Muhammad Tayyab Chaudhry, Teck Chaw Ling, Atif Manzoor, Syed Asad Hussain, JongWon Kim
IF 28
ACM Computing Surveys
Data centers can go green by saving electricity in two major areas: computing and cooling. Servers in data centers require a constant supply of cold air from on-site cooling mechanisms for reliability. An increased computational load makes servers dissipate more power as heat and eventually amplifies the cooling load. In thermal-aware scheduling, computations are scheduled with the objective of reducing the data-center-wide thermal gradient, hotspots, and cooling magnitude. Complemented by heat modeling and thermal-aware monitoring and profiling, this scheduling is energy efficient and economical. A survey is presented henceforth of thermal-ware scheduling and associated techniques for green data centers.
A visual-sharing switching device supporting programmable in-network content adaptation
Namgon Kim, Jae-Yong Yoo, Namgon Kim, JongWon Kim
IF 10.9
IEEE Transactions on Consumer Electronics
To share visual contents among various network-enabled consumer devices in home, the visual content needs to be adapted according to the consumer device that plays the contents. Due to heterogeneity of consumer devices and content formats, content adaptation becomes challenging and cannot be achieved with several fixed content adaptation functionalities. In this paper, we present a visual-sharing switching device supporting programmable in-network content adaptation for in-home distribution of visual content. It provides computing and networking resources and its switching software supports building of custom data plane for visual content. We prototype the visual-sharing switching device and verify that it can be flexibly programmed to support various visual-sharing scenarios.
Centralized mediation of multiparty video sharing for smart work
Sang‐Uk Han, JongWon Kim
IF 10.9
IEEE Transactions on Consumer Electronics
Natural sharing of informative media contents is a key service in collaborative and smart work that flexibly conducts remote operations and communicates with remote co-workers in home offices and smart work centers. For collaborative and smart work, we need to carefully disseminate media services tailored for each participating site in order to naturally exchange shared contents between participants. In this paper, we present a centralized mediation approach to fairly improve the qualities of shared videos in multi-producer multi-consumer environment. The proposed approach carries out progressive improvement of end-user quality and efficient placement of transcoders by balancing the overall usage of computation and networking resources. Computer-simulated experiment results demonstrate that the proposed approach can find a feasible solution and improve the running time performance.
Robust MMSE video decoding: theory and practical implementations
Chang‐Su Kim, JongWon Kim, Ioannis Katsavounidis, C.‐C. Jay Kuo
IF 11.1
IEEE Transactions on Circuits and Systems for Video Technology
A novel video decoding algorithm based on the minimum mean square error (MMSE) criterion is investigated in this research. To alleviate the effect of transmission errors, we first develop an error propagation model to estimate and track the mean square error (MSE) of each pixel in the decoder. Then, the proposed video decoding algorithm adjusts the reconstruction of each pixel adaptively according to fluctuating channel conditions. More specifically, the decoder reconstructs a pixel in the kth frame F/sub k/ by using a weighted sum of two pixels in frames F/sub k-1/ and F/sub k-2/, respectively, where their weights are adaptively selected to minimize the MSE of the reconstructed pixel by using the error propagation model. Extensive simulation results performed on standard H.263 bit streams demonstrate that the MMSE-based concealment algorithm yields a better performance than the conventional method, even if the encoder transmits a single motion vector per block. Moreover, the proposed MMSE decoding algorithm significantly enhances the error resilient capability of the double-vector motion compensation (DMC) algorithm, where two motion vectors are sent per block.
Muhammad Tayyab Chaudhry, Teck Chaw Ling, Atif Manzoor, Syed Asad Hussain, JongWon Kim
IF 28
ACM Computing Surveys
Data centers can go green by saving electricity in two major areas: computing and cooling. Servers in data centers require a constant supply of cold air from on-site cooling mechanisms for reliability. An increased computational load makes servers dissipate more power as heat and eventually amplifies the cooling load. In thermal-aware scheduling, computations are scheduled with the objective of reducing the data-center-wide thermal gradient, hotspots, and cooling magnitude. Complemented by heat modeling and thermal-aware monitoring and profiling, this scheduling is energy efficient and economical. A survey is presented henceforth of thermal-ware scheduling and associated techniques for green data centers.
