• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.19-29
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• 2011

Until now, many face recognition methods have been proposed, most of them use a 1-dimensional feature vector which is vectorized the input image without feature extraction process or input image itself is used as a feature matrix. It is known that the face recognition methods using raw image yield deteriorated performance in databases whose have severe illumination changes. In this paper, we propose a face recognition method using local statistics of gradients and correlations which are good for illumination changes. BDIP (block difference of inverse probabilities) is chosen as a local statistics of gradients and two types of BVLC (block variation of local correlation coefficients) is chosen as local statistics of correlations. When a input image enters the system, it extracts the BDIP, BVLC1 and BVLC2 feature images, fuses them, obtaining feature matrix by $(2D)^2$ PCA transformation, and classifies it with training feature matrix by nearest classifier. From experiment results of four face databases, FERET, Weizmann, Yale B, Yale, we can see that the proposed method is more reliable than other six methods in lighting and facial expression.

• Korean Journal of Construction Engineering and Management
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• v.6 no.4 s.26
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• pp.101-112
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• 2005

Recently, a curtain wall construction is a exterior finishing components which is most used for shortening time in high-rise building as well as the class of key management factors in cost and schedule control. Also, it is recognized that an effective management for curtain wall process is a major subject to accomplish the project successfully. However, as the current management for curtain wall construction is focused on the construction stage, it makes problems such as errors in business performance, rework by mistakes and duplications, errors and omissions by ineffective information management and there has never been any efficient management from a view of the entire Curtain Wall Life-cycle process. Therefore, the aim of this study is to suggest a stage check point for process improvement in the curtain wall Life-cycle process through current curtain wall process analysis, and then to investigate the cause of waste factors using the Muda method from the Toyota Production System and extract the weighted effects of the waste factors using the analytical hierarchy process method. According to the result, Most of the inefficient factors happened in architectural design stage of the entire curtain wall Life-cycle process and my research identified that detail factors of them are a delay of decision making and an approval in changes, a deficit of engineering capacity and a delay of approval in architectural design drawings by owner, etc.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.209-220
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• 2004

The main feature of H.264 standard against conventional video standards is the high coding efficiency and the network friendliness. In spite of these outstanding features, it is not easy to implement H.264 codec as a real-time system due to its high requirement of memory bandwidth and intensive computation. Although the variable block size motion compensation using multiple reference frames is one of the key coding tools to bring about its main performance gain, it demands substantial computational complexity due to SAD (Sum of Absolute Difference) calculation among all possible combinations of coding modes to find the best motion vector. For speedup of motion estimation process, therefore, this paper proposes fast algorithms for both integer-pel and fractional-pel motion search. Since many conventional fast integer-pel motion estimation algorithms are not suitable for H.264 having variable motion block sizes, we propose the motion field adaptive search using the hierarchical block structure based on the diamond search applicable to variable motion block sizes. Besides, we also propose fast fractional-pel motion search using small diamond search centered by predictive motion vector based on statistical characteristic of motion vector.

• Journal of the Korean Institute of Gas
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• v.2 no.4
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• pp.60-66
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• 1998

The hot stove system is a process that is continuously and constantly generating the hot combustion air required for the blast furnace. The hot stove process is considered as a main energy consumption process because it consumes about $20\%$ of the total energy in steel making works. So, many researchers have interested in the improvement of the heat efficiency of the hot stove to reduce the energy consumption. But they have difficulties in improving the heat efficiency of the hot stove because there is no precise information on heat transformation occurring during the heating period. In order to model the relationship between the operating conditions and heat efficiencies, we propose a neural network using feature extraction as one of experimental modeling methods. In order to show the performance of the model, we compare it with Partial Least Square (PLS) method. Both methods have similarities in using the dimension reduction technique. And then we present the simulation results on the prediction of the heat efficiency of the hot stove.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.4
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• pp.1-9
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• 2009

In this paper, a small area 12-bit 300MSPS CMOS Digital-to-Analog Converter(DAC) is proposed for display systems. The architecture of the DAC is based on a current steering 6+6 segmented type, which reduces non-linearity error and other secondary effects. In order to improve the linearity and glitch noise, an analog current cell using monitoring bias circuit is designed. For the purpose of reducing chip area and power dissipation, furthermore, a noble self-clocked switching logic is proposed. To verify the performance, it is fabricated with $0.13{\mu}m$ thick-gate 1-poly 6-metal N-well Samsung CMOS technology. The effective chip area is $0.26mm^2$ ($510{\mu}m{\times}510{\mu}m$) with 100mW power consumption. The measured INL (Integrated Non Linearity) and DNL (Differential Non Linearity) are within ${\pm}3LSB$ and ${\pm}1LSB$, respectively. The measured SFDR is about 70dB, when the input frequency is 15MHz at 300MHz clock frequency.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.29-38
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• 2012

