• Proceedings of the KIPE Conference
• /
• 2019.11a
• /
• pp.166-167
• /
• 2019

Smart windows are used as windows and doors to determine cooling and heating efficiency in the construction field. It's characteristics can increase the energy saving efficiency. In addition, the function of the smart window that can control the light transmittance transmitted from the external environment of the building to the building according to the needs of the user is attracting attention. In this study, a liquid crystal cell capable of controlling light transmittance of 297 × 210 ㎟ was fabricated by using a liquid crystal device as an optical shutter. Analysis of transmittance change according to driving voltage and driving stability according to thermal environment, We confirmed the applicability of building exterior materials as smart windows.

• Elastomers and Composites
• /
• v.57 no.2
• /
• pp.62-72
• /
• 2022

Passive daytime radiative cooling (PDRC) is attracting increasing attention as an eco-friendly technology that can save cooling energy by not requiring an external power supply. An ideal PDRC structure should improve solar reflectance and emissivity within the atmospheric spectral window. Early designs of photonic crystal materials demonstrated the benefits of PDRC. Since then, functional arrangements of polymer-based radiative cooling materials have played an important role and are rapidly expanding. This review summarizes the known inorganic, organic, and hybrid materials for PDRC. The review also provides a complete understanding of PDRC and highlights its practical applications.

• Journal of KIISE:Software and Applications
• /
• v.32 no.11
• /
• pp.1121-1135
• /
• 2005

This paper proposes a moving object extraction method using the contrast map and salient points. In order to make the contrast map, we generate three-feature maps such as luminance map, color map and directional map and extract salient points from an image. By using these features, we can decide the Attention Window(AW) location easily The purpose of the AW is to remove the useless regions in the image such as background as well as to reduce the amount of image processing. To create the exact location and flexible size of the AW, we use motion feature instead of pre-assumptions or heuristic parameters. After determining of the AW, we find the difference of edge to inner area from the AW. Then, we can extract horizontal candidate region and vortical candidate region. After finding both horizontal and vertical candidates, intersection regions through logical AND operation are further processed by morphological operations. The proposed algorithm has been applied to many video sequences which have static background like surveillance type of video sequences. The moving object was quite well segmented with accurate boundaries.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.11B
• /
• pp.891-899
• /
• 2004

Ethernet passive optical network (EPON) has drawn many attention as a promising access network technology because it can provide a high bandwidth with a low cost. Since the uplink in the EPON system is shared by many users, it is necessary for an EPON system to have an efficient bandwidth allocation mechanism. In addition, as the users demand more QoS-oriented applications, it is necessary for an EPON system to have an efficient mechanism supporting QoS. In this paper, we propose a variable window dynamic bandwidth allocation (DBA) algorithm for the EPON system. Unlike the previously proposed DBA algorithms, the variable window algorithm guarantees the QoS for the highest priority class, and at the same time provides more enhanced QoS for the lower priority classes by dynamically allocating bandwidth if necessary. It is verified through the simulations that the variable window algorithm can provide more enhanced QoS performance than other DBA algorithms.

• IEIE Transactions on Smart Processing and Computing
• /
• v.1 no.3
• /
• pp.133-142
• /
• 2012

This paper presents a salient region detection algorithm for auto-focusing based on the characteristics of a human's visual attention. To describe the saliency at the local, regional, and global levels, this paper proposes a set of novel features including multi-scale local contrast, variance, center-surround entropy, and closeness to the center. Those features are then prioritized to produce a saliency map. The major advantage of the proposed approach is twofold; i) robustness to changes in focus and ii) low computational complexity. The experimental results showed that the proposed method outperforms the existing low-level feature-based methods in the sense of both robustness and accuracy for auto-focusing.

• Asia pacific journal of information systems
• /
• v.30 no.4
• /
• pp.719-740
• /
• 2020

The stock market changes continuously as new information emerges, affecting the judgments of investors. Online news articles are valued as a traditional window to inform investors about various information that affects the stock market. This paper proposed new ways to utilize online news articles with technical indicators. The suggested hybrid model consists of three models. First, a self-attention-based convolutional neural network (CNN) model, considered to be better in interpreting the semantics of long texts, uses news content as inputs. Second, a self-attention-based, bi-long short-term memory (bi-LSTM) neural network model for short texts utilizes news titles as inputs. Third, a bi-LSTM model, considered to be better in analyzing context information and time-series models, uses 19 technical indicators as inputs. We used news articles from the previous day and technical indicators from the past seven days to predict the share price of the next day. An experiment was performed with Korean stock market data and news articles from 33 top companies over three years. Through this experiment, our proposed model showed better performance than previous approaches, which have mainly focused on news titles. This paper demonstrated that news titles and content should be treated in different ways for superior stock price prediction.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.12
• /
• pp.1020-1026
• /
• 2005

