• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.247-253
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• 2003

The mainly used technique to correct satellite images with geometric distortion is to develop a mathematical relationship between pixels on the image and corresponding points on the ground. Polynomial models with various transformations have been designed for defining the relationship between two coordinate systems. GCP based geometric correction has peformed overall plane to plane mapping. In the overall plane mapping, overall structure of a scene is considered, but local variation is discarded. The Region with highly variant height is rectified with distortion on overall plane mapping. To consider locally variable region in satellite image, TIN-based rectification on a satellite image is proposed in this paper. This paper describes the relationship between GCP distribution and rectification model through experimental result and analysis about each rectification model. We can choose a geometric correction model as the structural characteristic of a satellite image and the acquired GCP distribution.

• Journal of Biomedical Engineering Research
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• v.31 no.1
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• pp.1-13
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• 2010

There are a great numbers of disabled individuals who cannot freely move or control specific parts of their body because of serious neurological diseases such as spinal cord injury, amyotrophic lateral sclerosis, brainstem stroke, and so on. Brain-computer interfaces (BCIs) can help them to drive and control external devices using only their brain activity, without the need for physical body movements. Over the past 30 years, several Bel research programs have arisen and tried to develop new communication and control technology for those who are completely paralyzed. Thanks to the rapid development of computer science and neuroimaging technology, new understandings of brain functions, and most importantly many researchers' efforts, Bel is now becoming 'practical' to some extent. The present review article summarizes the current state of electroencephalogram (EEG)-based Bel, which have been being studied most widely, with specific emphasis on its basic concepts, system developments, and prospects for the future.

• Journal of the Semiconductor & Display Technology
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• v.5 no.2 s.15
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• pp.27-31
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• 2006

As more and more digital images are made by various applications, image retrieval becomes a primary concern in technology of multimedia. This paper presents color based descriptor that uses information of color distribution in color images which is the most basic element for image search and performance of proposed visual feature is evaluated through the simulation. In designing the image search descriptor used color histogram, HSV, Daubechies 9/7 and 2 level wavelet decomposition provide better results than other parameters in terms of computational time and performances. Also histogram quadratic matrix outperforms the sum of absolute difference in similarity measurements, but spends more than 60 computational times.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3168-3186
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• 2020

Automatic topic essay generation (TEG) is a controllable text generation task that aims to generate informative, diverse, and topic-consistent essays based on multiple topics. To make the generated essays of high quality, a reasonable method should consider both diversity and topic-consistency. Another essential issue is the intrinsic link of the topics, which contributes to making the essays closely surround the semantics of provided topics. However, it remains challenging for TEG to fill the semantic gap between source topic words and target output, and a more powerful model is needed to capture the semantics of given topics. To this end, we propose a pretraining-based contextual self-attention (PC-SAN) model that is built upon the seq2seq framework. For the encoder of our model, we employ a dynamic weight sum of layers from BERT to fully utilize the semantics of topics, which is of great help to fill the gap and improve the quality of the generated essays. In the decoding phase, we also transform the target-side contextual history information into the query layers to alleviate the lack of context in typical self-attention networks (SANs). Experimental results on large-scale paragraph-level Chinese corpora verify that our model is capable of generating diverse, topic-consistent text and essentially makes improvements as compare to strong baselines. Furthermore, extensive analysis validates the effectiveness of contextual embeddings from BERT and contextual history information in SANs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.769-786
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• 2016

Object recognition and object location have always drawn much interest. Also, recently various computational models have been designed. One of the big issues in this domain is the lack of an appropriate model for extracting important part of the picture and estimating the object place in the same environments that caused low accuracy. To solve this problem, a new Salient Based Bag of Visual Word (SBBoVW) model for object recognition and object location estimation is presented. Contributions lied in the present study are two-fold. One is to introduce a new approach, which is a Salient Based Bag of Visual Word model (SBBoVW) to recognize difficult objects that have had low accuracy in previous methods. This method integrates SIFT features of the original and salient parts of pictures and fuses them together to generate better codebooks using bag of visual word method. The second contribution is to introduce a new algorithm for finding object place based on the salient map automatically. The performance evaluation on several data sets proves that the new approach outperforms other state-of-the-arts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3798-3814
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• 2022

