• Journal of Advanced Navigation Technology
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• v.12 no.6
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• pp.591-597
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• 2008

With the established voice service, the data service is increasing in the field of mobile telecommunications in these days. Also, the data service develops into the form of multimedia service which combines various media. However, it is limited to provide QoS(Quality of Service) for the multimedia using the established network which manages all the data in sam: rule. So, this paper suggests the network architecture which assures QoS of multimedia data by applying MPLS(Multi-Protocol Label Switching) to the core network. Especially, we analyze the efficiency of the network combining Mobile IP network based on the WLAN(Wireless LAN) and core network based on MPLS through by network simulations using QualNet.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.12
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• pp.814-819
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• 2008

The purpose of this study was developing the building materials for creation the comfortable IAQ. By reducing formaldehyde(HCHO) known as the main factors of Sick House Syndrome. This material must be revealed the physical and eco-friendly performance, so this study set up the basic standards for building materials. The source of physical performance evaluation is Korea Industrial Standards and the base of environmental ability is the Eco Label considering certificated system related to an apartment house. Because the developed material was satisfied with the established standards, it was tested in mock-up room for obtaining the real date from indoor air. The mock-up test was conducted according environmental standard method for indoor air Quality of the ministry of environment. The result of this study were as follows; the functional building materials had a effect to reduce the formaldehyde concentration for a initial period without wall paper, so additional development is needed for application with the wall paper and the available period.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.300-312
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• 2021

Compressed sensing (CS) has been investigated in magnetic resonance (MR) parametric mapping to reduce scan time. However, the relatively long reconstruction time restricts its widespread applications in the clinic. Recently, deep learning-based methods have shown great potential in accelerating reconstruction time and improving imaging quality in fast MR imaging, although their adaptation to parametric mapping is still in an early stage. In this paper, we proposed a novel deep learning-based framework DEMO for fast and robust MR parametric mapping. Different from current deep learning-based methods, DEMO trains the network in an unsupervised way, which is more practical given that it is difficult to acquire large fully sampled training data of parametric-weighted images. Specifically, a CS-based loss function is used in DEMO to avoid the necessity of using fully sampled k-space data as the label, thus making it an unsupervised learning approach. DEMO reconstructs parametric weighted images and generates a parametric map simultaneously by unrolling an interaction approach in conventional fast MR parametric mapping, which enables multi-tasking learning. Experimental results showed promising performance of the proposed DEMO framework in quantitative MR T1ρ mapping.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1151-1151
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• 2001

The international coffee trade is conducted almost exclusively with green coffee. The main coffee producing countries include Brazil, Columbia, Indonesia, Mexico and the Ivory Coast. About 99 % of the coffee grown throughout the world belong to two coffee plant varieties that are commonly known as Arabica and Robusta. The quality of green coffee can be assessed according to several ISO standards (1,2,3,4,5). However, no official international standards for the authenticity of green coffee have been issued. It is important to know the country of origin of the coffee for the purposes of fair international trade. The geographic origin of the coffee is often stated on the label of coffee products such as speciality roasted and soluble coffees. Near Infrared Spectroscopy (NIR) is an accepted technique for quantitative analysis of various parameters in routine QC analysis of food products. It would appear to be a promising candidate as a tool for identification of green coffee origin and numerous feasibility studies have appeared in the literature on its use for soluble, roasted and green coffee variety identification as well as identification of arabica or robusta coffees. NIR spectrophotometers when configured in the reflectance mode are able to perform a complete profile of the NIR spectrum on whole beans. The data can then be interpreted by discriminant chemometrics data analysis. This is the approach used in the present study.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.98-102
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• 2023

This paper presents a study on how augmenting semi-synthetic image data improves the performance of human detection algorithms. In the field of object detection, securing a high-quality data set plays the most important role in training deep learning algorithms. Recently, the acquisition of real image data has become time consuming and expensive; therefore, research using synthesized data has been conducted. Synthetic data haves the advantage of being able to generate a vast amount of data and accurately label it. However, the utility of synthetic data in human detection has not yet been demonstrated. Therefore, we use You Only Look Once (YOLO), the object detection algorithm most commonly used, to experimentally analyze the effect of synthetic data augmentation on human detection performance. As a result of training YOLO using the Penn-Fudan dataset, it was shown that the YOLO network model trained on a dataset augmented with synthetic data provided high-performance results in terms of the Precision-Recall Curve and F1-Confidence Curve.

