• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.9
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• pp.35-46
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• 2011

Future Internet should support more efficient mobility management, flexible traffic engineering and various emerging new services. So, lots of traffic engineering techniques have been suggested and developed, but it's impossible to apply them on the current running commercial Internet. To overcome this problem, OpenFlow protocol was proposed as a technique to control network equipments using network controller with various networking applications. It is a software defined network, so researchers can verify their own traffic engineering techniques by applying them on the controller. In addition, for high-speed packet processing in the OpenFlow network, programmable NetFPGA card with four 1G-interfaces and commercial Procurve OpenFlow switches can be used. In this paper, we implement an OpenFlow test-bed using hardware-accelerated NetFPGA cards and Procurve switches on the KREONET, and implement CSPF (Constraint-based Shortest Path First) algorithm, which is one of popular QoS routing algorithms, and apply it on the large-scale testbed to verify performance and efficiency of multimedia traffic engineering scheme in Future Internet.

• 전자공학회논문지 IE
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• v.46 no.4
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• pp.57-65
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• 2009

This paper presents the image contrast enhancement technique suitable for local dimming backlight of small-sized mobile display while achieving the reduction of the power consumption. In addition to the large-sized TFT-LCD, small-sized one has adopted LED for backlight. Since, conventionally, LED was mounted on the side edge of a display panel, global dimming method has been widely used. However, recently, new advanced method of local dimming by placing the LED to the backside of the display panel and it raised the necessity of sub-blocked processing after partitioning the target image. When the sub-blocked image has low brightness, the supply current of a backlight LED is reduced, which gives both enhancement of contrast ratio and power consumption reduction. In this paper, we propose simple and improved image enhancement algorithm suitable for the small-sized mobile display. After partitioning the input image by equal sized blocks and analyzing the pixel information in each block, we realize the primary contrast enhancement by independently processing the sub-blocks using the information such as histogram, mean, and standard deviation values of luminance(Y) component. And then resulting information is transferred to each backlight control unit for local dimming to realize the secondary contrast enhancement as well as reduction of power consumption.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.131-143
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• 2011

Previous alerting service based on LBS was caused severe overload problem of server by using the method to confirm the location of each moving object on server. In this paper, by loading an App on smart moving object, we proposed a novel algorithm named ADAS(Active Disaster Alert Service) for accessing to the server site with oneself location information as needed and implemented the disaster alerting service system with visualization for user. In the proposed method, running App access to the server periodically with the present location coordinate gained from GPS module or network module and the ID of moving object. Then, the server compare the present location coordinate of moving object and the coordinates of disasters registered in DIDB and transmit the n NDIs existed in near distance orderly from the coordinate of present moving object to the client. The App compares the coordinate of present location for moving object and the coordinates of NDI is transmitted from server by real time and executes the service with classifying levels of alert into three steps such as danger, carefulness and safety. And new NDIs are gained by accessing DIDB on Server periodically during running App. Therefore, this will be become a novel method for reducing fundamentally the server overload problem in comparison with previous alerting service that the career of moving object is managed on server.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.19-32
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• 2007

This paper present a new face recognition method based on LVQ neural net to construct a real time face recognition system. The previous researches which used PCA, LDA combined neural net usually need much time in training neural net. The supervised LVQ neural net needs much less time in training and can maximize the separability between the classes. In this paper, the proposed method transforms the input face image by PCA and LDA sequentially into low-dimension feature vectors and recognizes the face through LVQ neural net. In order to make the system robust to external light variation, light compensation is performed on the detected face by max-min normalization method as preprocessing. PCA and LDA transformations are applied to the normalized face image to produce low-level feature vectors of the image. In order to determine the initial centers of LVQ and speed up the convergency of the LVQ neural net, the K-Means clustering algorithm is adopted. Subsequently, the class representative vectors can be produced by LVQ2 training using initial center vectors. The face recognition is achieved by using the euclidean distance measure between the center vector of classes and the feature vector of input image. From the experiments, we can prove that the proposed method is more effective in the recognition ratio for the cases of still images from ORL database and sequential images rather than using conventional PCA of a hybrid method with PCA and LDA.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.11-20
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• 2017

Recently, developments in the various fields of cloud computing technology has been utilized. Whereas the demand for cloud computing services is increasing, security threats are also increasing in the cloud computing environments. Especially, in case when the hosts interconnected in the cloud environments are infected and propagated through the attacks by malware. It can have an effect on the resource of other hosts and other security threats such as personal information can be spreaded and data deletion. Therefore, the study of malware analysis to respond these security threats has been proceeded actively. This paper proposes a type of attack clustering method of Zeus botnet using the k-means clustering algorithm for malware analysis that occurs in the cloud environments. By clustering the malicious activity by a type of the Zeus botnet occurred in the cloud environments. it is possible to determine whether it is a malware or not. In the future, it sets a goal of responding to an attack of the new type of Zeus botnet that may occur in the cloud environments.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.197-206
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• 2010

For an emotion retrieval system implementation to support pedestrian navigation, coordinating the pedestrian emotion model with the system user's emotion is considered a key component. This study proposes a new method for capturing the user's model that corresponds to the pedestrian emotion model and examines the validity of the method. In the first phase, a database comprising a set of interior images that represent hypothetical destinations was developed. In the second phase, 10 subjects were recruited and asked to evaluate on navigation and satisfaction toward each interior image in five rounds of navigation experiments. In the last phase, the subjects' feedback data was used for of the pedestrian emotion model, which is called ‘learning' in this study. After evaluations by the subjects, the learning effect was analyzed by the following aspects: recall ratio, precision ratio, retrieval ranking, and satisfaction. Findings of the analysis verify that all four aspects significantly were improved after the learning. This study demonstrates the effectiveness of the learning algorithm for the proposed pedestrian emotion model. Furthermore, this study demonstrates the potential of such pedestrian emotion model to be well applicable in the development of various mobile contents service systems dealing with visual images such as commercial interiors in the future.

