• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.11
• /
• pp.4065-4083
• /
• 2021

Super-resolution can improve the clarity of low-resolution (LR) images, which can increase the accuracy of high-level compute vision tasks. Portable devices have low computing power and storage performance. Large-scale neural network super-resolution methods are not suitable for portable devices. In order to save the computational cost and the number of parameters, Lightweight image processing method can improve the processing speed of portable devices. Therefore, we propose the Enhanced Information Multiple Distillation Network (EIMDN) to adapt lower delay and cost. The EIMDN takes feedback mechanism as the framework and obtains low level features through high level features. Further, we replace the feature extraction convolution operation in Information Multiple Distillation Block (IMDB), with Ghost module, and propose the Enhanced Information Multiple Distillation Block (EIMDB) to reduce the amount of calculation and the number of parameters. Finally, coordinate attention (CA) is used at the end of IMDB and EIMDB to enhance the important information extraction from Spaces and channels. Experimental results show that our proposed can achieve convergence faster with fewer parameters and computation, compared with other lightweight super-resolution methods. Under the condition of higher peak signal-to-noise ratio (PSNR) and higher structural similarity (SSIM), the performance of network reconstruction image texture and target contour is significantly improved.

• The KIPS Transactions:PartD
• /
• v.15D no.4
• /
• pp.463-474
• /
• 2008

The advancement of information technology and the popularization of Internet has explosively increased the amount of multimedia contents. Therefore, the requirement of multimedia recommendation to satisfy a user's needs increases fastly. Up to now, CF is used to recommend general items and multimedia contents. However, general CF doesn't reflect visual characteristics of image contents so that it can't be adaptable to image recommendation. Besides, it has limitations in new item recommendation, the sparsity problem, and dynamic change of user preference. In this paper, we present new image recommendation method FBCF (Feature Based Collaborative Filtering) to resolve such problems. FBCF builds new user profile by clustering visual features in terms of user preference, and reflects user's current preference to recommendation by using preference feedback. Experimental result using real mobile images demonstrate that FBCF outperforms conventional CF by 400% in terms of recommendation ratio.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.6
• /
• pp.19-26
• /
• 2014

An ensemble classifier system is a widely-used multi-classifier system, which combines the results from each classifier and, as a result, achieves better classification result than any single classifier used. Several methods have been used to build an ensemble classifier including boosting, which is a cascade method where misclassified examples in previous stage are used to boost the performance in current stage. Boosting is, however, a serial method which does not form a complete feedback loop. In this paper, proposed is context sensitive SVM ensemble (CASE) which adopts SVM, one of the best classifiers in term of classification rate, as a basic classifier and clustering method to divide feature space into contexts. As CASE divides feature space and trains SVMs simultaneously, the result from one component can be applied to the other and CASE achieves better result than boosting. Experimental results prove the usefulness of the proposed method.

• The KIPS Transactions:PartD
• /
• v.13D no.7 s.110
• /
• pp.857-866
• /
• 2006

Performance of an image retrieval system is usually very low because of the semantic gap between the low level feature and the high level concept in a query image. Semantically relevant images may exhibit very different visual characteristics, and may be scattered in several clusters. In this paper, we propose a content based image rertrieval approach which combines region based image retrieval and a new relevance feedback method using adaptive clustering together. Our main goal is finding semantically related clusters to narrow down the semantic gap. Our method consists of region based clustering processes and cluster-merging process. All segmented regions of relevant images are organized into semantically related hierarchical clusters, and clusters are merged by finding the number of the latent clusters. This method, in the cluster-merging process, applies r: using v principal components instead of classical Hotelling's $T_v^2$ [1] to find the unknown number of clusters and resolve the singularity problem in high dimensions and demonstrate that there is little difference between the performance of $T^2$ and that of $T_v^2$. Experiments have demonstrated that the proposed approach is effective in improving the performance of an image retrieval system.

• Proceedings of the KIEE Conference
• /
• 1995.07c
• /
• pp.1365-1367
• /
• 1995

The PLS 2-GeV linac employs 11 units of high-power pulsed klystrons(80MW) as the main RF sources. The matching modulators of 200 MW(400kV, 500 A) can provide a flat-top pulse width of 4.4 ${\mu}s$ with a maximum pulse repetition rate of 120 Hz at the full power level. For a good stability of electron beams, the pulse-to-pulse flat-top voltage variation of a modulator requires less than 0.5%. In order to achieve this goal, we stabilized high voltage charging power supplies within 1% by a phase controlled SCR voltage regulator. In addition, we employed ac/dc feedback together with a resistive De-Q'ing system to achieve far less than 0.5% variation of the PFN charging voltage. This paper presents the main feature of the klystron-modulator system and the characteristics of the pulsed high-power RF system performance during the beam injection operation for the Pohang Light Source commissioning.