• Journal of Communications and Networks
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• v.6 no.3
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• pp.269-279
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• 2004

A new online multi-layer integrated routing (MLIR) scheme that combines IP (electrical) layer routing with WDM (optical) layer routing is investigated. It is a highly efficient and cost-effective routing scheme viable for the next generation integrated optical Internet. A new simplified weighted graph model for the integrated optical Internet consisted of optical routers with multi-granularity optical-electrical hybrid switching capability is firstly proposed. Then, based on the proposed graph model, we develop an online integrated routing scheme called differentiated weighted fair algorithm (DWFA) employing adaptive admission control (routing) strategies with the motivation of service/bandwidth differentiation, which can jointly solve multi-layer routing problem by simply applying the minimal weighted path computation algorithm. The major objective of DWFA is fourfold: 1) Quality of service (QoS) routing for traffic requests with various priorities; 2) blocking fairness for traffic requests with various bandwidth granularities; 3) adaptive routing according to the policy parameters from service provider; 4) lower computational complexity. Simulation results show that DWFA performs better than traditional overlay routing schemes such as optical-first-routing (OFR) and electrical-first-routing (EFR), in terms of traffic blocking ratio, traffic blocking fairness, average traffic logical hop counts, and global network resource utilization. It has been proved that the DWFA is a simple, comprehensive, and practical scheme of integrated routing in optical Internet for service providers.

• Archives of design research
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• v.15 no.1
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• pp.69-79
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• 2002

The Korean textile industry contributed much to the country's economic success during the 1970s-80s. Since the end of the 1980s, however, most of the Korean textile industry has begun to suffer from both high labor costs and skilled-labor shortage. During this period, such countries as China, Indonesia, and Malaysia began to gain strong foothold in the global textile market, mainly owing to considerably low label costs. To maintain competitiveness in the global textile market, the Korean textile industry should undergo a structural change. It should switch from the mass production of low quality design to selective praction of high quality and well-designed textiles. An cement of high value-added should be put into the textile product.: Usage of functional material, new processing technology, automation, pro-environmental dye shes, and strategic marketing is required. In this appear, I suggest ways and means to make the Korean textile design be good enough to compete in the global market.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.511-523
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• 2007

In broadband convergence network(BcN), heterogeneous broadband wired & wireless subnetworks and various terminal equipments will be interconnected. In order to provide end-to-end realtime multimedia services on such heterogeneous networking environment, as a result, two major problems should be resolved: i) Multimedia session establishment & negotiation that adjusts the differences in the capability of multimedia data processing at the end terminal nodes, ii) quality of service(QoS)-guaranteed connection establishment or resource reservation with connection admission control(CAC) in each heterogeneous subnetworks along the path. The session layer signaling(e.g., SIP/SDP) should be extended for QoS negotiation, and must be tightly cooperating with network layer signaling or resource reservation with CAC function. In this paper we propose a session and connection management architecture for the QoS-guaranteed realtime multimedia service provisioning on BcN, with Q-SIP/SDP, resource reservation protocol with traffic engineering extension, and CAC functions. The detailed interaction scenario and related algorithms for QoS-guaranteed realtime multimedia session, resource reservation and connection establishment are explained and analyzed. From the experimental implementation of the proposed scheme on a small scale BcN testbed, we verified that the proposed architecture is applicable for the realtime multimedia service provisioning. We analyze the network performance and QoS parameters in detail.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.143-153
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• 2022

With the development of networks and the increase in the number of network devices, the number of cyber attacks targeting them is also increasing. Since these cyber-attacks aim to steal important information and destroy systems, it is necessary to minimize social and economic damage through early detection and rapid response. Many studies using machine learning (ML) and artificial intelligence (AI) have been conducted, among which payload learning is one of the most intuitive and effective methods to detect malicious behavior. In this study, we propose a preprocessing method to maximize the performance of the model when learning the payload in term units. The proposed method constructs a high-quality learning data set by eliminating unnecessary noise (stopwords) and preserving important features in consideration of the machine language and natural language characteristics of the packet payload. Our method consists of three steps: Preserving significant special characters, Generating a stopword list, and Class label refinement. By processing packets of various and complex structures based on these three processes, it is possible to make high-quality training data that can be helpful to build high-performance ML/AI models for security monitoring. We prove the effectiveness of the proposed method by comparing the performance of the AI model to which the proposed method is applied and not. Forthermore, by evaluating the performance of the AI model applied proposed method in the real-world Security Operating Center (SOC) environment with live network traffic, we demonstrate the applicability of the our method to the real environment.

• Korean Journal of Food Science and Technology
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• v.24 no.5
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• pp.492-496
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• 1992

In order to compare the quality of canned pork products which are called collectively as luncheon meat, residual nitrite, sodium, collagen, total heme pigments and chemical composition were analyzed in 12 products of 8 companies from 4 countries. Also, the proteins of products were compared with that of pork by SDS-PAGE analysis. The level of residual nitrite was low in all the products and sodium levels were similar except in one or two products. As for collagen and total heme pigments content, among imported products luncheon meats were different from chopped meat products while domestic products were similar regardless of label distinction. Collagen contents of domestic products were similar to those of imports but total heme pigments contents were much higher Densitometer scans of gel electrophoretograms of chopped meat were more similar to that of pork than those of luncheon meat. In terms of chemical composition, luncheon meat had more carbohydrate regardless of whether they are domestics or imports. The quality of domestic luncheon meat appears to be the composite of those of imported luncheon meat and chopped meat. Accordingly, the quality standard for luncheon meat as a cheap product should be established in Korea to enable the domestic products to have a competitive power in price.