Search

Your search keyword '"Kon, A."' showing total 1,502 results
Start Over Author "Kon, A." Publisher ieee
1,502 results on '"Kon, A."'

1. ZEC ECC: A Zero-Byte Eliminating Compression-Based ECC Scheme for DRAM Reliability

Author

Ji Hun Kwon, Hyeong Kon Bae, Young Seo Lee, Young-Ho Gong, and Sung Woo Chung

Subjects
DRAM reliability, data compression, error correction code, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

As DRAM cells continue to shrink, the conventional single error correction and double error detection (SECDED) code is not sufficient to provide DRAM error resilience. To satisfy DRAM reliability demands, various studies have proposed multi-bit error correctable ECC schemes with substantial performance and/or storage overhead compared to the SECDED code. In this paper, we propose ZEC ECC, a zero-byte eliminating compression based ECC scheme, which provides much stronger error correction capability with negligible performance overhead and no storage overhead. ZEC ECC exploits our proposed Zero-byte Eliminating Compression (ZEC) to make room for additional parity bits. Depending on the compression ratio of a memory block ( $\ge 60$ %, $\ge 50$ %, and

Published
2024
Full Text
View/download PDF

2. Minimal Aliasing Single-Error-Correction Codes for DRAM Reliability Improvement

Author

Sung-Il Pae, Vivek Kozhikkottu, Dinesh Somasekar, Wei Wu, Shankar Ganesh Ramasubramanian, Melin Dadual, Hyungmin Cho, and Kon-Woo Kwon

Subjects
In-DRAM error correcting code, minimal aliasing code, single error correction, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

We discuss the problem of finding a minimal aliasing code among a class of systematic single-error-correction codes that are suitable to be implemented within DRAM die, as opposed to external ECC used in memory controller outside of DRAM chip. We prove a sharp lower bound of aliasing probability and propose a simple method to come up with a code that meets the bound. By an experiment, we also demonstrate that a randomly chosen code is likely to have much more aliasings with overwhelmingly high probability.

Published
2021
Full Text
View/download PDF

6. Symmetrical and Crossed Double-Sided Passivation Emitter and Surface Field Solar Cells for Bifacial Applications

Author

Jyi-Tsong Lin, Kon-Yu Ho, Steve W. Haga, and Wen-Hao Chen

Subjects
Bifacial, silicon, PERC solar cells, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

This paper proposes symmetrical and crossed double-sided passivation emitter and surface field solar cells for bifacial applications which are fully compatible with the passivated emitter and rear contact (PERC) fabrication process. Our simulations use Silvaco TCAD Atlas, calibrated by real measurements. At an ideal albedo level where light enters both sides equally, these symmetrical and crossed structures boost energy by 88.78% and 106.74%, respectively. The reason for the crossed structure's better performance is that it has a surrounding electric field. The crossed structure also obtains a 40.18 mA/cm2 short-circuit current (Jsc), a 0.67 V open-circuit voltage (Voc), an 81.07% fill factor and a 21.93% conversion efficiency (η). Compared with PERC+, the crossed structure improves low bifaciality factor (φη) and increases η by 6.44% and energy boost by 31.41% for bifacial. For more-realistic albedo levels, the structure also performs strongly. At the spectral albedo level of snow, the energy boost of the crossed structure is 102.06%, which is close to the performance at ideal albedo. At the spectral albedo level of white sand, the energy boost is 77.13%. At lower albedos, the energy boost remains between 20% and 30%.

Published
2019
Full Text
View/download PDF

7. Modeling Application-Level Soft Error Effects for Single-Event Multi-Bit Upsets

Author

Hyungmin Cho and Kon-Woo Kwon

Subjects
Error resilience, multi-bit upsets, soft errors, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract

Transient errors induced by radiations cause bit-flips in flip-flops (flip-flop soft errors). Modeling the error resilience level of a target system for flip-flop soft errors is a crucial step to achieve a cost-effective error resilience solution. This step often requires a significant amount of time and effort for a large number of fault injection simulations. As technology scales, the required effort grows in a new dimension with the increased probability of multi-bit upsets (MBUs). In this work, we present a new estimation model that predicts the resulting error resilience levels for the flip-flop MBU cases. This estimation model only requires the measured soft error effects of the single-bit upset (SBU) cases. This model uses two strategies to address how multiple bit-flips that happen simultaneously in a system affects the outcome of application execution. We evaluate the accuracy level of the MBU estimation model using actual fault injection results on two different processor cores. The two main strategies in our estimation model improve the accuracy levels by more than 7×.

Published
2019
Full Text
View/download PDF

9. Microwave flow chemistry : Single-mode system for kg-scale organic synthesis

Author

Kohei Sato, Jun Ueda, Takuya Kon, Yushi Nakamura, Junko Fujimoto, Tetsuo Narumi, Kazuhiro Takeda, and Nobuyuki Mase

Subjects
in-line analysis, microwave heating, flow reaction, response surfaces, optimization
Abstract

2022 Asia-Pacific Microwave Conference (APMC)Date of Conference : 29 November 2022 - 02 December 2022Conference Location : Yokohama, Japan

Published
2023

10. Development and validation of a measurement system for laparoscopic surgical procedures in practical surgery training

