• Applied Microscopy
• /
• v.46 no.4
• /
• pp.184-187
• /
• 2016

Neuronal connectivity determines brain function. Therefore, understanding the full map of brain connectivity with functional annotations is one of the most desirable but challenging tasks in science. Current methods to achieve this goal are limited by the resolution of imaging tools and the field of view. Macroscale imaging tools (e.g., magnetic resonance imaging, diffusion tensor images, and positron emission tomography) are suitable for large-volume analysis, and the resolution of these methodologies is being improved by developing hardware and software systems. Microscale tools (e.g., serial electron microscopy and array tomography), on the other hand, are evolving to efficiently stack small volumes to expand the dimension of analysis. The advent of mesoscale tools (e.g., tissue clearing and single plane ilumination microscopy super-resolution imaging) has greatly contributed to filling in the gaps between macroscale and microscale data. To achieve anatomical maps with gene expression and neural connection tags as multimodal information hubs, much work on information analysis and processing is yet required. Once images are obtained, digitized, and cumulated, these large amounts of information should be analyzed with information processing tools. With this in mind, post-imaging processing with the aid of many advanced information processing tools (e.g., artificial intelligence-based image processing) is set to explode in the near future, and with that, anatomic problems will be transformed into informatics problems.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.6 no.2
• /
• pp.13-21
• /
• 1996

The necessity and usefulness of higher-order neural networks have been well-known since early days of neurocomputing. However the explosive number of terms has hampered the design and training of such networks. In this paper we present an evolutionary learning method for efficiently constructing problem-specific higher-order neural models. The crux of the method is the neural tree representation employing both sigma and pi units, in combination with the use of an MDL-based fitness function for learning minimal models. We provide experimental results in classification and prediction problems which demonstrate the effectiveness of the method. I. Introduction topology employs one hidden layer with full connectivity between neighboring layers. This structure has One of the most popular neural network models been very successful for many applications. However, used for supervised learning applications has been the they have some weaknesses. For instance, the fully mutilayer feedforward network. A commonly adopted connected structure is not necessarily a good topology unless the task contains a good predictor for the full *d*dWs %BH%W* input space.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2016.02a
• /
• pp.329-329
• /
• 2016

Large-area graphene films produced by means of chemical vapor deposition (CVD) are polycrystalline and thus contain numerous grain boundaries that can greatly degrade their performance and produce inhomogeneous properties. A better grain boundary engineering in CVD graphene is essential to realize the full potential of graphene in large-scale applications. Here, we report a defect-selective atomic layer deposition (ALD) for stitching grain boundaries of CVD graphene with ZnO so as to increase the connectivity between grains. In the present ALD process, ZnO with hexagonal wurtzite structure was selectively grown mainly on the defect-rich grain boundaries to produce ZnO-stitched CVD graphene with well-connected grains. For the CVD graphene film after ZnO stitching, the inter-grain mobility is notably improved with only a little change in free carrier density. We also demonstrate how ZnO-stitched CVD graphene can be successfully integrated into wafer-scale arrays of top-gated field effect transistors on 4-inch Si and polymer substrates, revealing remarkable device-to-device uniformity.

• Communications of the Korean Mathematical Society
• /
• v.11 no.4
• /
• pp.1159-1174
• /
• 1996

The spectrum of the Laplacian matrix of a graph gives an information of the structure of the graph. For example, the product of non-zero eigenvalues of the characteristic polynomial of the Laplacian matrix of a graph with n vertices is n times of the number of spanning trees of that graph. The characteristic polynomial of the Laplacian matrix of a graph tells us the number of spanning trees and the connectivity of given graph. in this paper, we compute the characteristic polynomial of the Laplacian matrix of a graph bundle when its voltage lie in an abelian subgroup of the full automorphism group of the fibre; in particular, the automorphism group of the fibre is abelian. Also we study a relation between the characteristic polynomial of the Laplacian matrix of a graph G and that of the Laplacian matrix of a graph bundle over G. Some applications are also discussed.

• Proceeding of KASS Symposium
• /
• 2006.05a
• /
• pp.175-181
• /
• 2006

This paper presents an efficient reanalysis algorithm, named PRAS (Partial Reanalysis algorithm using Adaptable Substructuring), for the partially changed structures. The algorithm recalculates directly any displacement or member force under consideration in real time without a full reanalysis in spite of local changes in member stiffness or connectivity. The key procedures consists of 1) partitioning the whole structure into the changed part and the unchanged part, 2) condensing the internal degrees of freedom and forming the unchanged part substructure, 3) assembling and solving the new stiffness matrix from the unchanged part substructure and the changed members.

