Seung Woo Seo

Most research efforts to date on optical networks have concentrated on wavelength-division multiplexing (WDM) techniques where the information from different channels is routed via separate optical wavelengths. The data corresponding to a particular channel is selected at the destination node by a frequency filter. Optical time-division multiplexing (OTDM) has been considered as an alternative to WDM for future networks operating in excess of 10 Gb/s. Systems based on TDM techniques rely upon a

Vacant parking‐slot recognition is one of the core elements for achieving a fully automated parking assistant system. The recognition of a vacant parking‐slot is typically executed in two stages: parking‐slot recognition and slot‐occupancy classification. In most previous works, considering the recognised slot results as a grid cell, the existence of objects is evaluated through the slot examination in slot‐occupancy classification. Despite moderate performance, however, these methods cannot dis

A new multipath multistage interconnection network called the composite banyan network is proposed. The network incorporates both the banyan and the reverse banyan networks and is constructed by superimposing the two. The basic building blocks in the composite banyan network are 3/spl times/3 switching elements with log/sub 2/N stages. A major advantage of the composite banyan network over existing networks with 3/spl times/3 SEs is an efficient and fast control algorithm that sets up a path bet

We propose an all-optical packet-switching scheme in multihop shuffle networks in which deflection routing is used as its contention-resolution principle. In our scheme only partial address information in the packet header is read before a routing decision is made. Because the new scheme does not involve a time-consuming look-up table, extremely low latency operation is possible at each node. Moreover, because the number of demultiplexers at each node can be kept constant even though the network

In this paper, we analyze ways of realizing permutations in a class of 2log/sub 2/N- or (2log/sub 2/N-1)-stage rearrangeable networks. The analysis is based on the newly developed inside-out routing algorithm and we derive the upper and lower bounds on the number of possible realizations of a permutation. It is shown that the algorithm can provide us with comparable degrees of freedom in realizing a given permutation as the well-known looping algorithm, while it can be more generally applied to

ABSTRACT Discovering therapeutic antibody starts by screening antibody library of phage-displayed, transgenic mouse or human B cells. The coverage of those kinds of libraries in the entire antibody sequence space is small; thus, the result highly depends on the quality of the library. Exploring sequence space by mutating a template antibody is also impossible to even with the state-of-the-art screening methods because of the cost. Deep learning helped with its pattern recognition nature to predi

Time synchronization system using dual frequency bands is designed and the error sources are analyzed for alternative synchronized-pseudolite navigation system (S-PNS) which aims at military application. To resolve near/far problem, dual frequency band operation is proposed instead of pulsing transmission which degrades level of reception. In dual frequency operation H/W delay should be considered to eliminate errors caused by inter-frequency bias (IFB) difference between the receivers of the ps

Abstract Self‐driving baggage tractors driving on airport ramps/aprons present new trends that promote better airport operation procedures and proliferate the aviation market. Airport ramps have unique mobility requirements when it comes to layout, population, demand, and patterns. Estimating aircraft movement is highly crucial and must be required because of safety reasons and airport operations rules. The movement of aircraft at the airport ramp is not dynamic but relatively static and slow. H

A generalization of the well-known shuffle network is proposed for multihop lightwave communication. In the classical definition of a shuffle network, i.e., N=kp/sup k/ where N is the number of nodes and k is the number of stages with base p, the realizable values of N are very discrete and many of the intermediate values of N are not realizable. In this paper, we propose a new definition of a shuffle network as N=nk where n is the number of nodes per stage with base p. Based on this new definit

Abstract Accurate real‐time localisation is crucial for various autonomous driving applications. Numerous methods for localization, combining various kinds of input such as data from environmental sensors, inertial measurement units, and the Global Positioning System, have been proposed. Given the present state of affairs with regards to map compactness and sensor affordability, lane map‐matching‐based methods with cameras used as environmental sensors have been widely proposed. In previous meth

A number of low-rise residential areas in Seoul came to be filled with single–family houses in the 1970s. But as the housing pattern changed to multi-family housing and demand of cars explosively increased, vehicle parking in the area became problematic. Although the local government tightened regulations on parking standards and built a public parking zone to solve this problem, the residents' complaints worsened as parking many vehicles along a narrow alley caused community conflicts and pedes

Multihop networks with wavelength-division multiplexing (WDM) are one possible way to conduct high data-rate communication. We provide an in-depth study of the generalization of the well-known shuffle network for ultrafast multihop lightwave communication. In the classical definition of a shuffle network, i.e., N=kp/sup k/ where N is the number of nodes and k is the number of stages with nodes of degree p, the realizable values of N are very sparse and many of the intermediate values of N are no

) score of 0.9849 and a low mean absolute error (MAE) of 0.0381. Furthermore, the efficacy of the active learning process was demonstrated through its rapid identification of proteins with high PA propensity. Consequently, the active learning approach achieved an MAE of 0.0291 in expected improvement, surpassing other methods. It identified 99% of the target proteins by exploring merely 29% of the entire search space. This improved GCN model demonstrates promise in selecting proteins susceptible