• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.773-777
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• 2009

In recent years, the field of synthesizing voice has been developed rapidly, and the technologies such as reading aloud an email or sound guidance of a car navigation system are used in various scenes of our life. The sound quality is monotonous like reading news. It is preferable for a text such as a novel to be read by the voice that expresses emotions wealthily. Therefore, we have been trying to develop a system reading aloud novels automatically that are expressed clear emotions comparatively such as juvenile literature. At first it is necessary to identify emotions expressed in a sentence in texts in order to make a computer read texts with an emotionally expressive voice. A method on the basis of the meaning interpretation that utilized artificial intelligence technology for a method to specify emotions of texts is thought, but it is very difficult with the current technology. Therefore, we propose a method to determine only emotion every sentence in a novel by a simpler way. This method determines the emotion of a sentence according to an emotion that words such as a verb in a Japanese verb sentence, and an adjective and an adverb in a adjective sentence, have. The emotional characteristics that these words have are prepared beforehand as a emotional words dictionary by us. The emotions used here are seven types: "joy," "sorrow," "anger," "surprise," "terror," "aversion" or "neutral."

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.709-730
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• 2017

To address the challenge of unprecedented growth in mobile data traffic, ultra-dense network deployment is a cost efficient solution to offload the traffic over some small cells. The overlapped coverage areas of small cells create more than one candidate access points for one mobile user. Signal strength based user association in IEEE 802.11 results in a significantly unbalanced load distribution among access points. However, the effective bandwidth demand of each user actually differs vastly due to their different preferences for mobile applications. In this paper, we formulate a set of non-linear integer programming models for joint user association control and user demand guarantee problem. In this model, we are trying to maximize the system capacity and guarantee the effective bandwidth demand for each user by soft-association control with a software defined network controller. With the fact of NP-hard complexity of non-linear integer programming solver, we propose a Kernighan Lin Algorithm based graph-partitioning method for a large-scale network. Finally, we evaluated the performance of the proposed algorithm for the edge users with heterogeneous bandwidth demands and mobility scenarios. Simulation results show that the proposed adaptive soft-association control can achieve a better performance than the other two and improves the individual quality of user experience with a little price on system throughput.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1561-1566
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• 2017

Due to the advances in machine learning and artificial intelligence technologies, many new services have become available. Among such services, recommendation systems have already been successfully applied to commercial services and made profits as in online shopping malls. Most recommendation algorithms in commercial services are based on content analysis or explicit feedback rates as in movie recommendations. However, many online shopping malls have difficulties in content analysis or are lacking explicit feedbacks on their items, which results in no recommendation system for their items. Even for such service systems, user log data is easily available, and if recommendations are possible with such log data, the quality of their service can be improved. In this paper, we extract implicit feedback like click information for items from log data and provide a recommendation system based on the implicit feedback. The proposed system is applied to a real in-service online shopping mall.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.81-97
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• 2003

In this paper, we suggest a method of robust watermarking for protection of multimedia data using the wavelet transform and artificial neural network. for the purpose of implementation, we decompose a original image using wavelet transform at level 3. After we classify transformed coefficients of other subbands using neural network except fur the lowest subband LL$_3$, we apply a calculated threshold about chosen cluster as the biggest. We used binary logo watermarks to make sure that it is true or not on behalf of the Gaussian Random Vector. Besides, we tested a method of dual watermark insertion and extraction. For the purpose of implementation, we decompose a original image using wavelet transform at level 3. After we classify transformed coefficients of other subbands using neural network except for the lowest subband LL$_3$, we apply a above mentioned watermark insert method. In the experimental results, we found that it has a good quality and robust about many attacks.

• Journal of the korean society of oceanography
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• v.32 no.4
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• pp.163-170
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• 1997

Some CMP gathers acquired from shallow marine seismic reflection survey in offshore Korea do not show the hyperbolic trend of moveout. It originated from so-called swell effect of source and streamer, which are towed under rough sea surface during the data acquisition. The observed time deviations of NMO-corrected traces can be entirely ascribed to the swell effect. To correct these time deviations, a residual statics is introduced using Genetic Algorithms (GA) into the swell correction. A new class of global optimization methods known as GA has recently been developed in the field of Artificial Intelligence and has a resemblance with the genetic evolution of biological systems. The basic idea in using GA as an optimization method is to represent a population of possible solutions or models in a chromosome-type encoding and manipulate these encoded models through simulated reproduction, crossover and mutation. GA parameters used in this paper are as follows: population size Q=40, probability of multiple-point crossover P$_c$=0.6, linear relationship of mutation probability P$_m$ from 0.002 to 0.004, and gray code representation are adopted. The number of the model participating in tournament selection (nt) is 3, and the number of expected copies desired for the best population member in the scaling of fitness is 1.5. With above parameters, an optimization run was iterated for 101 generations. The combination of above parameters are found to be optimal for the convergence of the algorithm. The resulting reflection events in every NMO-corrected CMP gather show good alignment and enhanced quality stack section.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.71-79
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• 2021

