OPT-VCG: A Novel Proposal for 3D SoC Test Optimization

Jingbo Shao,Yongqing Fu,Xiaoxiao Liu,Guohui Zhou 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.2

As an emerging technology for on-chip interconnect scaling in vertical direction in semiconductor industry, through-silicon-via (TSV) demonstrates its advantages and has been adopted for 3D SoC implementation. Optimal test architecture and test scheduling are significant for stacked 3D SoC design. However existing design methods cannot achieve both optimal test time and individual rationality. In this paper, game theory based 3D SoC test architecture optimization and test scheduling method is proposed under constraints of the available number of TSVs for test time minimization and rational test band width allocation. VCG algorithm is brought to 3D SoC design. Three kinds of stacked SoCs are built using ITC’02 SoC test benchmarks, and experimental results on them show the advantages of the proposed method over prior work.

Background Prior-based Salient Object Detection via Adaptive Figure-Ground Classification

( Jingbo Zhou ),( Jiyou Zhai ),( Yongfeng Ren ),( Ali Lu ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.3

In this paper, a novel background prior-based salient object detection framework is proposed to deal with images those are more complicated. We take the superpixels located in four borders into consideration and exploit a mechanism based on image boundary information to remove the foreground noises, which are used to form the background prior. Afterward, an initial foreground prior is obtained by selecting superpixels that are the most dissimilar to the background prior. To determine the regions of foreground and background based on the prior of them, a threshold is needed in this process. According to a fixed threshold, the remaining superpixels are iteratively assigned based on their proximity to the foreground or background prior. As the threshold changes, different foreground priors generate multiple different partitions that are assigned a likelihood of being foreground. Last, all segments are combined into a saliency map based on the idea of similarity voting. Experiments on five benchmark databases demonstrate the proposed method performs well when it compares with the state-of-the-art methods in terms of accuracy and robustness.

A New Connected Coherence Tree Algorithm For Image Segmentation

( Jingbo Zhou ),( Shangbing Gao ),( Zhong Jin ) 한국인터넷정보학회 2012 KSII Transactions on Internet and Information Syst Vol.6 No.4

In this paper, we propose a new multi-scale connected coherence tree algorithm (MCCTA) by improving the connected coherence tree algorithm (CCTA). In contrast to many multi-scale image processing algorithms, MCCTA works on multiple scales space of an image and can adaptively change the parameters to capture the coarse and fine level details. Furthermore, we design a Multi-scale Connected Coherence Tree algorithm plus Spectral graph partitioning (MCCTSGP) by combining MCCTA and Spectral graph partitioning in to a new framework. Specifically, the graph nodes are the regions produced by CCTA and the image pixels, and the weights are the affinities between nodes. Then we run a spectral graph partitioning algorithm to partition on the graph which can consider the information both from pixels and regions to improve the quality of segments for providing image segmentation. The experimental results on Berkeley image database demonstrate the accuracy of our algorithm as compared to existing popular methods.

Salient Object Detection via Adaptive Region Merging

( Jingbo Zhou ),( Jiyou Zhai ),( Yongfeng Ren ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.9

Most existing salient object detection algorithms commonly employed segmentation techniques to eliminate background noise and reduce computation by treating each segment as a processing unit. However, individual small segments provide little information about global contents. Such schemes have limited capability on modeling global perceptual phenomena. In this paper, a novel salient object detection algorithm is proposed based on region merging. An adaptive-based merging scheme is developed to reassemble regions based on their color dissimilarities. The merging strategy can be described as that a region R is merged with its adjacent region Q if Q has the lowest dissimilarity with Q among all Q`s adjacent regions. To guide the merging process, superpixels that located at the boundary of the image are treated as the seeds. However, it is possible for a boundary in the input image to be occupied by the foreground object. To avoid this case, we optimize the boundary influences by locating and eliminating erroneous boundaries before the region merging. We show that even though three simple region saliency measurements are adopted for each region, encouraging performance can be obtained. Experiments on four benchmark datasets including MSRA-B, SOD, SED and iCoSeg show the proposed method results in uniform object enhancement and achieve state-of-the-art performance by comparing with nine existing methods.

Salient Object Detection via Multiple Random Walks

( Jiyou Zhai ),( Jingbo Zhou ),( Yongfeng Ren ),( Zhijian Wang ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.4

In this paper, we propose a novel saliency detection framework via multiple random walks (MRW) which simulate multiple agents on a graph simultaneously. In the MRW system, two agents, which represent the seeds of background and foreground, traverse the graph according to a transition matrix, and interact with each other to achieve a state of equilibrium. The proposed algorithm is divided into three steps. First, an initial segmentation is performed to partition an input image into homogeneous regions (i.e., superpixels) for saliency computation. Based on the regions of image, we construct a graph that the nodes correspond to the superpixels in the image, and the edges between neighboring nodes represent the similarities of the corresponding superpixels. Second, to generate the seeds of background, we first filter out one of the four boundaries that most unlikely belong to the background. The superpixels on each of the three remaining sides of the image will be labeled as the seeds of background. To generate the seeds of foreground, we utilize the center prior that foreground objects tend to appear near the image center. In last step, the seeds of foreground and background are treated as two different agents in multiple random walkers to complete the process of salient object detection. Experimental results on three benchmark databases demonstrate the proposed method performs well when it against the state-of-the-art methods in terms of accuracy and robustness.