A visual-sharing switching device supporting programmable in-network content adaptation
Namgon Kim, Jae-Yong Yoo, Namgon Kim, JongWon Kim
IF 10.9
IEEE Transactions on Consumer Electronics
To share visual contents among various network-enabled consumer devices in home, the visual content needs to be adapted according to the consumer device that plays the contents. Due to heterogeneity of consumer devices and content formats, content adaptation becomes challenging and cannot be achieved with several fixed content adaptation functionalities. In this paper, we present a visual-sharing switching device supporting programmable in-network content adaptation for in-home distribution of visual content. It provides computing and networking resources and its switching software supports building of custom data plane for visual content. We prototype the visual-sharing switching device and verify that it can be flexibly programmed to support various visual-sharing scenarios.
Centralized mediation of multiparty video sharing for smart work
Sang‐Uk Han, JongWon Kim
IF 10.9
IEEE Transactions on Consumer Electronics
Natural sharing of informative media contents is a key service in collaborative and smart work that flexibly conducts remote operations and communicates with remote co-workers in home offices and smart work centers. For collaborative and smart work, we need to carefully disseminate media services tailored for each participating site in order to naturally exchange shared contents between participants. In this paper, we present a centralized mediation approach to fairly improve the qualities of shared videos in multi-producer multi-consumer environment. The proposed approach carries out progressive improvement of end-user quality and efficient placement of transcoders by balancing the overall usage of computation and networking resources. Computer-simulated experiment results demonstrate that the proposed approach can find a feasible solution and improve the running time performance.
Robust MMSE video decoding: theory and practical implementations
Chang‐Su Kim, JongWon Kim, Ioannis Katsavounidis, C.‐C. Jay Kuo
IF 11.1
IEEE Transactions on Circuits and Systems for Video Technology
A novel video decoding algorithm based on the minimum mean square error (MMSE) criterion is investigated in this research. To alleviate the effect of transmission errors, we first develop an error propagation model to estimate and track the mean square error (MSE) of each pixel in the decoder. Then, the proposed video decoding algorithm adjusts the reconstruction of each pixel adaptively according to fluctuating channel conditions. More specifically, the decoder reconstructs a pixel in the kth frame F/sub k/ by using a weighted sum of two pixels in frames F/sub k-1/ and F/sub k-2/, respectively, where their weights are adaptively selected to minimize the MSE of the reconstructed pixel by using the error propagation model. Extensive simulation results performed on standard H.263 bit streams demonstrate that the MMSE-based concealment algorithm yields a better performance than the conventional method, even if the encoder transmits a single motion vector per block. Moreover, the proposed MMSE decoding algorithm significantly enhances the error resilient capability of the double-vector motion compensation (DMC) algorithm, where two motion vectors are sent per block.
Longitudinal transformation of mitochondrial metabolism during neurogenesis
Donghoon Lim, Sewon Park, Jong Seung Lee, Hyo Jin Gwon, Yunwoo Nam, Suhyuk Choi, JongWon Kim, Yeonsu Kim, Geonwoo Park, Woo Yang Pyun, Hyun Woo Park, Seung‐Woo Cho, Hyun S. Ahn
IF 9.1
Proceedings of the National Academy of Sciences
Neural stem cells (NSCs) are valuable in the quest to conquer neurodegenerative diseases due to their capability to reconstruct the damaged neuronal networks. However, deep understanding of the intercellular signaling mechanism controlling the lineage and fate of the stem cells is required before potential clinical applications. Here, we applied nondestructive and label-free electrochemical methods for the longitudinal tracking of NSC respiratory metabolism. Sharp change in the oxygen utilization pattern was observed concomitant to stemness loss and onset of differentiation, suggesting metabolic reprogramming in the transition. Intra- and extracellular profiling of mitochondrial metabolites revealed molecular preference in the extracellular transport rates. Electrochemical emulation of the metabolite release pattern induced acceleration of neurite growth in nearby cells, suggesting paracrine signaling system mediated by mitochondrial metabolites.