• BMB Reports
• /
• v.49 no.11
• /
• pp.587-589
• /
• 2016

The circadian clock system enables organisms to anticipate the rhythmic environmental changes and to manifest behavior and physiology at advantageous times of the day. Transcriptional/translational feedback loop (TTFL) is the basic feature of the eukaryotic circadian clock and is based on the rhythmic association of circadian transcriptional activator and repressor. In Drosophila, repression of dCLOCK/CYCLE (dCLK/CYC) mediated transcription by PERIOD (PER) is critical for inducing circadian rhythms of gene expression. Pacemaker neurons in the brain control specific circadian behaviors upon environmental timing cues such as light and temperature cycle. We show that amino acids 657-707 of dCLK are important for the transcriptional activation and the association with PER both in vitro and in vivo. Flies expressing dCLK lacking AA657-707 in $Clk^{out}$ genetic background, homologous to the mouse Clock allele where exon 19 region is deleted, display pacemaker-neuron-dependent perturbation of the molecular clockwork. The molecular rhythms in light-cycle-sensitive pacemaker neurons such as ventral lateral neurons ($LN_vs$) were significantly disrupted, but those in temperature-cycle-sensitive pacemaker neurons such as dorsal neurons (DNs) were robust. Our results suggest that the dCLK-controlled TTFL diversify in a pacemaker-neuron-dependent manner which may contribute to specific functions such as different sensitivities to entraining cues.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.51 no.9
• /
• pp.441-450
• /
• 2002

In this paper, optimal tuning problem of power system stabilizer using IA-QFT is investigated to improve power system dynamic stability in spite of parameter variation and disturbance uncertainties. The most important feature of QFT is that it is able to deal with the design problem of complicated uncertain plants. However, loop shaping is currently performed in computer aided design environments manually and it is usually a trial and error procedure. It is difficult to design a controller to satisfy all specifications manually. To solve this problem, a study of design automation using IA needs to be taken into account. The robustness of the proposed controller has been investigated on a single machine infinite bus model. The results are shown that the proposed PSS using IA-QFT is more robust than conventional PSS.

• The KIPS Transactions:PartB
• /
• v.19B no.1
• /
• pp.37-42
• /
• 2012

The pseudo relevance feedback suggests that frequent words at the top documents are related to initial query. However, the main drawback associated with the term frequency method is the fact that it relies on feature independence, and disregards any dependencies that may exist between words in the text. In this paper, we propose query expansion based on word graph using term proximity. It supplements term frequency method. On TREC WT10g test collection, experimental results in MAP(Mean Average Precision) show that the proposed method achieved 6.4% improvement over language model.

• Journal of Communications and Networks
• /
• v.8 no.4
• /
• pp.391-400
• /
• 2006

With the on-going wireless access technologies, the Internet has become accessible anytime anywhere. In wireless networks, link errors significantly degrade the performance of the transmission control protocol (TCP). To cope with this issue, this paper improves the recently-proposed terrestrial REFWA (T-REFWA) scheme by adding a new error recovery mechanism to its original design. In the T-REFWA scheme, senders are acknowledged with appropriate sending rates at which an efficient and fair utilization of network resources can be achieved. As the feedback values are computed independently of link errors, senders can keep transmitting data at high rates even in case of link error occurrences. Using this feature, the proposed error recovery mechanism can achieve high throughput in environments with high bit error rates. The throughput is further improved by disabling the exponential back-off algorithm of TCP so that long idle times are avoided in case of link errors. We show through simulations that the proposed method improves TCP performance in high bit error rates. Compared with several TCP variants, the proposed error recovery scheme exhibits higher link utilization and guarantees system fairness for different bit error rates.

• The Bulletin of The Korean Astronomical Society
• /
• v.37 no.1
• /
• pp.40.1-40.1
• /
• 2012

In the hierarchical universe, galaxy merger is predicted to be frequent, and thus it is an important element for understanding galaxy evolution. In particular, star formation is greatly enhanced during the merger. The aim of this study is to understand the position and rate change of star formation caused by equal-mass edge-on mergers. We use the GADGET2- N-body/SPH code, and fully consider gas cooling, star formation, and supernova feedback. We show the star formation rate (SFR), and the magnitude and color evolution of the merger remnants for 18 different configurations varying orbit elements and inclinations of host galaxies against orbit planes. Then we construct the mock images of the remnants and investigate on how equal-mass galaxy merger affects the SFR and color/magnitude evolution while considering dust reddening. We conclude that over 90% mass of SF in equal-mass merger is in the central region. SF in tidal feature involves a small fraction of new stars and thus is difficult to detect unless deep imaging is performed. Around 55 ${\pm}$ 5 percent of gas turns into stars until the final coalescence which typically corresponds to 0.8, 1.2, and 2.5 Gyr for direct, parabolic, and elliptical orbit, respectively. This result is roughly consistent with Cox et al. 2000. We plan to implement this result into semi-analytic model of galaxy formation. Caveats and future work on merging conditions are discussed.