Standardization of the Comprehensive Attention Test for the Korean Children and Adolescents (국내 아동 및 청소년 주의력 평가를 위한 종합주의력검사의 표준화 연구)
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- Journal of the Korean Academy of Child and Adolescent Psychiatry
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- v.20 no.2
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- pp.68-75
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- 2009
Objectives: This study was conducted in order to develop and obtain the nonnative data of the computerized Comprehensive Attention Test(CAT) in Korean children and adolescents. It also aimed to evaluate the reliability and validity of the CAT. Methods: We developed the computerized CAT which includes the selective attention task, the sustained attention to response task, the flanker task, the divided attention task, and the spatial working memory task. We investigated the test-retest reliability and the construction validity of this computerized version by using the data from 21 children, and gathered the nonnative data of 9l2 subjects, aged 4 to 15 years, dwelling in the Metropolitan Seoul area in 2008. Results: No statistical differences between means of the tests and retests of the CAT were observed. The mean of the correlation coefficient of the test-retest scores was 0.715. The results from the factor analyses explained 51.7% of the cumulative variance. In addition, the nonnative data for all of the CAT subtests were obtained. Conclusion: The computerized CAT can be used as a reliable and valid tool in both clinical and research settings for Korean children and adolescents with or without neuropsychiatric conditions such as attention deficit.
In this Paper, an approximate processing method is proposed and tested. The proposed method uses variable CSD (VCSD) coefficients which approximate filter stopband attenuation by controlling the precision of the CSD coefficient sets. A decimation filter for Audio Codec '97 specifications has been designed having processor architecture that consists of program/data memory, arithmetic unit, energy/level decision, and sinc filter blocks, and fabricated with 0.6
In recent years, mobile devices have become increasingly multi-functional and high performance, resulting in a dramatical increase in processing speed. On the other hand, the size of device is reduced, circuits inside the device are more easily exposed to electromagnetic interference radiated from antenna or adjacent circuits, degrading the system performance. To prevent this, it is necessary to design the device considering the electromagnetic characteristics with EM simulation at the design stage of product. However, the EM simulation takes a long analysis time and require high-level system resources for fast analysis. In this paper, an equivalent circuit modeling method for a round wire is proposed using a PEEC method and the electromagnetic coupling from a dipole antenna to a transmission line is analyzed in frequency domain. And compared with the result of electromagnetic simulator. As a result, PEEC method shows good agreement with those of electromagnetic simulation, in a much more short time.
Fast Fourier transform (FFT) processors have been widely used in various application such as communications, image, and biomedical signal processing. Especially, high-performance and low-power FFT processing is indispensable in OFDM-based communication systems. This paper presents a novel radix-26 FFT algorithm with low computational complexity and high hardware efficiency. Applying a 7-dimensional index mapping, the twiddle factor is decomposed and then radix-26 FFT algorithm is derived. The proposed algorithm has a simple twiddle factor sequence and a small number of complex multiplications, which can reduce the memory size for storing the twiddle factor. When the coefficient of twiddle factor is small, complex constant multipliers can be used efficiently instead of complex multipliers. Complex constant multipliers can be designed more efficiently using canonic signed digit (CSD) and common subexpression elimination (CSE) algorithm. An efficient complex constant multiplier design method for the twiddle factor multiplication used in the proposed radix-26 algorithm is proposed applying CSD and CSE algorithm. To evaluate performance of the previous and the proposed methods, 256-point single-path delay feedback (SDF) FFT is designed and synthesized into FPGA. The proposed algorithm uses about 10% less hardware than the previous algorithm.
The recommender system is one of the possible solutions to assist customers in finding the items they would like to purchase. To date, a variety of recommendation techniques have been developed. One of the most successful recommendation techniques is Collaborative Filtering (CF) that has been used in a number of different applications such as recommending Web pages, movies, music, articles and products. CF identifies customers whose tastes are similar to those of a given customer, and recommends items those customers have liked in the past. Numerous CF algorithms have been developed to increase the performance of recommender systems. Broadly, there are memory-based CF algorithms, model-based CF algorithms, and hybrid CF algorithms which combine CF with content-based techniques or other recommender systems. While many researchers have focused their efforts in improving CF performance, the theoretical justification of CF algorithms is lacking. That is, we do not know many things about how CF is done. Furthermore, the relative performances of CF algorithms are known to be domain and data dependent. It is very time-consuming and expensive to implement and launce a CF recommender system, and also the system unsuited for the given domain provides customers with poor quality recommendations that make them easily annoyed. Therefore, predicting the performances of CF algorithms in advance is practically important and needed. In this study, we propose an efficient approach to predict the performance of CF. Social Network Analysis (SNA) and Artificial Neural Network (ANN) are applied to develop our prediction model. CF can be modeled as a social network in which customers are nodes and purchase relationships between customers are links. SNA facilitates an exploration of the topological properties of the network structure that are implicit in data for CF recommendations. An ANN model is developed through an analysis of network topology, such as network density, inclusiveness, clustering coefficient, network centralization, and Krackhardt's efficiency. While network density, expressed as a proportion of the maximum possible number of links, captures the density of the whole network, the clustering coefficient captures the degree to which the overall network contains localized pockets of dense connectivity. Inclusiveness refers to the number of nodes which are included within the various connected parts of the social network. Centralization reflects the extent to which connections are concentrated in a small number of nodes rather than distributed equally among all nodes. Krackhardt's efficiency characterizes how dense the social network is beyond that barely needed to keep the social group even indirectly connected to one another. We use these social network measures as input variables of the ANN model. As an output variable, we use the recommendation accuracy measured by F1-measure. In order to evaluate the effectiveness of the ANN model, sales transaction data from H department store, one of the well-known department stores in Korea, was used. Total 396 experimental samples were gathered, and we used 40%, 40%, and 20% of them, for training, test, and validation, respectively. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. The input variable measuring process consists of following three steps; analysis of customer similarities, construction of a social network, and analysis of social network patterns. We used Net Miner 3 and UCINET 6.0 for SNA, and Clementine 11.1 for ANN modeling. The experiments reported that the ANN model has 92.61% estimated accuracy and 0.0049 RMSE. Thus, we can know that our prediction model helps decide whether CF is useful for a given application with certain data characteristics.
In this study, after developing an LSTM-based deep learning model for estimating daily runoff in the Soyang River Dam basin, the accuracy of the model for various combinations of model structure and input data was investigated. A model was built based on the database consisting of average daily precipitation, average daily temperature, average daily wind speed (input up to here), and daily average flow rate (output) during the first 12 years (1997.1.1-2008.12.31). The Nash-Sutcliffe Model Efficiency Coefficient (NSE) and RMSE were examined for validation using the flow discharge data of the later 12 years (2009.1.1-2020.12.31). The combination that showed the highest accuracy was the case in which all possible input data (12 years of daily precipitation, weather temperature, wind speed) were used on the LSTM model structure with 64 hidden units. The NSE and RMSE of the verification period were 0.862 and 76.8 m3/s, respectively. When the number of hidden units of LSTM exceeds 500, the performance degradation of the model due to overfitting begins to appear, and when the number of hidden units exceeds 1000, the overfitting problem becomes prominent. A model with very high performance (NSE=0.8~0.84) could be obtained when only 12 years of daily precipitation was used for model training. A model with reasonably high performance (NSE=0.63-0.85) when only one year of input data was used for model training. In particular, an accurate model (NSE=0.85) could be obtained if the one year of training data contains a wide magnitude of flow events such as extreme flow and droughts as well as normal events. If the training data includes both the normal and extreme flow rates, input data that is longer than 5 years did not significantly improve the model performance.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70