Due to the rapid development of network environment and wireless communication technology, the distribution of digital video has made easily and the importance of the protection for digital video has been increased. This paper proposes the digital video encryption system based on multiple chaos maps for MPEG-2 video encoding process. The proposed method generates secret hash key of having 128-bit characteristics from hash chain using Tent map as a basic block and generates $8{\times}8$ lattice cipher by applying this hash key to Logistic map and Henon map. The method can reduce the encryption overhead by doing selective XOR operations between $8{\times}8$ lattice cipher and some coefficient of low frequency in DCT block and it provides simple and randomness characteristic because it uses the architecture of combining chaos maps. Experimental results show that PSNR of the proposed method is less than or equal to 12 dB with respect to encrypted video, the time change ratio, compression ratio of the proposed method are 2%, 0.4%, respectively so that it provides good performance in visual security and can be applied in real time.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• The Journal of Bigdata
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• v.4 no.2
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• pp.159-173
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• 2019

Last-Mile delivery optimization plays a key role in the urban supply chain operation, which is the most expensive and time-consuming and most complicated part of the whole delivery process. The urban consolidation center (UCC) is regarded as a significant asset for supporting customer demand in the last-mile delivery service. It is the key benefit of UCC to improve the load balance of vehicles and to reduce the total traveling distance by finding the better route with the well-organized multi-leg vehicle journey in the urban area. This paper presents the model using multiple scenario analysis integrated with mathematical optimization techniques using Geographic Information System (GIS). The model aims to find the best solution for the distribution network consisted of DC and UCC, which is applied to the case of Ulaanbaatar Mongolia. The proposed methodology integrates two sub-models, location-allocation model and vehicle routing problem. The multiple scenarios devised by selecting locations of UCC are compared considering the general performance and delivery patterns together. It has been adopted to make better decisions the quantitative metrics such as the economic value of capital cost, operating cost, and balance of using available resources. The result of this research may help the manager or public authorities who should design the distribution network for the last mile delivery service optimization using UCC within the urban area.

• Journal of Korean Society of Forest Science
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• v.107 no.2
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• pp.184-192
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• 2018

In this study was implemented to develop tree stem weight prediction equation of Larix kaempferi in central region by selecting a standard site, taking into account of diameter and position of the local trees. Fifty five sample trees were selected in total. By utilizing actual data of the sample trees, 11 models were compared and analyzed in order to estimate four different kinds of weights which include fresh weight, ovendry outside bark weight, ovendry inside bark weight and merchantable weight. As to estimate its weight, the study has classified its model according to three parameters: DBH, DBH and height, and volume. The optimal model was chosen by comparing the performance of model using the fit index and standard error of estimate and residual distribution. As a result, the formula utilizing DBH (Variable 1) is $W=a+bD+cD^2$ (3) and its fit index was 90~92%. The formula for DBH and height (Variable 2) is $W=aD^bH^C$ (8) and its fit index was 97~98%. In summation, Variable 2 model showed higher fitness than Variable 1 model. Moreover, fit index of formula for total volume and merchantable volume (W=aV) showed high rate of 98~99%, as well as resulting 7.7-17.5 with SEE and 8.0-10.0 with CV(%) which lead to predominately high fitness in conclusion. This study is expected to provide information on weights for single trees and furthermore, to be used as a basic study for weight of stand unit and biomass estimation equations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.137-142
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• 2016

A two-step open system(TOS) was proposed to relay between a healing platform and a repository of personal health documents. TOS was designed by taking into consideration the pubsub service based on large scale connections to monitor a provider's access/request process for health documents in real time. TOS, however, uses WebSocket as a communication protocol in case of pubsub. Given the operational environment of low quality wireless networks for mobile devices that are user terminals in a healing platform, there is a need to add a messaging protocol to support QoS as well as a transmission protocol. As a light messaging protocol optimized for mobile devices, MQTT defines reliable messaging QoS to consider a wireless network situation of low speed/low quality. This study designed an MQTT protocol-based message broker to support QoS in case of large scale connections and pubsub by taking into consideration mobile devices that are user terminals in a healing platform. After designing a model between TOS and MQTT message broker, the study implemented a prototype based on the proposed design and compared it with its counterparts from previous studies based on the performance indicators in a load-test with the MQTT client tool.