http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
TWiCe: Time Window Counter Based Row Refresh to Prevent Row-Hammering
Lee, Eojin,Lee, Sukhan,Suh, G. Edward,Ahn, Jung Ho IEEE 2018 IEEE computer architecture letters Vol.17 No.1
<P>Computer systems using DRAM are exposed to row-hammering attacks, which can flip data in a DRAM row without directly accessing a row but by frequently activating its adjacent ones. There have been a number of proposals to prevent row-hammering, but they either incur large area/performance overhead or provide probabilistic protection. In this paper, we propose a new row-hammering mitigation mechanism named <B>T</B>ime <B>Wi</B>ndow <B>C</B> ount<B>e</B>r based row refresh (TWiCe) which prevents row-hammering by using a small number of counters without performance overhead. We first make a key observation that the number of rows that can cause flipping their adjacent ones (aggressor candidates) is limited by the maximum values of row activation frequency and DRAM cell retention time. TWiCe exploits this limit to reduce the required number of counter entries by counting only actually activated DRAM rows and periodically invalidating the entries that are not activated frequently enough to be an aggressor. We calculate the maximum number of required counter entries per DRAM bank, with which row-hammering prevention is guaranteed. We further improve energy efficiency by adopting a pseudo-associative cache design to TWiCe. Our analysis shows that TWiCe incurs no performance overhead on normal DRAM operations and less than 0.7 percent area and energy overheads over contemporary DRAM devices.</P>
Surface Patch Primitive Based Object Modeling from CAD Data
Lee, Sukhan,Yoo, Kyeong Dae,Kim, Jae Woong,Lee, Moon Ju Trans Tech Publications, Ltd. 2012 Applied Mechanics and Materials Vol.162 No.-
<P>For manufacturing automation, for instance, the robotic automation of automobile sub-assembly, CAD data serves as DB offering the geometric information of parts essential for robotic manipulation. However, a direct application of CAD for the robotic manipulation of parts may be of an issue, due to the fact that the particular format of the CAD data available, e.g., STL, does not directly provide certain geometric entities such as surface patch primitives and/or features that are required for robotic manipulation. In this paper, we present a novel method for extracting geometric primitives and/or features, such surface patch primitives as planar, cylindrical, conic, and spherical patches, from the STL format of CAD data, such that an industrial part/object can be represented as a logical sum of these surface patch primitives extracted. This surface patch primitive based modeling makes the automated reasoning involved in the recognition and pose estimation, as well as the grasp planning, of parts/objects easy to be done. The proposed method is applied to various CAD data samples for experimentation: the results demonstrate the reliability as well as the computational efficiency of the proposed method in the extraction of surface patch primitives.</P>
이석한(Sukhan Lee),고한서(Han Seo Ko),변도영(Doyoung Byun),백승현(Seunghyun Baik),한상준(Sangjoon Han),김용재(Yong-Jae Kim),양지혜(Ji Hye Yang) 대한기계학회 2005 대한기계학회 춘추학술대회 Vol.2005 No.5
Carbon nanotubes have attracted great attention as future mechanical and electronic materials. However, manipulating techniques are not well developed yet. Thus, electrostatic drop-on-demand devices have been proposed to eject micro-droplets of micelle-suspended single walled carbon nanotubes. A simple electrostatic force analysis and photographic studies of droplet ejection process are presented. The analysis shows that semiconducting species have higher electrostatic force density. However, enrichment of specific electronic types is not clear at large size droplets produced in this study. A micro-scale jetting device is being produced to prove the suggested behavior.
Embedded Visual SLAM: Applications for Low-Cost Consumer Robots
Seongsoo Lee,Sukhan Lee IEEE 2013 IEEE robotics & automation magazine Vol.20 No.4
<P>A camera poses a highly attractive choice as a sensor in implementing simultaneous localization and mapping (SLAM) for low-cost consumer robots such as home cleaning robots. This is due to its low cost, light weight, and low power consumption. However, most of the visual SLAMs available to date are not designed and, consequently, not suitable for use in a low-cost embedded SLAM for consumer robots. This article presents a computationally light yet performance-wise robust SLAM algorithm and its implementation as an embedded system for low-cost consumer robots using an upward-looking camera. Especially for a large-scale mapping of indoor environments, methods of pose graph optimization as well as submapping are employed. An occupancy grid map is used to integrate an efficient Kalman filter-based localization into a SLAM framework. Furthermore, an algorithmic visual compass is introduced as a means of reducing the computational complexity involved in pose graph optimization, taking advantage of the distinct geometric features of the scenes captured by an upward-looking camera. The proposed visual SLAM is implemented in a real home cleaning robot as an embedded system using an ARM11 processor. Extensive test results demonstrate the power of the proposed embedded visual SLAM in terms of not only its computational efficiency but also its performance robustness in realworld applications.</P>
Recursive Unscented Kalman Filtering based SLAM using a Large Number of Noisy Observations
Seongsoo Lee,Sukhan Lee,Dongsung Kim 대한전기학회 2006 International Journal of Control, Automation, and Vol.4 No.6
Simultaneous Localization and Map Building (SLAM) is one of the fundamental problems in robot navigation. The Extended Kalman Filter (EKF), which is widely adopted in SLAM approaches, requires extensive computation. The conventional particle filter also needs intense computation to cover a high dimensional state space with particles. This paper proposes an efficient SLAM method based on the recursive unscented Kalman filtering in an environment including a large number of landmarks. The posterior probability distributions of the robot pose and the landmark locations are represented by their marginal Gaussian probability distributions. In particular, the posterior probability distribution of the robot pose is calculated recursively. Each landmark location is updated with the recursively updated robot pose. The proposed method reduces filtering dimensions and computational complexity significantly, and has produced very encouraging results for navigation experiments with noisy multiple simultaneous observations.