• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3A
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• pp.269-278
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• 2010

There are tendency that wireless sensor network is one of the important techniques for the future IT industry and thereby application areas in it are getting growing. Researches based on the hierarchical network topology are evaluated in good at energy efficiency in related protocols for wireless sensor network. LEACH is the best well known routing protocol for the hierarchical topology. However, there are problems in the range of message broadcasting, which should be expand into the overall network coverage, in LEACH related protocols. This dissertation proposes a new routing protocol to solve the co-shared problems in the previous protocols. The basic idea of our scheme is using the table for nodes connectivity and node energy information. The results show that the proposed protocol could support the load balancing by distributing the clusters with a reasonable number of member nodes and thereby the network life time would be extended in about 1.8 times longer than LEACH.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.3
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• pp.353-364
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• 1998

Consumer knowledge has been discussed as an important concept to understand information processing such as information search and evaluation process. It has been defined as the amounts and contents of information in consumer's memory accumulated by experiences. According to literature review, experts who have much knowledge are likely to retrieve their information related to products for a purchase efficiency. Therefore, they are likely to simplify the information processing for a choice. The purpose of this study was to examine the relationship between clothing product knowledge and evaluative criteria for a purchase. The results were as follows; First, it was found out that evaluative criteria were composed of four dimensions such as the management, the esthetic, the fitness and the brand. Therefore, it is implied that evaluative criteria for purchasing clothing products were multidimensional. Second, the level of objective knowledge was low, and consumers perceived that they didn't have much knowledge related with clothing products. Also, the relationships between objective and subjective knowledge were positive but low. Third, the evaluative criteria were effected by the level of consumer's knowledge significantly. In subjective knowledge, the subjects in a high group considered all criteria more deeply than in a low group. But there was a significant difference only in the esthetic between two groups in objective knowledge. The results of this study imply that consumer knowledge may influence evaluation process. Knowledgeable consumer would consider product attributes deeply for evaluating clothing products, and especially, the esthetic would be an important factor as an attribute including the instrumental and expressive functions in a purchase phase. Therefore, consumer knowl- edge would be a basis of predicting expert's information processing and managing heavy buyer or loyal consumers in apparel industry.

• Fashion & Textile Research Journal
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• v.2 no.3
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• pp.220-226
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• 2000

This study was to determine the characteristics of vapor-permeable waterproof finished fabric by the coating method. 4 different kinds of coating fabrics (A : wet, porous, polyurethane, B : dry, no porous, polyurethane, C : shape memory polyurethane and D : dry, porous polyurethane) were used, which were developed recently With this sample, moisture transport rate ($40^{\circ}C$, 45%RH & $40^{\circ}C$, 95%RH), changes of coating side's shape by washing times, water repellency rate, contracted length, qmax, heat conductivity, heat keeping rate, heat keeping rate with cotton, heat keeping rate on humidity temperature and humidity within clothing etc. were checked. And it was done in a climate chamber under $20{\pm}2^{\circ}C$, $65{\pm}5%RH$. The results of this study were as follow; In the moisture vapor transmission of sample B and C increased on high temperature and high humidity while sample A and D decreased, on this condition. Qmax rate had high relation with ground fabric's surface properties and the order was A>C>D>B. Heat conductivity had high relation with thickness and surface properties. Heat keeping rates on sweat condition showed around half percents of heat keeping rates on normal condition, but had no relation with moisture vapor transport rate. Changes of the fabric's properties by washing times were different in accordance with the construction of fabrics and the coating resin. Sample C had tow heat keeping rate on the high temperature and humidity and high heat keeping rate on the low temperature and humidity Moisture transport rate of vapor-permeable waterproof finished fabrics had high relation with the properties of ground fabrics on low humidity condition, but on the high humidity condition, it was highly related with the properties of coating resin.

• Journal of Information Technology and Architecture
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• v.11 no.2
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• pp.201-216
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• 2014

The internet and the information-oriented communities have brought many changes to increase brand power and product sales in many industries. This study investigates the influence of brand preference and information reliability on consumers' purchase decisions. If product information at the internet advertising matches with consumers' previous brand preference, they are more likely to enhance product information reliability after watching the advertising. Such brand preference match through the advertising will increase consumers' intention to purchase. From the results of our experiment, we found that information reliability and memory from the advertising give a positive impact on the intention to purchase when consumers' previous brand preference matches with advertising attributes. Our study suggests that firms need to develop the internet advertising which is closely matched with consumers' preferences.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.242-242
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• 2006

Increasingly complex tasks are performed by computers or cellular phone, requiring more and more memory capacity as well as faster and faster processing speeds. This leads to a constant need to develop more highly integrated circuit systems. Therefore, there have been numerous studies by many engineers investigating circuit patterning. In particular, PCB including module/package substrates such as FCB (Flip Chip Board) has been developed toward being low profile, low power and multi-functionalized due to the demands on miniaturization, increasing functional density of the boards and higher performances of the electric devices. Imprint lithography have received significant attention due to an alternative technology for photolithography on such devices. The imprint technique. is one of promising candidates, especially due to the fact that the expected resolution limits are far beyond the requirements of the PCB industry in the near future. For applying imprint lithography to FCB, it is very important to control thermal properties and mechanical properties of dielectric materials. These properties are very dependent on epoxy resin, curing agent, accelerator, filler and curing degree(%) of dielectric materials. In this work, the epoxy composites filled with silica fillers and cured with various accelerators having various curing degree(%) were prepared. The characterization of the thermal and mechanical properties wasperformed by thermal mechanical analysis (TMA), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), rheometer, an universal test machine (UTM).

