100 research outputs found
A mathematical morphological method to thin edge detection in dark region
[[abstract]]The performance of image segmentation depends on the output quality of the edge detection process. Typical edge detecting method is based on detecting pixels in an image with high gradient values, and then applies a global threshold value to extract the edge points of the image. By these methods, some detected edge points may not belong to the edge and some thin edge points in dark regions of the image are being eliminated. These eliminated edges may be with important features of the image. This paper proposes a new mathematical morphological edge-detecting algorithm based on the morphological residue transformation derived from dilation operation to detect and preserve the thin edges. Moreover, this work adopts five bipolar oriented edge masks to prune the miss detected edge points. The experimental results show that the proposed algorithm is successfully to preserve the thin edges in the dark regions.[[conferencetype]]國際[[conferencedate]]20041218~20041221[[booktype]]紙本[[conferencelocation]]Rome, Ital
Efficient Object Detection and Intelligent Information Display Using YOLOv4-Tiny
This study aims to develop an innovative image recognition and information display approach based on you only look once version 4 (YOLOv4)-tiny framework. The lightweight YOLOv4-tiny model is modified by replacing convolutional modules with Fire modules to further reduce its parameters. Performance reductions are offset by including spatial pyramid pooling, and they also improve the model’s detection ability for objects of various sizes. The pattern analysis, statistical modeling, and computational learning visual object classes (PASCAL VOC) 2012 dataset are used, the proposed modified YOLOv4-tiny architecture achieves a higher mean average precision (mAP) that is 1.59% higher than its unmodified counterpart. This study addresses the need for efficient object detection and recognition on resource-constrained devices by leveraging YOLOv4-tiny, Fire modules, and SPP to achieve accurate image recognition at a low computational cost
Ant colony optimization for best path planning
[[abstract]]The paper presents an optimal approach to search the best path of a map considering the traffic loading conditions. The main objective of this work is to minimize the path length to get the best path planning for a given map. This study proposes a solution algorithm based on the ant colony optimization technique to search the shortest path from a desired origin to a desired destination of the map. The proposed algorithm is implemented in C++. Furthermore, the simulation program can randomly generate maps for evaluating its flexibility and performance. Simulation results demonstrate that the proposed algorithm can obtain the shortest path of a map with fast speed.[[conferencetype]]國際[[conferencedate]]20041026~20041029[[booktype]]紙本[[conferencelocation]]Sapporo, Japa
Novel Dynamic Structure Neural Network for Optical Character Recognition
[[abstract]]This paper presents a novel dynamic structure neural network (DSNN) and a learning algorithm for training DSNN. The performance of a neural network system depends on several factors. In that, the architecture of a neural network plays an important role. The objective of the developing DSNN is to avoid trial-and-error process for designing a neural network system. The architecture of DSNN consists of a three-dimensional set of neurons with input/output nodes and connection weights. Designers can define the maximum connection number of each neuron. Moreover, designers can manually deploy neurons in a virtual 3D space, or randomly generate the system structure by the proposed learning algorithm. This work also develops an automatic restructuring algorithm integrated in the proposed learning algorithm to improve the system performance. Due to the novel dynamic structure of DSNN and the restructuring algorithm, the design of DSNN is fast and convenient. Furthermore, DSNN is implemented in C++ with man-machine interactive procedures and tested on many cases with very promising results.[[conferencetype]]國際[[conferencedate]]20041218~20041221[[iscallforpapers]]Y[[conferencelocation]]Rome, Ital
Whole pelvic helical tomotherapy for locally advanced cervical cancer: technical implementation of IMRT with helical tomothearapy
