• Journal of KIISE:Computing Practices and Letters
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• v.7 no.1
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• pp.12-23
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• 2001

Extended path expressions are used to denote multiple paths concisely by using '$\ast$' character. They are convenient for expressing OQL queries to retrieve XML data stored in OODBs. In this paper, we propose a multi-path index scheme as a new index scheme to efficiently process queries with extended path expressions. Our proposed index scheme allocates a unique path identifier for every possible single path in an extended path expression and provides functionalities of both a single path indexing and multiple path indexing through the composition of index key and path identifier while using only a index structure. The proposed index scheme provides better performance than single-path index schemes, and is practical since it can be implemented by little modification of leaf records of a B+-tree index.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.102-107
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• 2004

In this paper, we proposed a content-based image retrieval system using the multi-Index key. The multi-index ky combines the color distribution considering the spatial characteristic and the shape features of an image using the edge detection. Consequently, the evaluation shows that the performance of the proposed technique is better than other techniques.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.48-54
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• 2005

Recently, a couple of process capability indices are used to evaluate that the outputs of the process satisfy the specifications. An assumption of those indices is that the specifications of the characteristics are given single constant value. The display panel is a highly precise product and all the specifications of measure points are designed by their locations in the panel. So it is very difficult to locate the measurement facility to the exact position. In this paper, we propose a new process capability index in case of multi specifications and unfixable objects.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.628-645
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• 2014

In past few years, distributed hash table (DHT)-based P2P systems have been proven to be a promising way to manage decentralized index information and provide efficient lookup services. However, the skewness of users' preferences regarding keywords contained in a multi-keyword query causes a query load imbalance that combines both routing and response load. This imbalance means long file retrieval latency that negatively influences the overall system performance. Although index replication has a great potential for alleviating this problem, existing schemes did not explicitly address it or incurred high cost. To overcome this issue, we propose, in this paper, an integrated solution that consists of three replication schemes to alleviate query load imbalance while minimizing the cost. The first scheme is an active index replication that is used in order to decrease routing load in the system and to distribute response load of an index among peers that store replicas of the index. The second scheme is a proactive pointer replication that places location information of each index to a predetermined number of peers for reducing maintenance cost between the index and its replicas. The third scheme is a passive index replication that guarantees the maximum query load of peers. The result of simulations indicates that the proposed schemes can help alleviate the query load imbalance of peers. Moreover, it was found by comparison that our schemes are more cost-effective on placing replicas than PCache and EAD.

• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.195-210
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• 2003

In this paper, we propose an enhanced concurrency control algorithm that maximizes the concurrency of multi-dimensional index structures. The factors that deteriorate the concurrency of index structures are node splits and minimum bounding region (MBR) updates in multi-dimensional index structures. The proposed concurrency control algorithm introduces PLC(Partial Lock Coupling) technique to avoid lock coupling during MBR updates. Also, a new MBR update method that allows searchers to access nodes where MBR updates are being performed is proposed. To reduce the performance degradation by node splits the proposed algorithm holds exclusive latches not during whole split time but only during physical node split time that occupies the small part of a whole split process. For performance evaluation, we implement the proposed concurrency control algorithm and one of the existing link technique-based algorithms on MIDAS-3 that is a storage system of a BADA-4 DBMS. We show through various experiments that our proposed algorithm outperforms the existing algorithm in terms of throughput and response time. Also, we propose a recovery protocol for our proposed concurrency control algorithm. The recovery protocol is designed to assure high concurrency and fast recovery.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.113-123
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• 2003

Many researches on the application of neural networks for making financial index prediction have proven their advantages over statistical and other methods. In this paper, a neural network model is proposed for the Buying, Holding or Selling timing prediction in stocks by the price index of stocks by inputting the closing price and volume of dealing in stocks and the technical indexes(MACD, Psychological Line). This model has an equalized multi-layer arithmetic function as well as the time series prediction function of backpropagation neural network algorithm. In the case that the numbers of learning data are unbalanced among the three categories (Buying, Holding or Selling), the neural network with conventional method has the problem that it tries to improve only the prediction accuracy of the most dominant category. Therefore, this paper, after describing the structure, working and learning algorithm of the neural network, shows the equalized multi-layer arithmetic method controlling the numbers of learning data by using information about the importance of each category for improving prediction accuracy of other category. Experimental results show that the financial index prediction using the equalized multi-layer arithmetic neural network has much higher correctness rate than the other conventional models.

