstruct MU fluence from the acquired delivered leaf position data using MATLAB. We investigated five patient's plans delivered by both step-and-shoot IMRT and sliding window technologies. The total actual fluence was compared with the MU fluence reconstructed by using commercial software (Verisoft 3.1, PTW) and gamma analysis method (criteria: 3%/3 mm and 2%/1 mm). Gamma pass rates were $97.8{\pm}1.33$% and the reconstructed fluence was shown good agreement with RTP-based actual fluence. The fluence from step and shoot IMRT was shown slightly higher agreement with the actual fluence than that from sliding window IMRT. If moving from IMRT QA measurements toward independent computer calculations, the developed method can be used for IMRT QA. A point dose calculation method from reconstructed fluences is under development for the routine IMRT QA purpose.

• Progress in Medical Physics
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• v.17 no.2
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• pp.114-122
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• 2006

The two commonly used methods in delivering intensity modulated radiation therapy (IMRT) plan are the dynamic (sliding window) and static (stop and shoot) mode. In this study, the two IMRI delivery techniques are compared by measuring point dose and dose distributions. Using treatment planning system, clinical target volume (CTV) was created as a sphere with various diameter (3 cm, 7 cm, 12 cm). Two IMRT plans were peformed to deliver 200 cGy to the CTV in dynamic and static mode. The two plans were delivered on a phantom and central point dose and dose distributions were measured. The central point dose differences between static and dynamic IMRT delivery were 0.2%, 0.2% and 0.4% when the diameter of CTV was 3 cm, 7 cm, and 12 cm, respectively. The differences In volume receiving 90% of the proscribed dose were 2.7%, 2.2%, and 2.9% for the diameter of CTV was 3 cm, 7 cm, and 12 cm, respectively. For lung cancer patients, the differences in central point dose were 0.2%, 0.2%, and 0.4% when the volume of CTV was 35.5 cc, 296.8 cc, and 903.5 cc, respectively. The differences in volume receiving 90% of the prescribed dose were 2.7%, 4.8%, and 9.1% when the volume of CTV was 35.5 cc, 296.8 cc, and 903.5 cc, respectively. In conclusion, it was possible to deliver IMRT plans using dynamic mode of MLC operation although the loaves are In motion during radiation delivery.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.9
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• pp.73-80
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• 2004

In this paper, we present the cell resequencing buffer to solve the cell sequence integrity problem of the Cyclic banyan network that is a high-performance fault-tolerant cell switch. By offering multiple paths between input ports and output ports, using the deflection self-routing, the Cyclic banyan switch offer high reliability, and it also solves congestion problem for the internal links of the switch. By the way, these multiple paths can be different lengths for each other. Therefore, the cells departing from an identical source port and arriving at an identical destination port can reach to the output port as the order that is different from the order arriving at input port. The proposed cell resequencing buffer is a hardware sliding window mechanism. to solve such cell sequence integrity problem. To calculate the size of sliding window that cause the prime cost of the presented device, we analyzed the distribution of the cell delay through the simulation analyses under traffic load that have a nonuniform address distribution that express tile Property of traffic of the Internet. Through these analyses, we found out that we can make a cell resequencing buffer by which the cell sequence integrity is to be secured, by using a, few of ordinary memory and control logic. The cell resequencing buffer presented in this paper can be used for other multiple paths switching networks.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1061-1069
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• 2021

Recently, the magnitude and frequency of extreme heavy rains and localized heavy rains have increased due to abnormal climate, which caused increased flood damage in river basin. As a result, the nonlinearity of the hydrological system of rivers or basins is increasing, and there is a limitation in that the lead time is insufficient to predict the water level using the existing physical-based hydrological model. This study predicted the water level at Ulsan (Taehwagyo) with a lead time of 0, 1, 2, 3, 6, 12 hours by applying deep learning techniques based on Deep Neural Network (DNN) and Long Short-Term Memory (LSTM) and evaluated the prediction accuracy. As a result, DNN model using the sliding window concept showed the highest accuracy with a correlation coefficient of 0.97 and RMSE of 0.82 m. If deep learning-based water level prediction using a DNN model is performed in the future, high prediction accuracy and sufficient lead time can be secured than water level prediction using existing physical-based hydrological models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.8A
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• pp.671-678
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• 2005