Social recommendation algorithm can alleviate data sparsity and cold start problems in recommendation system by integrated social information. Among them, matrix-based decomposition algorithms are the most widely used and studied. Such algorithms use dot product operations to calculate the similarity between users and items, which ignores user's potential preferences, reduces algorithms' recommendation accuracy. This deficiency can be avoided by a metric learning-based social recommendation algorithm, which learns the distance between user embedding vectors and item embedding vectors instead of vector dot-product operations. However, previous works provide no theoretical explanation for its plausibility. Moreover, most works focus on the indirect impact of social friends on user's preferences, ignoring the direct impact on user's rating preferences, which is the influence of user rating preferences. To solve these problems, this study proposes a user bias drift social recommendation algorithm based on metric learning (BDML). The main work of this paper is as follows: (1) the process of introducing metric learning in the social recommendation scenario is introduced in the form of equations, and explained the reason why metric learning can replace the click operation; (2) a new user bias is constructed to simultaneously model the impact of social relationships on user's ratings preferences and user's preferences; Experimental results on two datasets show that the BDML algorithm proposed in this study has better recommendation accuracy compared with other comparison algorithms, and will be able to guarantee the recommendation effect in a more sparse dataset.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.234-244
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• 2022

Tourism products involve the transfer of money that is flowing to countries with partners or borders, which do not possess any relations surrounding their business environment. Suitable platforms must be generated by the tourism industry, which are beneficial to users when their demands are satisfied based on financial, technology, knowledge, and industry matters. Intermediaries are applied to alleviate different problems that are related to the non-fulfilment of contracts of existing users and service providers who are offering their services and represent a reliable third party. However, it is significant that intermediaries must be reliable when charges are incurred for any possible commission. Cryptocurrencies rely on blockchain technology to provide smoothness in money interchange without the need for reliable third parties. This interchange allows an increasing number of different new forms, which are related to different customer-to-customer transactions. The study attempts to provide an appropriate answer to the main research question, which is: 'Will the widespread adoption of cryptocurrencies bring new types of customer-to-customer markets from a technological, organizational, and environmental perspective?'.

• Journal of Computing Science and Engineering
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• v.6 no.2
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• pp.89-104
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• 2012

In dynamic Web service environments, the performance of the Internet is unpredictable; the reliability and effectiveness of remote Web services are also unclear. Therefore, it can hardly be guaranteed that the quality of Web service (QoWS) attributes of Web services do not fluctuate with the dynamic Web service environments. When a composite service is planned in the context of dynamic service environments, there is another aspect which has not been taken into account by existing works, namely, concurrency - the fact that multiple requests to a composite service may arrive at the same time. Considering the dynamics of Web service environments and concurrency of requests, we propose in this paper a service selection scheme which adopts top-k dominating queries to generate a composition solution rather than only select the best composition solution for a given request. The experimental results have investigated the efficiency and effectiveness of our approach and shown that it outperforms baseline and traditional methods for service selection.

• International Commerce and Information Review
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• v.5 no.2
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• pp.47-69
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• 2003

The computer was only used to calculate and solve the mathematical problems, to send the simple data, and to exchange the text based informations in the early 1990's. But nowadays, computer technology give us the chance to exchange digital goods and services, etc. And more, computer and computer based systems can be applied everywhere, for example, it can be used at office, at home, and at school. Most of all, one of the remarkable changes is the development of mobile industry, which can be applied anywhere and anytime. So, this study focused on the current situation and promotion plans of the mobile industry. Mobile is based on the IT, IT and mobile technology are the foundation stone of ubiquitous computing environments. Accordingly, this thesis analysis the meaning of ubiquitous, the meaning and roll of mobile industry. With the analysis of this, the conclusion is that to develop and success the new business model at home and overseas, the cooperation of government section and industry section is the most import thing to make it out.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.1095-1100
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• 2004

The computer system is gradually complicated because of explosive growth of computer system and IT technology. For efficient management of complicated system, system load monitoring technology is essential. In this paper, we is implemented the real-time load monitoring system based mobile than the traditional methods that are used load-related commands in system manager or specific load application programs based connected wire. Advantage of implemented load monitoring system in this paper is freely saw load information in time and space though mobile method like as PDA, cellular phone, more than traditional methods intime and space.