In the era of ubiquitous computing, human-friendly man-machine interface is getting more attention due to its possibility to offer convenient services. For this, in this paper, we introduce a 'Half-Mirror Interface System (HMIS)' as a novel type of human-friendly man-machine interfaces. Basically, HMIS consists of half-mirror, USB-Webcam, microphone, 2ch-speaker, and high-speed processing unit. In our HMIS, two principal operation modes are selected by the existence of the user in front of it. The first one, 'mirror-mode', is activated when the user's face is detected via USB-Webcam. In this mode, HMIS provides three basic functions such as 1) make-up assistance by magnifying an interested facial component and TTS (Text-To-Speech) guide for appropriate make-up, 2) Daily weather information provider via WWW service, 3) Health monitoring/diagnosis service using Chinese medicine knowledge. The second one, 'display-mode' is designed to show decorative pictures, family photos, art paintings and so on. This mode is activated when the user's face is not detected for a time being. In display-mode, we also added a 'healing-window' function and 'healing-music player' function for user's psychological comfort and/or relaxation. All these functions are accessible by commercially available voice synthesis/recognition package.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.10a
• /
• pp.589-590
• /
• 2010

Recently, as various smart phones released smart phones are becoming popular.Accordingly, the growing interest in mobile information service or advertising serviece, and attention has been concentrated in the mobile environment. These servieces should be carried out smoothly in the all situation (cannot access mobile Wi-Fi networks and 3G services), and should have the uniqueness that is fit for purpose. In this papaer, module for a particular purpose of the foundation of specialized location-based map services was implemented using a Packing R-tree by using a GIS engine based on Microsoft Window Mobile and Android operating system without communication device like 3G or Wi-Fi.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.9
• /
• pp.2323-2340
• /
• 2012

Recent advances in cognitive radio technology have drawn immense attention to higher layer protocols above medium access control, such as transmission control protocol (TCP). Most proposals to improve the TCP performance in cognitive radio (CR) networks have assumed that either all nodes are in CR networks or the TCP sender side is in CR links. In those proposals, lower layer information such as the CR link status could be easily exploited to adjust the congestion window and improve throughput. In this paper, we consider a TCP network in which the TCP sender is located remotely over the Internet while the TCP receiver is connected by a CR link. This topology is more realistic than the earlier proposals, but the lower layer information cannot be exploited. Under this assumption, we propose an enhanced TCP protocol for CR networks called TCP for cognitive radio (TCP-CR) to improve the existing TCP by (1) detection of primary user (PU) interference by a remote sender without support from lower layers, (2) delayed congestion control (DCC) based on PU detection when the retransmission timeout (RTO) expires, and (3) exploitation of two separate scales of the congestion window adapted for PU activity. Performance evaluation demonstrated that the proposed TCP-CR achieves up to 255% improvement of the end-to-end throughput. Furthermore, we verified that the proposed TCP does not deteriorate the fairness of existing TCP flows and does not cause congestions.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.8
• /
• pp.3946-3965
• /
• 2018

Network anomaly detection in Software Defined Networking, especially the detection of DDoS attack, has been given great attention in recent years. It is convenient to build the Traffic Matrix from a global view in SDN. However, the monitoring and management of high-volume feature-rich traffic in large networks brings significant challenges. In this paper, we propose a moving window Principal Components Analysis based anomaly detection and mitigation approach to map data onto a low-dimensional subspace and keep monitoring the network state in real-time. Once the anomaly is detected, the controller will install the defense flow table rules onto the corresponding data plane switches to mitigate the attack. Furthermore, we evaluate our approach with experiments. The Receiver Operating Characteristic curves show that our approach performs well in both detection probability and false alarm probability compared with the entropy-based approach. In addition, the mitigation effect is impressive that our approach can prevent most of the attacking traffic. At last, we evaluate the overhead of the system, including the detection delay and utilization of CPU, which is not excessive. Our anomaly detection approach is lightweight and effective.