Fe- and Co-based Amorphous / Nanocrystalline Soft-magnetic Materials

Baolong Shen 한국자기학회 2010 한국자기학회 학술연구발표회 논문개요집 Vol.2010 No.12

Fast CU Encoding Schemes Based on Merge Mode and Motion Estimation for HEVC Inter Prediction

( Jinfu Wu ),( Baolong Guo ),( Jie Hou ),( Yunyi Yan ),( Jie Jiang ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.3

The emerging video coding standard High Efficiency Video Coding (HEVC) has shown almost 40% bit-rate reduction over the state-of-the-art Advanced Video Coding (AVC) standard but at about 40% computational complexity overhead. The main reason for HEVC computational complexity is the inter prediction that accounts for 60%-70% of the whole encoding time. In this paper, we propose several fast coding unit (CU) encoding schemes based on the Merge mode and motion estimation information to reduce the computational complexity caused by the HEVC inter prediction. Firstly, an early Merge mode decision method based on motion estimation (EMD) is proposed for each CU size. Then, a Merge mode based early termination method (MET) is developed to determine the CU size at an early stage. To provide a better balance between computational complexity and coding efficiency, several fast CU encoding schemes are surveyed according to the rate-distortion-complexity characteristics of EMD and MET methods as a function of CU sizes. These fast CU encoding schemes can be seamlessly incorporated in the existing control structures of the HEVC encoder without limiting its potential parallelization and hardware acceleration. Experimental results demonstrate that the proposed schemes achieve 19%-46% computational complexity reduction over the HEVC test model reference software, HM 16.4, at a cost of 0.2%-2.4% bit-rate increases under the random access coding configuration. The respective values under the low-delay B coding configuration are 17%-43% and 0.1%-1.2%.

A Sparse Target Matrix Generation Based Unsupervised Feature Learning Algorithm for Image Classification

( Dan Zhao ),( Baolong Guo ),( Yunyi Yan ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.6

Unsupervised learning has shown good performance on image, video and audio classification tasks, and much progress has been made so far. It studies how systems can learn to represent particular input patterns in a way that reflects the statistical structure of the overall collection of input patterns. Many promising deep learning systems are commonly trained by the greedy layerwise unsupervised learning manner. The performance of these deep learning architectures benefits from the unsupervised learning ability to disentangling the abstractions and picking out the useful features. However, the existing unsupervised learning algorithms are often difficult to train partly because of the requirement of extensive hyperparameters. The tuning of these hyperparameters is a laborious task that requires expert knowledge, rules of thumb or extensive search. In this paper, we propose a simple and effective unsupervised feature learning algorithm for image classification, which exploits an explicit optimizing way for population and lifetime sparsity. Firstly, a sparse target matrix is built by the competitive rules. Then, the sparse features are optimized by means of minimizing the Euclidean norm (L₂) error between the sparse target and the competitive layer outputs. Finally, a classifier is trained using the obtained sparse features. Experimental results show that the proposed method achieves good performance for image classification, and provides discriminative features that generalize well.

Image Retrieval Method Based on IPDSH and SRIP

( Xu Zhang ),( Baolong Guo ),( Yunyi Yan ),( Wei Sun ),( Meng Yi ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.5

At present, the Content-Based Image Retrieval (CBIR) system has become a hot research topic in the computer vision field. In the CBIR system, the accurate extractions of low-level features can reduce the gaps between high-level semantics and improve retrieval precision. This paper puts forward a new retrieval method aiming at the problems of high computational complexities and low precision of global feature extraction algorithms. The establishment of the new retrieval method is on the basis of the SIFT and Harris (APISH) algorithm, and the salient region of interest points (SRIP) algorithm to satisfy users` interests in the specific targets of images. In the first place, by using the IPDSH and SRIP algorithms, we tested stable interest points and found salient regions. The interest points in the salient region were named as salient interest points. Secondary, we extracted the pseudo-Zernike moments of the salient interest points` neighborhood as the feature vectors. Finally, we calculated the similarities between query and database images. Finally, We conducted this experiment based on the Caltech-101 database. By studying the experiment, the results have shown that this new retrieval method can decrease the interference of unstable interest points in the regions of non-interests and improve the ratios of accuracy and recall.

STAR-24K: A Public Dataset for Space Common Target Detection

Chaoyan Zhang,Baolong Guo,Nannan Liao,Qiuyun Zhong,Hengyan Liu,Cheng Li,Jianglei Gong 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.2

The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.

