• IMMUNE NETWORK
• /
• v.12 no.4
• /
• pp.155-164
• /
• 2012

It is well established that blocking the interaction of EGFR with growth factors leads to the arrest of tumor growth, resulting in tumor cell death. ER414 is a human monoclonal antibody (mAb) derived by guided selection of the mouse mAb A13. The ER414 exhibited a ~17-fold lower affinity and, as a result, lower efficacy of inhibition of the EGF-mediated tyrosine phosphorylation of EGFR when compared with mAb A13 and cetuximab. We performed a stepwise in vitro affinity maturation to improve the affinity of ER414. We obtained a 3D model of ER414 to identify the amino acids in the CDRs that needed to be mutated. Clones were selected from the phage library with randomized amino acids in the CDRs and substitution of amino acids in the HCDR3 and LCDR1 of ER414 led to improved affinity. A clone, H3-14, with a ~20-fold increased affinity, was selected from the HCDR3 randomized library. Then three clones, ER2, ER78 and ER79, were selected from the LCDR1 randomized library based on the H3-14 but did not show further increased affinities compared to that of H3-14. Of the three, ER2 was chosen for further characterization due to its better expression than others. We successfully performed affinity maturation of ER414 and obtained antibodies with a similar affinity as cetuximab. And antibody from an affinity maturation inhibits the EGF-mediated tyrosine phosphorylation of EGFR in a manner similar to cetuximab.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.2C
• /
• pp.208-218
• /
• 2006

In this paper, we introduce the creation methods of attack detection model using data mining technologies that can classify the latest attack types, and can detect the modification of existing attacks as well as the novel attacks. Also, we evaluate comparatively these attack detection models in the view of detection accuracy and detection time. As the important factors for creating detection models, there are data, attribute, and detection algorithm. Thus, we used NetFlow data gathered at the real network, and KDD Cup 1999 data for the experiment in large quantities. And for attribute selection, we used a heuristic method and a theoretical method using decision tree algorithm. We evaluate comparatively detection models using a single supervised/unsupervised data mining approach and a combined supervised data mining approach. As a result, although a combined supervised data mining approach required more modeling time, it had better detection rate. All models using data mining techniques could detect the attacks within 1 second, thus these approaches could prove the real-time detection. Also, our experimental results for anomaly detection showed that our approaches provided the detection possibility for novel attack, and especially SOM model provided the additional information about existing attack that is similar to novel attack.

• Journal of KIISE:Information Networking
• /
• v.31 no.2
• /
• pp.123-130
• /
• 2004

Routing and wavelength assignment(RWA) problem is an important issue in optical transport networks based on wavelength division multiplexing(WDM) technique. It is typically solved using a combination of linear programming and graph coloring, or path selection based graph algorithms. Such methods are either complex or make extensive use of heuristics. In this paper we propose a novel and efficient approach which basically obtains the maximum edge disjoint paths (EDPs) for each source-destination demand pair. And those EDPs obtained are stored in Lookup Table and used for the update of weight matrix. Routes are determined in order by the weight matrix for the demand set. The comprehensive computer simulation shows that the Proposed algorithm uses similar or fewer wavelengths with significantly less execution time than bounded greedy approach (BGA) for EDP which is currently known to be effective in practice.

• Journal of KIISE:Computing Practices and Letters
• /
• v.11 no.1
• /
• pp.50-61
• /
• 2005

To provide adaptively video streaming services on network environment, video transcoding is introduced. The one of transcoding methods is the frame-rate conversion. it needs a re-estimation about a motion vector of the frame to refer a skipping frame. This re-estimation makes higher the computational complexity in video transcoding. To reduce the computational complexity of a motion vector refinement, this paper proposes a region & activity based motion vector composition scheme that refine the moving vector of a skipping frame. This scheme composes each motion vector from the weight based on the activity information of a macroblock and the site of the overlapped area. The experiment result shows that RABVC has a higher PSNR than the value of existing weight-based motion vector selection schemes though the computational complexity of our scheme is similar to that of other schemes.

• Journal of Internet Computing and Services
• /
• v.12 no.5
• /
• pp.11-19
• /
• 2011

In this paper, Service Boundary Line approximation method is proposed to improve the accuracy of aggregated link state information for source routing in transport networks that conduct hierarchical QoS routing. The proposed method is especially useful for aggregating links that have both delay and bandwidth as their QoS parameters. This method selects the main path weight in the network and transports the data to the external networks together with the aggregation information, reducing information distortion caused from the loss of some path weight during aggregation process. In this paper, the main path weight is defined as outlier. Service Boundary Line has 2k+5parameters. k is the number of outliers. The number of storage spaces of Service Boundary Line changes according to the number of outliers. Simulation results show that our approximation method requires a storage space that 1.5-2 times larger than those in other known techniques depending on outlier selection method, but its information accuracy of proposed method in the ratio between storage space and information accuracy is higher.