Author

Ebina, Koki, primary, Abe, Takashige, additional, Hotta, Kiyohiko, additional, Higuchi, Madoka, additional, Furumido, Jun, additional, Iwahara, Naoya, additional, Kon, Masafumi, additional, Komizunai, Shunsuke, additional, Kurashima, Yo, additional, Kikuchi, Hiroshi, additional, Matsumoto, Ryuji, additional, Osawa, Takahiro, additional, Murai, Sachiyo, additional, Tsujita, Teppei, additional, Sase, Kazuya, additional, Chen, Xiaoshuai, additional, Shinohara, Nobuo, additional, and Konno, Atsushi, additional

Published
2023
Full Text
View/download PDF

22. PiMS: A Pre-ML Labelling Tool

Author

Logothetis, Irini, primary, Barnett, Scott, additional, Hoon, Leonard, additional, Thudumu, Srikanth, additional, Mathew, Joseph, additional, Luckhoff, Carl, additional, O'Reilly, Gerard, additional, Collard, David, additional, Vasa, Rajesh, additional, Mouzakis, Kon, additional, and Fitzgerald, Mark, additional

Published
2022
Full Text
View/download PDF

28. PiMS: A Pre-ML Labelling Tool

Author

Irini Logothetis, Scott Barnett, Leonard Hoon, Srikanth Thudumu, Joseph Mathew, Carl Luckhoff, Gerard O'Reilly, David Collard, Rajesh Vasa, Kon Mouzakis, and Mark Fitzgerald

Published
2022

29. Subspace based Anomaly Detection Framework for Point Clouds

Author

Zyl, Johnahan van, Du, Hung, Thudumu, Srikanth, Logothetis, Irini, Barnett, Scott, Vasa, Rajesh, and Mouzakis, Kon

Subjects
paper-presentation
Abstract

In many real-world applications such as the inspection of powerlines, the automated detection of anomalies can minimise damage and reduce costs that result from the presence of unknown anomalies. Technologies such as LiDAR scans obtained from Unmanned Aerial Vehicles (UAV) are becoming prominent due to the data depth they provide. In the context of powerline transmission, investigators must search for anomalous elements such as line defects or obstructions. Such occurrences are not always apparent and require extensive analysis of data, which encompasses vast areas of wilderness, in order to detect them. Automating this process can reduce labour costs and save time. Hence, we propose a methodology to define what constitutes an anomaly within mapped real-world scenes, and a technique to address different types of anomalies. The notion of unknowns and knowns composed of unknown to both human and machine, known to human and unknown to machine, unknown to human and known to machine, and known to both human and machine is considered to develop a novel framework that detects anomalous patterns. For the purpose of evaluation, we introduce synthetic anomalous data points through our data augmentation methods. Our framework achieved 63.78% accuracy in detecting the points known to the machine and unknown to the machine from the Sensat Urban validation scene. Within the scene, 78.22% of the incorrectly classified data were detected as unknown to the machine. Furthermore, our framework achieved 84.34% accuracy in detecting the synthetic data and 35.5% accuracy in detecting those data as anomalies.

Published
2022

46. Physics-Guided Neural Networks for Feedforward Control: An Orthogonal Projection-Based Approach

Author

Kon, Johan, Bruijnen, Dennis, van de Wijdeven, Jeroen, Heertjes, Marcel, Oomen, Tom, Control Systems Technology, Group Oomen, and EAISI High Tech Systems

Subjects
ComputingMethodologies_PATTERNRECOGNITION, Cost function, Quantitative Biology::Neurons and Cognition, Feedforward neural networks, Computer Science::Neural and Evolutionary Computation, Limiting, FOS: Electrical engineering, electronic engineering, information engineering, Training, Systems and Control (eess.SY), System dynamics, Maximum likelihood detection, Electrical Engineering and Systems Science - Systems and Control, Nonlinear filters
Abstract

Unknown nonlinear dynamics can limit the performance of model-based feedforward control. The aim of this paper is to develop a feedforward control framework for systems with unknown, typically nonlinear, dynamics. To address the unknown dynamics, a physics-based feedforward model is complemented by a neural network. The neural network output in the subspace of the model is penalized through orthogonal projection. This results in uniquely identifiable model coefficients, enabling both increased performance and good generalization. The feedforward control framework is validated on a representative system with performance limiting nonlinear friction characteristics., Submitted for presentation at the 2022 American Control Conference (ACC)

Published
2022

50. Intermittent Sampling in Repetitive Control: Exploiting Time-Varying Measurements

Author

Kon, Johan, Strijbosch, Nard, Koekebakker, Sjirk, Oomen, T.A.E., Control Systems Technology, Group Steinbuch, and EAISI High Tech Systems

Subjects
FOS: Electrical engineering, electronic engineering, information engineering, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control
Abstract

The performance increase up to the sensor resolution in repetitive control (RC) invalidates the standard assumption in RC that data is available at equidistant time instances, e.g., in systems with package loss or when exploiting timestamped data from optical encoders. The aim of this paper is to develop an intermittent sampling RC framework for non-equidistant measurements. Sufficient stability conditions are derived that can be verified using non-parametric frequency response function data. This results in a frequency domain design procedure to explicitly address uncertainty. The RC framework is validated on an industrial printbelt setup for which exact non-equidistant measurement data is available., Comment: Accepted for presentation at the 60th Conference on Decision and Control 2021 (CDC2021)

Published
2021

Catalog

Books, media, physical & digital resources
See catalog results