• The Journal of Korean Association of Computer Education
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• v.14 no.2
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• pp.83-94
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• 2011

In the biomedical domain, the longest matching method is frequently used for recognizing named entity written in the literature. This method uses a dictionary as a resource for named entity recognition. If there exist appropriated dictionary about target domain, the longest matching method has the advantage of being able to recognize the entities of target domain quickly and exactly. However, the longest matching method is difficult to recognize the enumerated named entities, because these entities are frequently expressed as being omitted some words. In order to resolve this problem, we propose the partial matching method using a dictionary. The proposed method makes several candidate entities on the assumption that the ellipses may be included. After that, the method selects the most valid one among candidate entities through the optimization algorithm. We tested the longest and partial matching method about HLA entities: HLA gene, antigen, and allele entities, which are frequently enumerated among biomedical entities. As preparing for named entity recognition, we built two new resource, extended dictionary and tag-based dictionary about HLA entities. And later, we performed the longest and partial matching method using each dictionary. According to our experiment result, the longest matching method was effective in recognizing HLA antigen entities, in which the ellipses are rare, and the partial matching method was effective in recognizing HLA gene and allele entities, in which the ellipses are frequent. Especially, the partial matching method had a high F-score 95.59% about HLA alleles.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.1 s.343
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• pp.57-70
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• 2006

This paper descWireless Sensor Network consisting of a number of small sensors with transceiver and data processor is an effective means for gathering data in a variety of environments. The data collected by each sensor is transmitted to a processing center that use all reported data to estimate characteristics of the environment or detect an event. This process must be designed to conserve the limited energy resources of the sensor since neighboring sensors generally have the data of similar information. Therefore, clustering scheme which sends aggregated information to the processing center may save energy. Existing multi-hop cluster energy consumption modeling scheme can not estimate exact energy consumption of an individual sensor. In this paper, we propose a new cluster energy consumption model which modified existing problem. We can estimate more accurate total energy consumption according to the number of clusterheads by using Voronoi tessellation. Thus, we can realize an energy efficient cluster formation. Our modeling has an accuracy over $90\%$ when compared with simulation and has considerably superior than existing modeling scheme about $60\%.$ We also confirmed that energy consumption of the proposed modeling scheme is more accurate when the sensor density is increased.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.1
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• pp.24-36
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• 2003

The digital mobile communication will be developed till getting multimedia service in anyone, any where, any time. Theses requiring items are going to be come true via IMT-2000 system. Transmitting signal bandwidth of IMT-2000 system is 3 times as large as IS-95 system. That is mean peak to average of signal is higher than IS-95A system. So we have to design it carefully not to effect in adjacent channel. HPA(High Power Amplifier) located in the end point of system is operated in 1-㏈ compression point(Pl㏈), then it generates 3rd and 5th inter modulation signals. Theses signals affect at adjacent channel and RF signal is distorted by compressed signal which is operated near by Pl㏈ point. Then the most important design factor is how we make HPA having high linearity. Feedback, Pre-distorter and Feed-forward methods are presented to solve theses problems. Feed-forward of these methods is having excellent improving capacity, but composed with complex structure. Generally, Linearity and Efficiency in power amplifier operate in the contrary, then it is difficult for us to find optimal operating point. In this paper we applied algorithm which searches optimal point of linear characteristics, which is key in Power Amplifier, using minimum current point of error amplifier in 1st loop. And we made 2nd loop compose with new structure. We confirmed fabricated LPA is operated by having high linearity and minimum current condition with ACPR of -26 ㏈m max. @ 30㎑ BW in 3.515㎒ and ACLR of 48 ㏈c max@${\pm}$㎒ from 1W to 40W.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.3
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• pp.52-58
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• 2009

If a moving target has a linear characteristics, the Kalman filter can estimate relatively accurate the location of a target, but this performance depends on how the dynamic status characteristics of the target is accurately modeled. In many practical problems of tracking a maneuvering target, a simple kinematic model can fairly accurately describe the target dynamics for a wide class of maneuvers. However, since the target can exhibit a wide range of dynamic characteristics, no fixed SKF(Simple Kalman filter) can be matched to estimate, to the required accuracy, the states of the target for every specific maneuver. In this paper, a new AKF(Active Kalman filter) is proposed to solve this problem The process noise covariance level of the Kalman filter is adjusted at each time step according to the study result which uses the neural network algorithm. It is demonstrated by means of a computer simulation that the tracking capability of the proposed AKF(Active Kalman filter) is better than that of the SKF(Simple Kalman Filter).