• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.416-424
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• 2017

In this study, we propose a design of digits recognition system based on RBFNNs through a comparative study of pre-processing algorithms in order to recognize digits in handwritten. Histogram of Oriented Gradient(HOG) is used to get the features of digits in the proposed digits recognition system. In the pre-processing part, a dimensional reduction is executed by using Principal Component Analysis(PCA) and (2D)2PCA which are widely adopted methods in order to minimize a loss of the information during the reduction process of feature space. Also, The architecture of radial basis function neural networks consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, the connection weights are used as the extended type of polynomial expression such as constant, linear, quadratic and modified quadratic. By using MNIST handwritten digit benchmarking database, experimental results show the effectiveness and efficiency of proposed digit recognition system when compared with other studies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.87-93
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• 2014

For n/m=qm+r, there is no simple divisibility rule for simple m=7 such that is the n multiply by m? This problem can be more complex for two or more digits of m. The Dunkels method has been known for generalized divisibility test method, but this method can not compute very large digits number that can not processed by computer. This paper suggests simple and exact divisibility method for m completely irrelevant n and m of digits. The proposed method sets $r_1=n_1n_2{\cdots}n_l(mod m)$ for $n=n_1n_2n_3{\cdots}n_k$, $m=m_1m_2{\cdots}m_l$. Then this method computes $r_i=r_{i-1}{\times}10+n_i(mod m)$, $i=2,3,{\cdots}k-l+1$ and reduces the digits of n one-by-one. The proposed method can be get the quotient and remainder with easy, fast and correct for various n,m experimental data.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.125-132
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• 2021

As the layers of artificial neural network deepens, and the dimension of data used as an input increases, there is a problem of high arithmetic operation requiring a lot of arithmetic operation at a high speed in the learning and recognition of the neural network (NN). Thus, this study proposes a data dimensionality reduction method to reduce the dimension of the input data in the NN. The proposed Line-segment Feature Analysis (LFA) algorithm applies a gradient-based edge detection algorithm using median filters to analyze the line-segment features of the objects existing in an image. Concerning the extracted edge image, the eigenvalues corresponding to eight kinds of line-segment are calculated, using 3×3 or 5×5-sized detection filters consisting of the coefficient values, including [0, 1, 2, 4, 8, 16, 32, 64, and 128]. Two one-dimensional 256-sized data are produced, accumulating the same response values from the eigenvalue calculated with each detection filter, and the two data elements are added up. Two LFA256 data are merged to produce 512-sized LAF512 data. For the performance evaluation of the proposed LFA algorithm to reduce the data dimension for the recognition of handwritten numbers, as a result of a comparative experiment, using the PCA technique and AlexNet model, LFA256 and LFA512 showed a recognition performance respectively of 98.7% and 99%.

• Clinics in Shoulder and Elbow
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• v.8 no.2
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• pp.181-186
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• 2005

An anterior dislocation of the elbow without a fracture of the olecranon is an extremely rare injury. This paper reports a 36-year-old male who stumbled and fell on his outstretched hand during a soccer game. The anteroposterior and lateral radiographs indicated a simple anterior dislocation of the elbow, which was reduced using a closed method. The elbow joint was stable in the range of motion, but the sensation of the two ulnar digits was still reduced. MRI was useful for the identification of the pathoanatomy. At the follow-up examination three months after the initial trauma, the hypesthesia has fully recovered and the patient regained the full range of the elbow and forearm motion without pain and instability. After 18 months, the patient had a normal elbow function, and could play various sports. If an anterior elbow dislocation is detected early, a closed reduction with careful pathoanatomical considerations would be successful.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1E
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• pp.64-70
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• 1994

Predictive neural network models are powerful speech recognition models based on a nonlinear pattern prediction. But those models suffer from poor discrimination between acoustically similar words. In this paper we propose an discriminative training algorithm for predictive neural network models. This algorithm is derived from GPD (Generalized Probabilistic Descent) algorithm coupled with MCEF(Minimum Classification Error Formulation). It allows direct minimization of a recognition error rate. Evaluation of our training algoritym on ten Korean digits shows its effectiveness by 30% reduction of recognition error.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.997-1002
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• 1994