• 한국정보통신설비학회:학술대회논문집
• /
• 2008.08a
• /
• pp.350-354
• /
• 2008

IP-based mobile communication system is one of the key research items in the mobile networks for a long time. But, due to some technical issues and no need of markets, it is still not full-fledged. Recently, CDMA and WCDMA service providers want to introduce IP-based network connectivity. Even though their efforts, the main network intra-structure depends on ATM or HDLC technology. This article describes a good example of commercialization of IP-based mobile communication systems. Our research is not experimental system but a in-service system - replacing the existing equipments with new IP-based systems. In this paper, we introduce IP related technologies used in our research such as IP-based ATCA(Advanced Telecommunications Computing Architecture) platform, HA(High Availability) redundancy, IP multicast, network redundancy techniques, multi-link bundling and IP header compression. These are already well-known to internet domain. We mix them with mobile communication systems concretely.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.6
• /
• pp.55-62
• /
• 2010

Monitoring systems are able to report certain events at region of interest(ROI) and to take an appropriate action. From industrial product line full of robots to fire detection, intrusion detection, smart grid application, environmental pollution alarm system, monitoring system has widely used in diverse industry sector. Recently, due to advance of wireless communication technology and availability of low cost sensors, intelligent and/or smart monitoring systems such as sensor networks has been developed. Several deployment methods are introduced to meet various monitoring needs and deployment performance criteria are also summarized to be used to identify weak point and be useful at designing monitoring systems. Both efficiency during deployment and usefulness after the deployment should be assessed. Efficiency factors during deployment are elapsed time, energy required, deployment cost, safety, sensor node failure rate, scalability. Usefulness factors after deployment are ROI coverage, connectivity, uniformity, target density similarity, energy consumption rate per unit time and so on.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.5
• /
• pp.1187-1193
• /
• 2014

This paper presents an effective motion estimation to improve the performance of the motion compensated temporal filtering (MCTF) which is a core part of the wavelet-based scalable video coding. The proposed scheme makes the motion vector field uniform by the modified median operation and the search strategies using adjacent motion vectors, in order to enhance the pixel connectivity which is significantly relevant to the performance of the MCTF. Moreover, the motion estimation with variable block sizes that reflects the features of frames is introduced for further correlation improvement of the motion vector field. Experimental results illustrate that the proposed method reduces the decomposed energy on the temporal high frequency subband frame up to 30.33% in terms of variance compared to the case of the full search with fixed block sizes.

• Journal of Communications and Networks
• /
• v.16 no.3
• /
• pp.335-343
• /
• 2014

This paper considers the crucial problem of deploying wireless relays for achieving a connected wireless sensor network in indoor environments, an important aspect related to the management of the sensor network. Several algorithms have been proposed for ensuring full sensing coverage and network connectivity. These algorithms are not applicable to indoor environments because of the complexity of indoor environments, in which a radio signal can be dramatically degraded by obstacles such as walls. We first prove theoretically that the indoor relay placement problem is NP-hard. We then predict the radio coverage of a given relay deployment in indoor environments. We consider two practical scenarios; wire-connected relays and radio-connected relays. For the network with wire-connected relays, we propose an efficient greedy algorithm to compute the deployment locations of relays for achieving the required coverage percentage. This algorithm is proved to provide a $H_n$ factor approximation to the theoretical optimum, where $H_n=1+{\frac{1}{2}}+{\cdots}+{\frac{1}{n}}={\ln}(n)+1$, and n is the number of all grid points. In the network with radio-connected relays, relays have to be connected in an ad hoc mode. We then propose an algorithm based on the previous algorithm for ensuring the connectivity of relays. Experimental results demonstrate that the proposed algorithms achieve better performance than baseline algorithms.

• Convergence Security Journal
• /
• v.9 no.4
• /
• pp.7-12
• /
• 2009

It is very difficult to completely block the DDoS attack, which paralyzes services by depleting resources or occupying the network bandwidth by transmitting a vast amount of traffic to the specific website or server from normal users' PCs that have been already infected by an outside attacker. In order to defense or endure the DDoS attack, we usually use various solutions such as IDS (Intrusion Detection System), IPS (Intrusion Prevention System), ITS (Intrusion Tolerance System), FW (Firewall), and the dedicated security equipment against DDoS attack. However, diverse types of security appliances cause the cost problem, besides, the full function of the equipments are not performed well owing to the unproper setting without considering connectivity among systems. In this paper, we present the effective connectivity of security equipments and countermeasure methodology against DDoS attack. In practice, it is approved by experimentation that this designed methdology is better than existing network structure in the efficiency of block and endurance. Therefore, we would like to propose the effective security control measures responding and enduring against discriminated DDoS attacks through this research.