• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.1
• /
• pp.343-347
• /
• 2012

Non-linear equalization techniques using decision feedback structure are highly demanded for cancellation of intersymbol interferences occurred in severe channel environments. In this paper decision feedback structure is applied to the linear blind equalizer algorithm that is based on information theoretic learning and a randomly generated symbol set. At the decision feedback equalizer (DFE) the random symbols are generated to have the same probability density function (PDF) as that of the transmitted symbols. By minimizing difference between the PDF of blind DFE output and that of randomly generated symbols, the proposed DFE algorithm produces equalized output signal. From the simulation results, the proposed method has shown enhanced convergence and error performance compared to its linear counterpart.

• Journal of Korean Society for Geospatial Information Science
• /
• v.8 no.2 s.16
• /
• pp.117-127
• /
• 2000

The economic development and the development of medical treatment by scientific technology development progressed the level of national people life and improved average life gradually. In this reason, old people who have finance power would like to receive a comport and high level service, though paying proper expense. In this study, receiving this requirement, we focused that silver town have reasonable and comfortable residing environment in developing rural and rest form silver town objecting external area of Chon-Ju city, and selected land suitability. Through the learning of the neural network theory in the method of land suitability, we applied in the full of study area and improved a flexible determination making as giving each class value in each cell. Also, we compare a method of land suitability using the neural network theory, and it's analysis with a method of land suitability by the duplication method of Boolean Logic have been used In Geo Spatial Information System(GSIS) and proved the Boolean Logic's lose of values and the propriety.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.12
• /
• pp.111-121
• /
• 2021

As the main carrier of information, digital image is becoming more and more important. However, with the popularity of image acquisition equipment and the rapid development of image editing software, in recent years, digital image counterfeiting incidents have emerged one after another, which not only reduces the credibility of images, but also brings great negative impacts to society and individuals. Image copy-paste tampering is one of the most common types of image tampering, which is easy to operate and effective, and is often used to change the semantic information of digital images. In this paper, a method to protect the authenticity and integrity of image content by studying the tamper detection method of image copy and paste was proposed. In view of the excellent learning and analysis ability of deep learning, two tamper detection methods based on deep learning were proposed, which use the traces left by image processing operations to distinguish the tampered area from the original area in the image. A series of experimental results verified the rationality of the theoretical basis, the accuracy of tampering detection, location and classification.

• Journal of Satellite, Information and Communications
• /
• v.9 no.1
• /
• pp.51-56
• /
• 2014

High-availability seamless redundancy (HSR) is a protocol for fault-tolerant Ethernet (FTE) networks. It provides two frame copies and each copy is forwarded on a separate physical path, which provides zero fail-over time. Therefore, the HSR is becoming a potential candidate for various real-time FTE applications. However, the generation and circulation of unnecessary frames due to the duplication of every sending frame is inherent drawback of HSR. Such drawback degrades the performance of the network and may deplete its resources. In this paper, we present a new algorithm called port locking (PL) based on the media access control (MAC) address to solve the abovementioned problem in popular connected-rings network. Our approach makes the network gradually learn the locations of the source and the destination nodes without relying on network control frames. It then prunes all the rings that do not contain the destination node by locking corresponding rings' entrance ports. With the PL algorithm, the traffic can be significantly reduced and therefore the network performance will be greatly enhanced specially in a large scale connected-rings network. Analytical results are provided to validate the PL algorithm.

• The Journal of Information Systems
• /
• v.24 no.2
• /
• pp.23-52
• /
• 2015

Purpose This study aims to understand the role of digital knowledge in accepting the green technology. This study combined digital option theory with the second version of the Unified Theory of Acceptance and Use of Technology (UTAUT2). Contrary to other studies in which the UTAUT2 is used to explain IT adoption behavior, we look at the relationship between IT and the UTAUT2 from a new angle, incorporating an important aspect of IT, that is, digitized knowledge richness, as a determinant of the UTAUT2. Design/methodology/approach Grounded in the UTAUT2, a content analysis was conducted to investigate novel constructs dedicated to explaining green technology adoption. In this study, an amended version of the UTAUT2 specific to green technology is offered that better explains the green technology adoption behavior of consumers. Using the items identified by content analysis, we developed a questionnaire with 36 survey items. We measured all the items on a seven-point Likert-type scale. We randomly selected 402 survey respondents from a set of panel data. After a pilot study, we analyzed the main survey data by using PLS 2.0M3 and SPSS 20.0, and employed structural equation modeling to test the hypotheses. Findings The results suggest that the UTAUT2 was found to be extendable to technologies other than conventional IT. Social influence is more significant than conventional utilitarian and hedonic-based constructs such as those utilized in the UTAUT and UTAUT2 in explaining adoption behavior in the context of green technologies. The hypothesized connection between digitized knowledge richness and adoption intention was supported by the results of studies on the role of IT in formation of attitudes toward eco-friendly production. The results also indicate that digital knowledge can also encourage people to try green technology when they learn that their peers are already using the technology successfully.