• Journal of the Korean Society for Precision Engineering
• /
• v.28 no.4
• /
• pp.482-489
• /
• 2011

In practical design process, designer needs to find an optimal solution by using full factorial discrete combination, rather than by using optimization algorithm considering continuous design variables. So, ANOVA(Analysis of Variance) based on an orthogonal array, i.e. Taguchi method, has been widely used in most parts of industry area. However, the Taguchi method is limited for the shape optimization by using CAE, because the multi-level and multi-objective optimization can't be carried out simultaneously. In this study, a combined method was proposed taking into account of multi-level computational orthogonal array and TOPSIS(Technique for Order preference by Similarity to Ideal Solution), which is known as a classical method of multiple attribute decision making and enables to solve various decision making or selection problems in an aspect of multi-objective optimization. The proposed method was applied to a case study of the multi-level shape optimization of lower arm used to automobile parts, and the design space was explored via an efficient application of the related CAE tools. The multi-level shape optimization was performed sequentially by applying both of the neural network model generated from seven-level four-factor computational orthogonal array and the TOPSIS. The weight and maximum stress of the lower arm, as the objective functions for the multi-level shape optimization, showed an improvement of 0.07% and 17.89%, respectively. In addition, the number of CAE carried out for the shape optimization was only 55 times in comparison to full factorial method necessary to 2,401 times.

• Journal of Korea Water Resources Association
• /
• v.37 no.6
• /
• pp.449-460
• /
• 2004

The purpose of this study is to test the applicability of neuro-fuzzy system for monthly dam inflow forecasts by using weather forecasting information. The neuro-fuzzy algorithm adopted in this study is the ANFIS(Adaptive neuro-fuzzy Inference System) in which neural network theory is combined with fuzzy theory. The ANFIS model can experience the difficulties in selection of a control rule by a space partition because the number of control value increases rapidly as the number of fuzzy variable increases. In an effort to overcome this drawback, this study used the subtractive clustering which is one of fuzzy clustering methods. Also, this study proposed a method for converting qualitative weather forecasting information to quantitative one. ANFIS for monthly dam inflow forecasts was tested in cases of with or without weather forecasting information. It can be seen that the model performances obtained from the use of past observed data and future weather forecasting information are much better than those from past observed data only.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.5
• /
• pp.859-876
• /
• 2010

In this paper, we propose a hierarchical application traffic classification system as an alternative means to overcome the limitations of the port number and payload based methodologies, which are traditionally considered traffic classification methods. The proposed system is a new classification model that hierarchically combines a binary classifier SVM and Support Vector Data Descriptions (SVDDs). The proposed system selects an optimal attribute subset from the bi-directional traffic flows generated by our traffic analysis system (KU-MON) that enables real-time collection and analysis of campus traffic. The system is composed of three layers: The first layer is a binary classifier SVM that performs rapid classification between P2P and non-P2P traffic. The second layer classifies P2P traffic into file-sharing, messenger and TV, based on three SVDDs. The third layer performs specialized classification of all individual application traffic types. Since the proposed system enables both coarse- and fine-grained classification, it can guarantee efficient resource management, such as a stable network environment, seamless bandwidth guarantee and appropriate QoS. Moreover, even when a new application emerges, it can be easily adapted for incremental updating and scaling. Only additional training for the new part of the application traffic is needed instead of retraining the entire system. The performance of the proposed system is validated via experiments which confirm that its recall and precision measures are satisfactory.

• Journal of KIISE:Information Networking
• /
• v.33 no.4
• /
• pp.310-323
• /
• 2006

In this paper, we describe a secure cluster-routing protocol based on a multi-layer scheme in ad hoc networks. We propose efficient protocols, Authentication based on Multi-layer Clustering for Ad hoc Networks (AMCAN), for detailed security threats against ad hoc routing protocols using the selection of the cluster head (CH) and control cluster head (CCH) using a modification of cluster-based routing ARCH and DMAC. This protocol provides scalability of Shadow Key using threshold authentication scheme in ad hoc networks. The proposed protocol comprises an end-to-end authentication protocol that relies on mutual trust between nodes in other clusters. This scheme takes advantage of Shadow Key using threshold authentication key configuration in large ad hoc networks. In experiments, we show security threats against multilayer routing scheme, thereby successfully including, establishment of secure channels, the detection of reply attacks, mutual end-to-end authentication, prevention of node identity fabrication, and the secure distribution of provisional session keys using threshold key configuration.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.4A
• /
• pp.394-400
• /
• 2010

Mobile Multi-hop Relaying (MMR) system can provide increased system capacity of wireless access network by coverage extension and enhanced transmission rate within the Base Station (BS) coverage area. The previous researches for the MMR system with a non-transparent mode Relay Station (RS) do not consider channel selection procedure of Mobile Station (MS), co-channel interference and Multi-hop Relay Base Station (MR-BS) coverage and RS coverage ratio in MMR system. In this paper, we investigate the performance of MMR uplink system in multicell environments with various topologies. The performance is presented in terms of call blocking probability, channel utilization, outage probability and system throughput by varying offered load. It is found that, for certain system parameters, the MMR uplink system achieve the maximum system throughput when MR-BS coverage to RS coverage ratio is 7.