Predictive neural network models are powerful speech recognition models based on a nonlinear pattern prediction. Those models can effectively normalize the temporal and spatial variability of speech signals. But those models suffer from poor discrimination between acoustically similar words. In this paper, we propose a discriminative training algorithm for predictive neural network models based on a generalized probabilistic descent (GPD) algorithm and minimum classification error formulation (MCEF). The Evaluation of our training algorithm on ten Korean digits shows its effectiveness by 40% reduction of recognition error.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.108-115
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• 1994

Most pattern classifiers have been designed based on the ML (Maximum Likelihood) training algorithm which is simple and relatively powerful. The ML training is an efficient algorithm to individually estimate the model parameters of each class under the assumption that all class models in a classifier are statistically independent. That assumption, however, is not valid in many real situations, which degrades the performance of the classifier. In this paper, we propose a minimum-error-rate training algorithm based on the MAP (Maximum a Posteriori) approach. The algorithm regards the normalized outputs of the classifier as estimates of the a posteriori probability, and tries to maximize those estimates. According to Bayes decision theory, the proposed algorithm satisfies the condition of minimum-error-rate classificatin. We apply this algorithm to NPM (Neural Prediction Model) for speech recognition, and derive new disrminative training algorithms. Experimental results on ten Korean digits recognition have shown the reduction of 37.5% of the number of recognition errors.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.2
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• pp.71-79
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• 1997

In this paper, we propose a new nearest-neighbor classifier with reduced computational complexity in search process. In the proposed classifier, the classes are divided into two sets: reference and non-reference sets. It reduces computational requriement by approximating the distance between the input and a class iwth the information of distances among the calsses. It calculates only the distance between the input and the reference classes. We convert a given classifier into RCC (reduced computational complexity but smal lincrease in misclassification probability of its corresponding RCC classifier. We designed RCC classifiers for the recognition of digits from the NIST database. We obtained an RCC classifier with 60% reduction in the computational complexity with the cost of 0.5% increase in misclassification probability.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.11
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• pp.491-494
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• 2006

In the adder design, reduction of the delay of the carry propagation or ripple is the most important consideration. Previously, it was introduced that, if a redundant number system is adopted, the carry propagation is completely eliminated, with which addition can be done in a constant time, without regarding to the count of the digits of numbers involved in addition. In this paper, a RBCD(Redundant Binary Coded Decimal) is adopted to code 0 to 11, and an efficient and economic carry-free BCD adder is designed.

• Archives of Plastic Surgery
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• v.48 no.1
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• pp.98-106
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• 2021

Background Hand fractures can be treated using various operative or nonoperative methods. When an operative technique utilizing fixation is performed, early postoperative mobilization has been advocated. We implemented a protocol involving controlled active exercise in the early postoperative period and analyzed the outcomes. Methods Patients who were diagnosed with proximal phalangeal or metacarpal fractures of the second to fifth digits were included (n=37). Minimally invasive open reduction and internal fixation procedures were performed. At 3 weeks postoperatively, controlled active exercise was initiated, with stress applied against the direction of axial loading. The exercise involved pain-free active traction in three positions (supination, neutral, and pronation) between 3 and 5 weeks postoperatively. Postoperative radiographs and range of motion (ROM) in the interphalangeal and metacarpophalangeal joints were analyzed. Results Significant improvements in ROM were found between 6 and 12 weeks for both proximal phalangeal and metacarpal fractures (P<0.05). At 12 weeks, 26 patients achieved a total ROM of more than 230° in the affected finger. Postoperative radiographic images demonstrated union of the affected proximal phalangeal and metacarpal bones at a 20-week postoperative follow-up. Conclusions Minimally invasive open reduction and internal fixation minimized periosteal and peritendinous dissection in hand fractures. Controlled active exercise utilizing pain-free active traction in three different positions resulted in early functional exercise with an acceptable ROM.