In the manufacturing industry, there is a transition to multi-item production for reinforcement of competitiveness. Therefore, the hybrid manufacturing technology is increasing. Especially, many efforts in production quality improvement are made through the adoption of the manufacturing execution system and ERP, so it is necessary to operate MES for prompt and effective management. MES should improve ineffective parts in production activities while managing all stages related to production of products. If there is change in the process, the changed items should be reflected to the system. However, most manufacturing execution systems are operated passively and repetitively by system administrators. This study presents a model that system administrators can comprehensively apply reference information about production related requirements on specific line's equipment to the same equipment of other lines. The flexible response for application to production lines is possible thanks to the division of blanket application and selective application of reference information through proposed model.

• Smart Media Journal
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• v.10 no.2
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• pp.30-37
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• 2021

Recently, 3D contents used in various fields have been attracting people's attention due to the development of virtual reality and augmented reality technology. In order to produce 3D contents, it is necessary to model the objects as vertices. However, high-quality modeling is time-consuming and costly. In order to convert a 2D character into a 3D model, it is necessary to express it as line drawings through feature line extraction. The extraction of consistent line drawings from 2D cartoon cartoons is difficult because the styles and techniques differ depending on the designer who produces them. Therefore, it is necessary to extract the line drawings that show the geometrical characteristics well in 2D cartoon shapes of various styles. This study proposes a method of automatically extracting line drawings. The 2D Cartoon shading image and line drawings are learned by using adversarial network model, which is artificial intelligence technology and outputs 2D cartoon artwork of various styles. Experimental results show the proposed method in this research can be obtained as a result of the line drawings representing the geometric characteristics when a 2D cartoon painting as input.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3917-3941
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• 2019

The recent interest in artificial intelligence and machine learning has partly contributed to an interest in the use of such approaches for hyperspectral remote sensing (HRS) imagery classification, as evidenced by the increasing number of deep framework with deep convolutional neural networks (CNN) structures proposed in the literature. In these approaches, the assumption of obtaining high quality deep features by using CNN is not always easy and efficient because of the complex data distribution and the limited sample size. In this paper, conventional handcrafted learning-based multi features based on expert knowledge are introduced as the input of a special designed CNN to improve the pixel description and classification performance of HRS imagery. The introduction of these handcrafted features can reduce the complexity of the original HRS data and reduce the sample requirements by eliminating redundant information and improving the starting point of deep feature training. It also provides some concise and effective features that are not readily available from direct training with CNN. Evaluations using three public HRS datasets demonstrate the utility of our proposed method in HRS classification.

• Journal of Arbitration Studies
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• v.28 no.3
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• pp.35-53
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• 2018

The purpose of this paper is to focus on the development of the arbitration system, such as the establishment of the arbitration industry and expanding the scope of arbitration fields. The solution method of arbitration differs greatly from that of the court's trial process. This can be seen in the way of autonomous conflict resolution. Therefore, the role of arbitrator is a very important function. In this sense, it seems necessary to establish a professional arbitrator system. Now the Arbitration Promotion Act has been enacted and interest in the arbitration industry is also rising. It is necessary to deal effectively with new incidents according to changes in the legal environment internationally. In order to do this, it is imperative to train professional arbitrators. A training plan for arbitration manager to assist this is now under consideration. The coming of the Fourth Industrial Revolution and the growth of artificial intelligence (AI) technology will simply stop the uniform way of determining winners by lawsuits. Even in new companies entering new markets as well as overseas companies, assistance from arbitration experts is indispensable in order to effectively deal with international trade disputes that will develop in the future. In addition to fostering the arbitration industry, it is necessary to train experts in domestic and foreign arbitration and arbitration practitioners to provide high-quality legal services. For these human resource development measures, we will explore the subject and procedural methods. The Arbitrators Association should concentrate on these matters and be cautious when focusing on the training of arbitrators and arbitration managers through the selection process. The Arbitrators Association must strengthen the level of new education (designation / consignment). Measures must be taken in order to grant such procedures as well as subsequent steps.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.151-160
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• 2019

EPC companies to continue operating overseas, it is increasingly becoming apparent that risk is no longer something to be avoided but a subject to be managed. During the bidding stage, the requirements, specifications and project line items within the bid package must be studied in details to analyze the various risk factors in order to avoid cost overruns. However, reviewing vast quantities of bidding documents is time consuming and labor intensive and is not an easy task and this is where automated information technology can help. For this study, I have constructed an ITB analysis model based on Watson AI that can analyze and apply vast amount of documents more effectively in a short time. Configuration of the Watson Explorer AI architecture for AI-based ITB risk management model research, the selection of learning procedures and analysis subjects, and the performance evaluation criteria were defined, and a test bed was constructed to conduct a pilot research. Consequently, I verified the effectiveness of the analytical time reduction and the quality of its results and VOC operations by professionals.