• Journal of the Korea Computer Industry Society
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• v.3 no.3
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• pp.321-330
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• 2002

A 2-D median filter has many applications in various image and video signal processing areas. The rapid development in VLSI technology makes it possible to implement a real-time or near real-time 2-D median filter with reasonable cost. For the efficient VLSI implementation, the algorithm should have characteristics such as small memory requirements, regular computations, and local data transfers. This paper presents an architecture of the real-time two-dimensional separable median filter which has appropriate characteristics for the VLSI implementation. For the efficient two-dimensional median filter, a separable two-dimensional median filtering structure and a bit-sliced pipelined median searching algorithm are used. A behavioral simulator is implemented with C language and used for the analysis of the presented architecture.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.267-276
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• 2021

The automotive industry and academic research have been continuously conducting research on standardization such as AUTOSAR (AUTomotive Open System ARchitecture) and ISO26262 to solve problems such as safety and efficiency caused by the complexity of electric/electronic architecture of automotive. AUTOSAR is an automotive standard software platform that has a layered structure independent of MCU (Micro Controller Unit) hardware, and improves product reliability through software modularity and reusability. And, ISO26262, an international standard for automotive functional safety and suggests a method to minimize errors in automotive ECU (Electronic Control Unit)s by defining the development process and results for the entire life cycle of automotive electrical/electronic systems. These design methods are variously applied in representative automotive safety-critical systems. However, since the functional and safety requirements are different according to the characteristics of the safety-critical system, it is essential to research the AUTOSAR functional safety design method specialized for each application domain. In this paper, a software functional safety mechanism design method using AUTOSAR is proposed, and a new failure management framework is proposed to ensure the high reliability of the product. The AUTOSAR functional safety mechanism consists of memory partitioning protection, timing monitoring protection, and end-to-end protection. The fault management framework is composed of several safety SWCs to maintain the minimum function and performance even if a fault occurs during the operation of a safety-critical system. Finally, the proposed method is applied to the Shift-by-Wire system design to prove the validity of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.179-184
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• 2021

In this paper, we propose the deep learning-based neural network model to predict bunker price. In the shipping industry, since fuel oil accounts for the largest portion of ship operation costs and its price is highly volatile, so companies can secure market competitiveness by making fuel oil purchasing decisions based on rational and scientific method. In this paper, short-term predictive analysis of HSFO 380CST in Singapore is conducted by using three recurrent neural network models like RNN, LSTM, and GRU. As a result, first, the forecasting performance of RNN models is better than LSTM and GRUs using long-term memory, and thus the predictive contribution of long-term information is low. Second, since the predictive performance of recurrent neural network models is superior to the previous studies using econometric models, it is confirmed that the recurrent neural network models should consider nonlinear properties of bunker price. The result of this paper will be helpful to improve the decision quality of bunker purchasing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2304-2320
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• 2021

Intelligently detecting anomalies in health sensor data streams (e.g., Electrocardiogram, ECG) can improve the development of E-health industry. The physiological signals of patients are collected through sensors. Timely diagnosis and treatment save medical resources, promote physical health, and reduce complications. However, it is difficult to automatically classify the ECG data, as the features of ECGs are difficult to extract. And the volume of labeled ECG data is limited, which affects the classification performance. In this paper, we propose a Generative Adversarial Network (GAN)-based deep learning framework (called CAB) for heart arrhythmia classification. CAB focuses on improving the detection accuracy based on a small number of labeled samples. It is trained based on the class-imbalance ECG data. Augmenting ECG data by a GAN model eliminates the impact of data scarcity. After data augmentation, CAB classifies the ECG data by using a Bidirectional Long Short Term Memory Recurrent Neural Network (Bi-LSTM). Experiment results show a better performance of CAB compared with state-of-the-art methods. The overall classification accuracy of CAB is 99.71%. The F1-scores of classifying Normal beats (N), Supraventricular ectopic beats (S), Ventricular ectopic beats (V), Fusion beats (F) and Unclassifiable beats (Q) heartbeats are 99.86%, 97.66%, 99.05%, 98.57% and 99.88%, respectively. Unclassifiable beats (Q) heartbeats are 99.86%, 97.66%, 99.05%, 98.57% and 99.88%, respectively.

• Journal of the Korean institute of surface engineering
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• v.53 no.6
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• pp.330-342
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• 2020

Since the original report on ferroelectricity in Si-doped HfO2 in 2011, fluorite-structured ferroelectrics have attracted increasing interest due to their scalability, established deposition techniques including atomic layer deposition, and compatibility with the complementary-metal-oxide-semiconductor technology. Especially, the emerging fluorite-structured ferroelectrics are considered promising for the next-generation semiconductor devices such as storage class memories, memory-logic hybrid devices, and neuromorphic computing devices. For achieving the practical semiconductor devices, understanding polarization switching kinetics in fluorite-structured ferroelectrics is an urgent task. To understand the polarization switching kinetics and domain dynamics in this emerging ferroelectric materials, various classical models such as Kolmogorov-Avrami-Ishibashi model, nucleation limited switching model, inhomogeneous field mechanism model, and Du-Chen model have been applied to the fluorite-structured ferroelectrics. However, the polarization switching kinetics of fluorite-structured ferroelectrics are reported to be strongly affected by various nonideal factors such as nanoscale polymorphism, strong effect of defects such as oxygen vacancies and residual impurities, and polycrystallinity with a weak texture. Moreover, some important parameters for polarization switching kinetics and domain dynamics including activation field, domain wall velocity, and switching time distribution have been reported quantitatively different from conventional ferroelectrics such as perovskite-structured ferroelectrics. In this focused review, therefore, the polarization switching kinetics of fluorite-structured ferroelectrics are comprehensively reviewed based on the available literature.