• Environmental and Resource Economics Review
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• v.12 no.3
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• pp.487-513
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• 2003

Currently, development of environmental index has been an increasingly important issue to achieve sustainable development, providing critical information to policy-makers. In particular, marine environmental composite index for Korea is widely required to establish. This paper constructs a marine environmental composite index using the OECD pressure-state-response (PSR) framework and employing multi-attribute utility theory (MAUT). The PSR framework links human activities as a pressure to environmental state and policy response. Weights are calculated by the MAUT technique. The paper provides annual pressure, state, response indices, and state index by sea area from 1991 to 2001 in Korea. The implications of the results and application plan of the index are also discussed.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.7
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• pp.153-171
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• 2022

To measure economic performance, customer satisfaction indices are constructed. This study proposes an index for banking and telecom, a significant evaluative system for comparing and enhancing customer satisfaction across the industries. The study suggests and examines amendments and improvements to the prior indices and incorporates ignored indicators to propose a punier index for Pakistan. The study is a pioneer in integrating online and offline indices into a single comprehensive model. The study is enriched by the Theory of Reasoned Action and Technological Acceptance Model. A sample of 320 respondents was used. The sample was divided based on gender and marital status. To authenticate the theoretical model, PLS-SEM was applied. We discovered nine latent variables that define customer satisfaction and conclude that a single model can be utilized for e-commerce enterprises as well. The index scores are comparable to the American index for banking and the Turkish index for telecom. Multi-group analysis (MGA) was used to comprehend the differences among the groups. This reveals that customization, design, reliability, and responsiveness induce satisfaction in telecom male and married customers. For the banking industry, the difference exists in complaint handling, customization, corporate image, perceived price, reliability, responsiveness, sentiments, convenience, and security to satisfaction links, image and complaint handling to loyalty links.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.513-520
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• 2005

In this paper, we propose a robust multi-watermarking method based on vector quantization using an index transform function. In contrast with the conventional watermark embedding methods to embed only one watermark at a time into the original image, we present a method to embed multiple watermarks for copyright protection. The proposed method efficiently enhances the robustness by index transform function which minimizes changes of vector quantization indices against various attacks. Experimental results show that the proposed method has a good robustness against various attacks compared with the conventional multi-watermarking method based on vector quantization.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.16-25
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• 2020

Vegetation segmentation in a field color image is a process of distinguishing vegetation objects of interests like crops and weeds from a background of soil and/or other residues. The performance of the process is crucial in automatic precision agriculture which includes weed control and crop status monitoring. To facilitate the segmentation, color indices have predominantly been used to transform the color image into its gray-scale image. A thresholding technique like the Otsu method is then applied to distinguish vegetation parts from the background. An obvious demerit of the thresholding based segmentation will be that classification of each pixel into vegetation or background is carried out solely by using the color feature of the pixel itself without taking into account color features of its neighboring pixels. This paper presents a new pixel-based segmentation method which employs a multi-layer perceptron neural network to classify the gray-scale image into vegetation and nonvegetation pixels. The input data of the neural network for each pixel are 2-dimensional gray-level values surrounding the pixel. To generate a gray-scale image from a raw RGB color image, a well-known color index called Excess Green minus Excess Red Index was used. Experimental results using 80 field images of 4 vegetation species demonstrate the superiority of the neural network to existing threshold-based segmentation methods in terms of accuracy, precision, recall, and harmonic mean.