Quantitative framework for the definition of planar spatial resolution in scanning electrochemical microscopy
Geonwoo Park, H. J. Oh, Jongwon Kim, JongWon Kim, Seungwoo Hong, Hyun S. Ahn
IF 4.2
Chemical Communications
This study presents a set of quantitative criteria for the definition of planar spatial resolution in scanning electrochemical microscopy (SECM) imaging using an effective diffusion ellipsoid (EDE) model. Experiments and simulations confirm that smaller electrodes improve imaging resolution, and the resolution-step-size equivalence holds across both feedback and generation-collection modes. The finding reported here enables the establishment of standardized conditions for surface activity mapping by SECM.
MV2: A Large-Scale 360-degree Multi-View Maritime Vision Dataset for Object Detection and Segmentation
Junseok Lee, JongWon Kim, Seongju Lee, Taeri Kim, Kyoobin Lee
Reliable navigation of autonomous vessels critically depends on robust situational awareness, particularly object detection. For this, an accurate, 360-degree perception of the surrounding environment is essential. However, most existing datasets lack the comprehensive multi-view data required for this full environmental coverage. This absence of large-scale, multi-view image datasets specifically designed for maritime situational awareness on vessels presents a significant challenge. To address this, we introduce the Multi-View Maritime Vision (MV2) dataset, comprising 159,386 visible-light images captured from six distinct viewpoints around a vessel. MV2 provides a complete 360-degree omnidirectional perspective, offering critical support for maritime situational awareness applications. The dataset includes object bounding boxes, along with semantic, instance, and panoptic segmentation labels, and encompasses a wide range of environmental conditions, supporting diverse computer-vision tasks. Additionally, we benchmarked state-of-the-art object-detection and panoptic-segmentation models on MV2, demonstrating its contribution to advancing maritime autonomy research. The dataset is available at https://sites.google.com/view/multi-view-maritime-vision.
Two novel genetic variants in WFDC2 gene from patients with bronchiectasis
Jeong‐Min Kim, Soojin Hwang, Hye-Won Cho, Young Jun Kim, Dong Mun Shin, Eun Hee Lee, Myungshin Kim, Cheonghwa Lee, JongWon Kim, Hyun‐Young Park, Beom Hee Lee, Mi‐Hyun Park
Design of Virtual Driving Test Environment for Collecting and Validating Bad Weather SiLS Data Based on Multi-Source Images Using DCU with V2X-Car Edge Cloud
In real-world autonomous driving tests, unexpected events such as pedestrians or wild animals suddenly entering the driving path can occur. Conducting actual test drives under various weather conditions may also lead to dangerous situations. Furthermore, autonomous vehicles may operate abnormally in bad weather due to limitations of their sensors and GPS. Driving simulators, which replicate driving conditions nearly identical to those in the real world, can drastically reduce the time and cost required for market entry validation; consequently, they have become widely used. In this paper, we design a virtual driving test environment capable of collecting and verifying SiLS data under adverse weather conditions using multi-source images. The proposed method generates a virtual testing environment that incorporates various events, including weather, time of day, and moving objects, that cannot be easily verified in real-world autonomous driving tests. By setting up scenario-based virtual environment events, multi-source image analysis and verification using real-world DCUs (Data Concentrator Units) with V2X-Car edge cloud can effectively address risk factors that may arise in real-world situations. We tested and validated the proposed method with scenarios employing V2X communication and multi-source image analysis.