This paper proposed symbol rate method which does not require a priori knowledge on the symbol rate and simplified modulation identification method to classify BPSK, QPSK, 8PSK signal. In order to estimate the unknown symbol rate, sliding FFT and simple moving average to estimate the spectrum of the signals is utilized, and sliding window and decimation, LPF blcok to estimate the proper symbol rate is used. Although conventional modulation ID method must use SNR value as the test statistics, the receiver cannot estimate the SNR value since the receiver cannot know the modulation type at the start of communication, and bit resolution is high due to using nonlinear function such as log, cosh. Therefore, we proposed the simplified fixed SNR value method. The performance of symbol rate estimation and modulation ID is shown using Monte Carlo computer simulation. This paper show that symbol rate estimation also has good performance in low SNR, and proposed simplified fixed SNR method has almost equivalent performance compared to conventional method.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.131-140
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• 2011

Smart packet agent is an application that is proposed to provide routing protocol and service module in ubiquitous network environment. However, it uses multi-hop broadcast, thus it causes increasing network traffic, low-speed data transmission, and the unnecessary joining nodes. In this paper, a transmit technique that uses unicast-based multi-hop to have lower network traffic and faster transmission time than the multi-hop broadcast technique. In our scheme, u-Zone Master establishes temporary routing paths by calculating moving nodes' hop-counter. Therefore, it reduces smart packet agent's network traffic and retransmission rate. Besides, this paper proposed an UDP transmission that bases on sliding window. Hence, the Stop & Wait transmission speed is improved. The results, which are taken by analyzing performance prove that the proposed scheme has better performance.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.89-98
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• 2009

As data stream is entered into system continuously and the memory space is limited, the data exceeding the memory size cannot be processed. In order to solve the problem, load shedding methods which drop a part of data to prevent exceeding the storage space have been researched. Generally, a traditional load shedding method uses random sampling with optimized rate according to data deviation. The method samples data not to distinguish those used in spatial query because the method uses only a random sampling with optimized rate according to data deviation. Therefore, the accuracy of query was reduced in u-GIS environment including spatial query. In this paper, we researched a new load shedding method improving accuracy of the query in u-GIS environment which runs spatial query and aspatial query simultaneously. The method uses a new sampling method that samples data having low probability used in query. Therefore proposed method improves spatial query accuracy and query processing speed as applying spatial filtering operation to sampling operator.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.27-45
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• 2001

Sequential discovery from time series data has mainly concerned about events or item sets. Recently, the research has stated to applied to the numerical data. An example is sensor information generated by checking a machine state. The numerical data hardly have the same valuers while making patterns. So, it is important to extract suitable number of pattern features, which can be transformed to events or item sets and be applied to sequential pattern mining tasks. The popular methods to extract the patterns are sliding window and clustering. The results of these methods are sensitive to window sine or clustering parameters; that makes users to apply data mining task repeatedly and to interpret the results. This paper suggests the method to retrieve pattern features making numerical data into vector of an angle and a magnitude. The retrieved pattern features using this method make the result easy to understand and sequential patterns finding fast. We define an inclusion relation among pattern features using angles and magnitudes of vectors. Using this relation, we can fad sequential patterns faster than other methods, which use all data by reducing the data size.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1633-1649
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• 2017

In remote sensing image processing, the traditional fusion algorithm is based on the Intensity-Hue-Saturation (IHS) transformation. This method does not take into account the texture or spectrum information, spatial resolution and statistical information of the photos adequately, which leads to spectrum distortion of the image. Although traditional solutions in such application combine manifold methods, the fusion procedure is rather complicated and not suitable for practical operation. In this paper, an improved IHS transformation fusion algorithm based on the local variance weighting scheme is proposed for remote sensing images. In our proposal, firstly, the local variance of the SPOT (which comes from French "Systeme Probatoire d'Observation dela Tarre" and means "earth observing system") image is calculated by using different sliding windows. The optimal window size is then selected with the images being normalized with the optimal window local variance. Secondly, the power exponent is chosen as the mapping function, and the local variance is used to obtain the weight of the I component and match SPOT images. Then we obtain the I' component with the weight, the I component and the matched SPOT images. Finally, the final fusion image is obtained by the inverse Intensity-Hue-Saturation transformation of the I', H and S components. The proposed algorithm has been tested and compared with some other image fusion methods well known in the literature. Simulation result indicates that the proposed algorithm could obtain a superior fused image based on quantitative fusion evaluation indices.