Proteome Analysis on Lethal Effect of l2 in the Sex-linked Balanced Lethal Strains of Silkworm, Bombyx mori

Jine Chen,Baolong Niu,Yongqiang Wang,Yan Liu,Peigang Liu,Zhiqi Meng,Boxiong Zhong 한국생물공학회 2012 Biotechnology and Bioprocess Engineering Vol.17 No.2

The sex-linked balanced lethal (SLBL) strains of silkworm serve as an effective system for sex-control in silkworm. To gain comprehensive insight into the effect of one sex-linked balanced lethal gene l2, comparative proteomic analysis was carried out between the survival embryos (W +l 1 Z l 1 +l 2 ) and lethal embryos (W +l 1 Z l 1 +l 2 ) before the lethal stage. The lethal stage of l2 was confirmed by observing the typical dead embryo morphology. The two genotype embryos before lethal stage were distinguished using polymorphic simple sequence repeats (SSR) markers closely linked to l2 on the sex chromosome. Finally, 11 differentially expressed protein spots were successfully identified by MALDI-TOF/TOF mass spectrometry (MS). Among them,only 1 protein identified as heat shock protein 20.4(HSP20.4) was up-regulated in the lethal embryos, while the other 10 were down-regulated. The up-regulation of HSP20.4 suggests that there may be abnormal polypeptides produced in the lethal embryos. The gene ontology (GO)annotation indicated those down-regulated proteins are involved in important biological processes including embryo development, nucleoside metabolism, tRNA splicing, translation and protein folding. The biological pathway analysis showed that those down-regulated proteins are mainly involved in spindle assemblage and morphogenesis. Based on our results, we suggest that the l2 may be the mutant expressing abnormal polypeptides. Its expression has a negative effect on mitosis and morphogenesis processes. The death of the embryos may be caused by the accumulation of abnormal polypeptides and the handicap of cell proliferation and morphogenesis.

A Fast TU Size Decision Method for HEVC RQT Coding

( Jinfu Wu ),( Baolong Guo ),( Yunyi Yan ),( Jie Hou ),( Dan Zhao ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.6

The emerging high efficiency video coding (HEVC) standard adopts the quadtree-structured transform unit (TU) in the residual quadtree (RQT) coding. Each TU allows to be split into four equal sub-TUs recursively. The RQT coding is performed for all the possible transform depth levels to achieve the highest coding efficiency, but it requires a very high computational complexity for HEVC encoders. In order to reduce the computational complexity requested by the RQT coding, in this paper, we propose a fast TU size decision method incorporating an adaptive maximum transform depth determination (AMTD) algorithm and a full check skipping - early termination (FCS-ET) algorithm. Because the optimal transform depth level is highly content-dependent, it is not necessary to perform the RQT coding at all transform depth levels. By the AMTD algorithm, the maximum transform depth level is determined for current treeblock to skip those transform depth levels rarely used by its spatially adjacent treeblocks. Additionally, the FCS-ET algorithm is introduced to exploit the correlations of transform depth level between four sub-CUs generated by one coding unit (CU) quadtree partitioning. Experimental results demonstrate that the proposed overall algorithm significantly reduces on average 21% computational complexity while maintaining almost the same rate distortion (RD) performance as the HEVC test model reference software, HM 13.0.

Large Glass-forming ability and Magnetocaloric Effect in Gd₅₅Co₂₀Al₂₃Si₂ Bulk Metallic Glass

Li Qian,Cai Pingping,Shen Baolong,Makino Akihiro,Inoue Akihisa 한국자기학회 2010 한국자기학회 학술연구발표회 논문개요집 Vol.2010 No.12

Enhancement of Soft-magnetic Properties of FeCoNbBCu Nanocrystalline Alloys with Ni Addition

Fanli Kong,Xingdu Fan,Anding Wang,Baolong Shen,Akihiro Makino,Akihisa Inoue 한국자기학회 2010 한국자기학회 학술연구발표회 논문개요집 Vol.2010 No.12

Large Glass-forming Ability and Magnetocaloric Effectin Gd<SUB>55</SUB>Co<SUB>20</SUB>Al<SUB>23</SUB>Si<SUB>2</SUB> Bulk Metallic Glass

Li Qian,Cai Pingping,Shen Baolong,Makino Akihiro,Inoue Akihisa 한국자기학회 2011 Journal of Magnetics Vol.16 No.4

In this study, we investigated the glass-forming ability (GFA) and magnetocaloric effect (MCE) of Gd55Co20Al23Si2 bulk glassy alloy. It is found that the addition of 2 at% Si is effective for extension of the supercooled liquid region (ΔTx), the ΔTx is 55 K for the Gd55Co20Al25 glassy alloy, and increases to 79 K for the Gd55Co20Al23Si2 alloy. As a result, Gd55Co20Al23Si2 glassy alloys with diameters up to 5 mm were successfully synthesized. The alloys also exhibit large MCE, i.e., the magnetic entropy change (ΔSm) of 8.9 J kg<SUP>?1</SUP> K<SUP>?1</SUP>, the full width at half maximum of the ΔSm (δTFWHM) of 87 K, and the refrigerant capacity (RC) of 774 J kg<SUP>?1</SUP>.