• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.435-441
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• 2017

Detecting an inter-harmonic accurately is not easy work, because it has small magnitude, and its frequency which can be observed is not an integer multiple of fundamental frequency. In this paper, a new method using filter bank system and adaptive predictor is proposed. Filter bank system decomposes input signal to sub bands. In adaptive predictor, inter-harmonic is detected with decomposed sub band signal as input, and error signal as output. In this scheme, input-output characteristic of adaptive predictor is notch filter, as predicted harmonic is canceled in error signal, so detecting an inter-harmonic can be possible. Magnitude and frequency of detected inter-harmonic is estimated by recursive algorithm. The performances of proposed method are evaluated to sinusoidal signal model synthesized with harmonics and inter-harmonics. And validity of the method is proved as comparing the inter-harmonic detection results to MUSIC and ESPRIT.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.95-106
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• 2014

In this paper, we design a smart phone UX/UI and a tap pattern recognition algorithm that can recognize tap patterns from a tapping user's fingers on the screen, and implement an application that provides user-customizable smart phones's services from the tap patterns. A user can generate a pattern by tapping the input pad several times and register it by using a smart phone's favorite program. More specifically, when the user inputs a tap pattern on the input pad, the proposed application searches a stored similar tap pattern and can run a service registered on it by measuring tap pattern similarity. Our experimental results show that the proposed method helps to guarantee the higher recognition rate and shorter input time for a variety of tap patterns.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.407-416
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• 2006

It is difficult for the movement detection of an object through a camera to detect exact movement because of unnecessary noises and changes of the light. It can be recognized as a background, when there is no movement after the inflow of an object. Therefore, It is necessary to fast search algorithm for tracking and extract of object that is realtime image. In this thesis, we evaluate the difference of the input vision based on initial image and replace some pixels in process of time. When there is a big difference between background image and input image, we decide it is the point of the time of the object input and then extract boundary point of it. The extracted boundary point detects precise movement of the object by creating minimum block of it and searching block that maintaining distance. The designed and embodied system shows more than 95% accuracy in the performance test.

• Journal of the Korea Society of Computer and Information
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• v.7 no.2
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• pp.115-123
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• 2002

This thesis proposes a new type of Input-Output Buffered ATM Switch which employs an arbiter and its performance under different traffic conditions studied. The proposed switch is designed with a view to exploit the architecture and other characteristics of the arbiter. The primary aim of the proposed switch is the elimination, or at least, the reduction of HOL blocking phenomenon which occurs in the simple input buffered switch. Several HOL arbitration algorithms have been proposed for this purpose in the literature. The proposed switch attempts to reduce the HOL blocking as it uses the arbiter and the buffer at the output port in an effective manner. The arbiter is designed to work with Three Phase Algorithm which is one of the many well known HOL arbitration algorithms. The Proposed switch acquires control over priority transmission through the REQ signal. As the signals are transmitted to the arbiter, the latter controls the one which is sent by the input buffer. Computer simulation results have been provided to demonstrate the effectiveness of the Proposed switch under uniform traffic conditions.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.97-105
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• 2003

This thesis proposes a new type of Input-Output Buffered ATM Switch which employs an arbiter and its performance under different traffic conditions studied. The proposed switch is designed with a view to exploit the architecture and other characteristics of the arbiter The primary aim of the proposed switch is the elimination, or at least, the reduction of HOL blocking phenomenon which occurs in the simple input buffered switch. Several HOL arbitration algorithms have been proposed for this purpose in the literature. The Proposed switch attempts to reduce the HOL blocking as it uses the arbiter and the buffer at the output Port in an effective manner. The arbiter is designed to work with Three Phase Algorithm which is one of the many well known HOL arbitration algorithms . The proposed switch acquires control over priority transmission through the REd signal. As the signals are transmitted to the arbiter, the latter controls the one which is sent by the input buffer. Computer simulation results have been provided to demonstrate the effectiveness of the proposed switch under non-uniform random traffic conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3102-3119
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• 2021