• Geophysics and Geophysical Exploration
• /
• v.25 no.4
• /
• pp.227-241
• /
• 2022

Full waveform inversion (FWI) in the field of seismic data processing is an inversion technique that is used to estimate the velocity model of the subsurface for oil and gas exploration. Recently, deep learning (DL) technology has been increasingly used for seismic data processing, and its combination with FWI has attracted remarkable research efforts. For example, DL-based data processing techniques have been utilized for preprocessing input data for FWI, enabling the direct implementation of FWI through DL technology. DL-based FWI can be divided into the following methods: pure data-based, physics-based neural network, encoder-decoder, reparameterized FWI, and physics-informed neural network. In this review, we describe the theory and characteristics of the methods by systematizing them in the order of advancements. In the early days of DL-based FWI, the DL model predicted the velocity model by preparing a large training data set to adopt faithfully the basic principles of data science and apply a pure data-based prediction model. The current research trend is to supplement the shortcomings of the pure data-based approach using the loss function consisting of seismic data or physical information from the wave equation itself in deep neural networks. Based on these developments, DL-based FWI has evolved to not require a large amount of learning data, alleviating the cycle-skipping problem, which is an intrinsic limitation of FWI, and reducing computation times dramatically. The value of DL-based FWI is expected to increase continually in the processing of seismic data.

• Korean Journal of Cognitive Science
• /
• v.13 no.4
• /
• pp.80-80
• /
• 2002

The main thesis of this article is that the decisive point of creativity education is the cultivation of critical thinking capability. Although the narrow conception of creativity as divergent thinking is not subsumed under that of critical thinking, the role of divergent thinking is not so crucial in the science context of creative problem-solving. On the contrary, the broad conception of creativity as focusing on the reference to utility and the third conception of creativity as a process based on the variation and combination of existing pieces of information are crucial in creative problem-solving context, which are yet subsumed under that of critical thinking. The emphasis on critical thinking education is connected with the characteristics of contemporary knowledge-based society. This rapidly changing society requires situation-adaptive or situation-sensitive cognitive ability, whose core is critical thinking capability. Hence, the education of critical thinking is to be centered on the learning of blowing-how and procedural knowledge but not of knowing-that and declarative knowledge. Accordingly, the learning of critical thinking is to be headed towards the cultivation of competence but not just of performance. In conclusion, when a rational problem-solving through critical and logical thinking turns out consequently to be novel, we call it creative thinking. So, creativity is an emergent property based on critical and logical thinking.

• Korean Journal of Cognitive Science
• /
• v.13 no.4
• /
• pp.81-90
• /
• 2002

The main thesis of this article is that the decisive point of creativity education is the cultivation of critical thinking capability. Although the narrow conception of creativity as divergent thinking is not subsumed under that of critical thinking, the role of divergent thinking is not so crucial in the science context of creative problem-solving. On the contrary, the broad conception of creativity as focusing on the reference to utility and the third conception of creativity as a process based on the variation and combination of existing pieces of information are crucial in creative problem-solving context, which are yet subsumed under that of critical thinking. The emphasis on critical thinking education is connected with the characteristics of contemporary knowledge-based society. This rapidly changing society requires situation-adaptive or situation-sensitive cognitive ability, whose core is critical thinking capability. Hence, the education of critical thinking is to be centered on the learning of blowing-how and procedural knowledge but not of knowing-that and declarative knowledge. Accordingly, the learning of critical thinking is to be headed towards the cultivation of competence but not just of performance. In conclusion, when a rational problem-solving through critical and logical thinking turns out consequently to be novel, we call it creative thinking. So, creativity is an emergent property based on critical and logical thinking.

• The Journal of the Korea Contents Association
• /
• v.17 no.2
• /
• pp.288-297
• /
• 2017

Online education is a new domain of learning that combines distance learning with the practice of face-to-face instruction utilizing computer-mediated communication. As technology continues to develop and the needs of teachers require better access to higher learning, online graduate degree programs can be a valid alternative. Some institutions in the United States have already offered graduate degrees in music education through the online distance learning. In this study, 8 accredited online graduate degree programs in music education were identified in terms of curriculum requirement, program requirement, and admission requirement. Online programs offer considerable benefits of convenience, while their drawbacks relates to the quality of learning, feelings of weaker interpersonal interaction. More researches need in order for online music programmers to achieve higher standards of instruction and to inform other disciplines in the fields of arts education and the performing arts.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.326-327
• /
• 2021

Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.