An Improved Saliency Detection for Different Light Conditions

( Yongfeng Ren ),( Jingbo Zhou ),( Zhijian Wang ),( Yunyang Yan ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.3

In this paper, we propose a novel saliency detection framework based on illumination invariant features to improve the accuracy of the saliency detection under the different light conditions. The proposed algorithm is divided into three steps. First, we extract the illuminant invariant features to reduce the effect of the illumination based on the local sensitive histograms. Second, a preliminary saliency map is obtained in the CIE Lab color space. Last, we use the region growing method to fuse the illuminant invariant features and the preliminary saliency map into a new framework. In addition, we integrate the information of spatial distinctness since the saliency objects are usually compact. The experiments on the benchmark dataset show that the proposed saliency detection framework outperforms the state-of-the-art algorithms in terms of different illuminants in the images.

A Case of MOGAD Complicated With Cerebral Vasculitis: Case Report and Literature Review

Yimin Cao,Jingbo Xu,Zexi Yi,Lixia Zhou 대한신경과학회 2023 Journal of Clinical Neurology Vol.19 No.1

Effects of Marbling on Meat Quality Characteristics and Intramuscular Connective Tissue of Beef Longissimus Muscle

Li, Chunbao,Zhou, Guanghong,Xu, Xinglian,Zhang, Jingbo,Xu, Shuqin,Ji, Yanfeng Asian Australasian Association of Animal Productio 2006 Animal Bioscience Vol.19 No.12

This study was designed to explore the effects of marbling on meat quality characteristics and intramuscular connective tissue of beef longissimus muscle. Chemical determinations, histological and mechanical measurements were performed on the raw and cooked meat at d 4 postmortem. The results showed that crude fat, collagen, fiber diameter and maximum transition temperature of intramuscular connective tissue increased (p<0.05) with the increase of marbling score. The cooking losses, collagen solubility, WBSF and perimysial thickness decreased (p<0.05) with the increasing marbling. WBSF correlated (p<0.05) with moisture, crude fat, collagen, cooking losses, sarcomere length and perimysial thickness. The development of marbling results in the decline in cooking losses, the avoidance of sarcomere shortening, and the disorganization of the perimysia, which accounts for the improvement of beef tenderness.

LitCovid-AGAC: cellular and molecular level annotation data set based on COVID-19

Ouyang, Sizhuo,Wang, Yuxing,Zhou, Kaiyin,Xia, Jingbo Korea Genome Organization 2021 Genomics & informatics Vol.19 No.3

Currently, coronavirus disease 2019 (COVID-19) literature has been increasing dramatically, and the increased text amount make it possible to perform large scale text mining and knowledge discovery. Therefore, curation of these texts becomes a crucial issue for Bio-medical Natural Language Processing (BioNLP) community, so as to retrieve the important information about the mechanism of COVID-19. PubAnnotation is an aligned annotation system which provides an efficient platform for biological curators to upload their annotations or merge other external annotations. Inspired by the integration among multiple useful COVID-19 annotations, we merged three annotations resources to LitCovid data set, and constructed a cross-annotated corpus, LitCovid-AGAC. This corpus consists of 12 labels including Mutation, Species, Gene, Disease from PubTator, GO, CHEBI from OGER, Var, MPA, CPA, NegReg, PosReg, Reg from AGAC, upon 50,018 COVID-19 abstracts in LitCovid. Contain sufficient abundant information being possible to unveil the hidden knowledge in the pathological mechanism of COVID-19.

Research and Practice of Full Plugging Groundwater Technology in Water-Rich TBM Diversion Tunnel

Lichuan Wang,Shuai Zhang,Zongqing Zhou,Jian Wu,Tao Bai,Yunjuan Chen,Jingbo Zhao,Shuo Xu 대한토목학회 2024 KSCE Journal of Civil Engineering Vol.28 No.2

To solve the problem of water discharge in the tunnel when the tunnel passes through the low-pressure water-rich fractured stratum, the grouting plugging technology of the low-pressure water-rich tunnel is studied. The grouting plugging scheme is optimized through the field test. The post-validation research is numerically simulated and the parameters of the complete sealing grouting ring are analyzed. The results show that: 1) Full plugging grouting can effectively improve the funnel effect of precipitation with good water plugging effect. With the decrease of the permeability coefficient and the increase of the thickness of the grouting ring, the flow velocity around the tunnel and the water discharge in the tunnel both decreased significantly, with a trend of “rapidly decreasing-slowly decreasing”. Considering various factors, an optimal grouting ring thickness between 1.5 m and 2.5 m and a reasonable range for permeability coefficient between 2.07 × 10−6 cm/s and 4.14 × 10−6 cm/s are considered appropriate. 2) The use of cement-water glass system full plugging grouting for water plugging, can significantly reduce the discharge of water, only partial dripping or even dripping state. Using polyurethane foam single point method to systematically block grouting and water plugging can only changes the discharge path and hardly attenuates water discharge.