In the modern rapid growing web era, the scope of web publication is about accessing the web resources. Due to the increased size of web, the search engines face many challenges, in indexing the web pages as well as producing result to the user query. Methodologies discussed in literatures towards clustering web documents suffer in producing higher clustering accuracy. Problem is mitigated using, the proposed scheme, Semantic Conceptual Relational Similarity (SCRS) based clustering algorithm which, considers the relationship of any document in two ways, to measure the similarity. One is with the number of semantic relations of any document class covered by the input document and the second is the number of conceptual relation the input document covers towards any document class. With a given data set Ds, the method estimates the SCRS measure for each document Di towards available class of documents. As a result, a class with maximum SCRS is identified and the document is indexed on the selected class. The SCRS measure is measured according to the semantic relevancy of input document towards each document of any class. Similarly, the input query has been measured for Query Relational Semantic Score (QRSS) towards each class of documents. Based on the value of QRSS measure, the document class is identified, retrieved and ranked based on the QRSS measure to produce final population. In both the way, the semantic measures are estimated based on the concepts available in semantic ontology. The proposed method had risen efficient result in indexing as well as search efficiency also has been improved.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.639-644
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• 2014

In low-density parity-check (LDPC) coded multiple-input multiple-output (MIMO) communication systems, probabilistic information are exchanged between an LDPC decoder and a MIMO detector. TheMIMO detector has to calculate probabilistic values for each bit which can be very complex. In [1], the authors presented a class of linear block codes named low-density MIMO codes (LDMC) which can reduce the complexity of MIMO detector. However, this code only supports the outer-iterations between the MIMO detector and decoder, but does not support the inner-iterations inside the LDPC decoder. In this paper, a new approach to construct LDMC codes is introduced. The new LDMC codes can be encoded efficiently at the transmitter side and support both of the inner-iterations and outer-iterations at the receiver side. Furthermore they can achieve the design rates and perform very well over MIMO channels.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.367-369
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• 2022

With the development of web technology, the web provides customized information that meets the needs of users. Information is provided according to the input form and the user's query, and a web service that provides information that is difficult to search with a search engine is called an in-depth web. These deep webs contain more information than surface webs, but it is difficult to collect information with general crawling, which collects information at the time of the visit. The deep web provides users with information on the server by running script languages such as javascript in their browsers. In this paper, we propose an algorithm capable of exploring dynamically changing websites and collecting information by analyzing scripts for deep web collection. In this paper, the script of the bulletin board of the Korea Centers for Disease Control and Prevention was analyzed for experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1888-1906
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• 2024

Aiming at the problems that the edge of melanoma image is fuzzy, the contrast with the background is low, and the hair occlusion makes it difficult to segment accurately, this paper proposes a model MSCNet for melanoma segmentation based on U-net frame. Firstly, a multi-scale pyramid fusion module is designed to reconstruct the skip connection and transmit global information to the decoder. Secondly, the contextural information conduction module is innovatively added to the top of the encoder. The module provides different receptive fields for the segmented target by using the hole convolution with different expansion rates, so as to better fuse multi-scale contextural information. In addition, in order to suppress redundant information in the input image and pay more attention to melanoma feature information, global channel attention mechanism is introduced into the decoder. Finally, In order to solve the problem of lesion class imbalance, this paper uses a combined loss function. The algorithm of this paper is verified on ISIC 2017 and ISIC 2018 public datasets. The experimental results indicate that the proposed algorithm has better accuracy for melanoma segmentation compared with other CNN-based image segmentation algorithms.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.999-1007
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• 2006

The Backpropagation learning algorithm is known to have slow and false convergence aroused from plateau and local minima. Many substitutes for backpropagation announced so far appear to pay some trade-off for convergence speed and stability of convergence according to parameters. Here, a new algorithm is proposed, which avoids some of those problems associated with the conventional backpropagation problems, especially with local minima, and gives relatively stable and fast convergence with low storage requirement. This is the separate learning algorithm in which the upper connections, hidden-to-output, and the lower connections, input-to-hidden, separately trained. This algorithm requires less computational work than the conventional backpropagation and other improved algorithms. It is shown in various classification problems to be relatively reliable on the overall performance.