<p>Abstract</p> <p>Background</p> <p>To review the experience and to evaluate the treatment plan of using helical tomotherapy (HT) for the treatment of cervical cancer.</p> <p>Methods</p> <p>Between November 1st, 2006 and May 31, 2009, 10 cervical cancer patients histologically confirmed were enrolled. All of the patients received definitive concurrent chemoradiation (CCRT) with whole pelvic HT (WPHT) followed by brachytherapy. During WPHT, all patients were treated with cisplatin, 40 mg/m<sup>2 </sup>intravenously weekly. Toxicity of treatment was scored according to the Common Terminology Criteria for Adverse Events v3.0 (CTCAE v3.0).</p> <p>Results</p> <p>The mean survival was 25 months (range, 3 to 27 months). The actuarial overall survival, disease-free survival, locoregional control and distant metastasis-free rates at 2 years were 67%, 77%, 90% and 88%, respectively. The average of uniformity index and conformal index was 1.06 and 1.19, respectively. One grade 3 of acute toxicity for diarrhea, thrombocytopenia and three grade 3 leucopenia were noted during CCRT. Only one grade 3 of subacute toxicity for thrombocytopenia was noted. There were no grade 3 or 4 subacute toxicities of anemia, leucopenia, genitourinary or gastrointestinal effects. Compared with conventional whole pelvic radiation therapy (WPRT), WPHT decreases the mean dose to rectum, bladder and intestines successfully.</p> <p>Conclusion</p> <p>HT provides feasible clinical outcomes in locally advanced cervical cancer patients. Long-term follow-up and enroll more locally advanced cervical carcinoma patients by limiting bone marrow radiation dose with WPHT technique is warranted.</p
In vitro modification of human centromere protein CENP-C fragments by small ubiquitin-like modifier (SUMO) protein: Definitive identification of the modification sites by tandem mass spectrometry analysis of the isopeptides
Protein sumoylation by small ubiquitin-like modifier (SUMO) proteins is an important post-translational regulatory modification. A role in the control of chromosome dynamics was first suggested when SUMO was identified as high-copy suppressor of the centromere protein CENP-C mutants. CENP-C itself contains a consensus sumoylation sequence motif that partially overlaps with its DNA binding and centromere localization domain. To ascertain whether CENP-C can be sumoylated, tandem mass spectrometry (MS) based strategy was developed for high sensitivity identification and sequencing of sumoylated isopeptides present among in-gel-digested tryptic peptides of SDS-PAGE fractionated target proteins. Without a predisposition to searching for the expected isopeptides based on calculated molecular mass and relying instead on the characteristic MS/MS fragmentation pattern to identify sumolylation, we demonstrate that several other lysine residues located not within the perfect consensus sumoylation motif {psi}KXE/D, where {psi} represents a large hydrophobic amino acid, and X represnts any amino acid, can be sumolylated with a reconstituted in vitro system containing only the SUMO proteins, E1-activating enzyme and E2-conjugating enzyme (Ubc9). In all cases, target sites that can be sumoylated by SUMO-2 were shown to be equally susceptible to SUMO-1 attachments which include specific sites on SUMO-2 itself, Ubc9, and the recombinant CENP-C fragments. Two non-consensus sites on one of the CENP-C fragments were found to be sumoylated in addition to the predicted site on the other fragment. The developed methodologies should facilitate future studies in delineating the dynamics and substrate specificities of SUMO-1/2/3 modifications and the respective roles of E3 ligases in the process
Toll-like receptor 2 gene polymorphisms, pulmonary tuberculosis, and natural killer cell counts
<p>Abstract</p> <p>Background</p> <p>To investigate whether the toll-like receptor 2 polymorphisms could influence susceptibility to pulmonary TB, its phenotypes, and blood lymphocyte subsets.</p> <p>Methods</p> <p>A total of 368 subjects, including 184 patients with pulmonary TB and 184 healthy controls, were examined for TLR2 polymorphisms over locus -100 (microsatellite guanine-thymine repeats), -16934 (T>A), -15607 (A>G), -196 to -174 (insertion>deletion), and 1350 (T>C). Eighty-six TB patients were examined to determine the peripheral blood lymphocyte subpopulations.</p> <p>Results</p> <p>We newly identified an association between the haplotype [A-G-(insertion)-T] and susceptibility to pulmonary TB (p = 0.006, false discovery rate q = 0.072). TB patients with systemic symptoms had a lower -196 to -174 deletion/deletion genotype frequency than those without systemic symptoms (5.7% vs. 17.7%; p = 0.01). TB patients with the deletion/deletion genotype had higher blood NK cell counts than those carrying the insertion allele (526 vs. 243.5 cells/μl, p = 0.009). TB patients with pleuritis had a higher 1350 CC genotype frequency than those without pleuritis (12.5% vs. 2.1%; p = 0.004). TB patients with the 1350 CC genotype had higher blood NK cell counts than those carrying the T allele (641 vs. 250 cells/μl, p = 0.004). TB patients carrying homozygous short alleles for GT repeats had higher blood NK cell counts than those carrying one or no short allele (641 vs. 250 cells/μl, p = 0.004).</p> <p>Conclusions</p> <p>TLR2 genetic polymorphisms influence susceptibility to pulmonary TB. TLR2 variants play a role in the development of TB phenotypes, probably by controlling the expansion of NK cells.</p
A Novel Dynamic Structural Neural Networks with Neuron-regeneration and Neuronegeneration Mechanisms
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