• Journal of Environmental Science International
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• v.29 no.8
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• pp.847-855
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• 2020

This study presented problems and improvements in the quality control of an air monitoring network, using Gyeongnam as an example. 1) The effective utilization rate of the air monitoring was 95%, which showed good management, but the maximum of 2% was indicated by zero or detection limit among measurement data. 2) In the equivalence evaluation of PM_2.5, the slope and intercept satisfy the evaluation criteria; however, 1% of the PM_2.5/PM₁₀ ratios were outliers. 3) All air monitoring stations meet the quality control standards; however, the management status is added to the quality inspection, management system is unified and the related budget is expanded, and systematic commission management is required.

• ETRI Journal
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• v.38 no.4
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• pp.703-713
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• 2016

In this paper, we present a segmentation-based method for offline Farsi handwritten word recognition. Although most segmentation-based systems suffer from segmentation errors within the first stages of recognition, using the inherent features of the Farsi writing script, we have segmented the words into sub-words. Instead of using a single complex classifier with many (N) output classes, we have created N simple recurrent neural network classifiers, each having only true/false outputs with the ability to recognize sub-words. Through the extraction of the number of sub-words in each word, and labeling the position of each sub-word (beginning/middle/end), many of the sub-word classifiers can be pruned, and a few remaining sub-word classifiers can be evaluated during the sub-word recognition stage. The candidate sub-words are then joined together and the closest word from the lexicon is chosen. The proposed method was evaluated using the Iranshahr database, which consists of 17,000 samples of Iranian handwritten city names. The results show the high recognition accuracy of the proposed method.

• Journal of information and communication convergence engineering
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• v.11 no.2
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• pp.69-81
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• 2013

Maintaining connectivity is essential in multi-hop wireless networks since the network topology cannot be pre-determined due to mobility and environmental effects. To maintain the connectivity, a critical point in the network topology should be identified where the critical point is the link or node that partitions the network when it fails. In this paper, we propose a new critical point identification algorithm and also present numerical results that compare the critical points of the network and H-hop sub-network illustrating how effectively sub-network information can detect the network-wide critical points. Then, we propose two localized topological control resilient schemes that can be applied to both global and local H-hop sub-network critical points to improve the network connectivity and the network resilience. Numerical studies to evaluate the proposed schemes under node and link failure network conditions show that our proposed resilient schemes increase the probability of the network being connected in variety of link and node failure conditions.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.464-467
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• 1996

This paper aims to exploit inter/intra-speaker phoneme sub-class variations as criteria for adaptation in a phoneme recognition system based on a novel neural network architecture. Using a subcluster neural network design based on the One-Class-in-One-Network (OCON) feed forward subnets, similar to those proposed by Kung (2) and Jou (1), joined by a common front-end layer. the idea is to adapt only the neurons within the common front-end layer of the network. Consequently resulting in an adaptation which can be concentrated primarily on the speakers vocal characteristics. Since the adaptation occurs in an area common to all classes, convergence on a single class will improve the recognition of the remaining classes in the network. Results show that adaptation towards a phoneme, in the vowel sub-class, for speakers MDABO and MWBTO Improve the recognition of remaining vowel sub-class phonemes from the same speaker

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.402-408
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• 2021

We are designed the delivery constitution technique that is to be measure the safe RFID statusof thewireless delivery system level (WDSL) on the delivery system tracking system. The delivery system level condition by the delivery system tracking system is organized with the RFID system. As to inspection a wireless network of the wireless network, we are found of the delivery value with wireless network by the upper take form. The concept of delivery system level is organized the reference of wireless level for delivery signal by the delivery RFID tracking system. Further, symbolizing a safe deliveryof the WDSL of the medium-minimum interval of the RFID tracking system, and the delivery wireless network RFID that was the delivery value of the far delivery of the DSTS-FA-_φMED-MIN with 5.80±1.20 units, that was the delivery value of the convenient delivery of the DSTS-CO-_φMED-MIN with 4.06±(-0.04) units, that was the delivery value of the flank delivery of the DSTS-_φMED-MIN with 0.91±0.07 units, that was the delivery value of the vicinage delivery of the DSTS-VI-_φMED-MIN with 0.18±(-0.03) units. The RFID will be to look into at the safe of the RFID tracking systemwith wireless network bythe delivery system level on the WDSL that is supply the wireless tracking system by the delivery system level system. We will be possible make to curb of a tracking system that to put the wireless signal and to use of the delivery data of RFID level by the delivery system.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.1-8
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• 2024

Busan is the 6th largest port city in the world, where nitrogen dioxide (NO₂) emissions from transportation and port industries are significant. This study aims to assess the NO₂ products of the Geostationary Environment Monitoring Spectrometer (GEMS) over Busan using ground-based instruments (i.e., surface in-situ network and Pandora). The GEMS vertical column densities of NO₂ showed reasonable consistency in the spatiotemporal variations, comparable to the previous studies. The GEMS data showed a consistent seasonal trend of NO₂ with the Korea Ministry of Environment network and Pandora in 2022, which is higher in winter and lower in summer. These agreements prove the capability of the GEMS data to monitor the air quality in Busan. The correlation coefficient and the mean bias error between the GEMS and Pandora NO₂ over Busan in 2022 were 0.53 and 0.023 DU, respectively. The GEMS NO₂ data were also positively correlated with the ground-based in-situ network with a correlation coefficient of 0.42. However, due to the significant spatiotemporal variabilities of the NO₂, the GEMS footprint size can hardly resolve small-scale variabilities such as the emissions from the road and point sources. In addition, relative biases of the GEMS NO₂ retrievals to the Pandora data showed seasonal variabilities, which is attributable to the air mass factor estimation of the GEMS. Further studies with more measurement locations for longer periods of data can better contribute to assessing the GEMS NO₂ data. Reliable GEMS data can further help us understand the Asian air quality with the diurnal variabilities.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.878-879
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• 2021

Most state-of-the-art CNNs for action recognition are based on a two-stream architecture: RGB frames stream represents the appearance and the optical flow stream interprets the motion of action. However, the cost of optical flow computation is very high and then it increases action recognition latency. We introduce a design strategy for action recognition inspired by a two-stream network and teacher-student architecture. There are two sub-networks in our neural networks, the optical flow sub-network as a teacher and the RGB frames sub-network as a student. In the training stage, we distill the feature from the teacher as a baseline to train student sub-network. In the test stage, we only use the student so that the latency reduces without computing optical flow. Our experiments show that its advantages over two-stream architecture in both speed and performance.

• Journal of Information Processing Systems
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• v.6 no.3
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• pp.307-322
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• 2010

Traffic classification is an essential task for network management. Many researchers have paid attention to initial sub-flow features based classifiers for traffic classification. However, the existing classifiers cannot classify traffic effectively in mobile IP networks. The classifiers depend on initial sub-flows, but they cannot always capture the sub-flows at a point of attachment for a variety of elements because of seamless mobility. Thus the ideal classifier should be capable of traffic classification based on not only initial sub-flows but also various types of sub-flows. In this paper, we propose a classifiable sub-flow selection method to realize the ideal classifier. The experimental results are so far promising for this research direction, even though they are derived from a reduced set of general applications and under relatively simplifying assumptions. Altogether, the significant contribution is indicating the feasibility of the ideal classifier by selecting not only initial sub-flows but also transition sub-flows.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.3
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• pp.106-112
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• 2004

This paper presents a new heuristic algorithm for the machine cell(MC) formation problem. MC formation problem is represented as an unbalanced k-way network partition and the proposed algorithm uses four stage-approach to solve the problem. Four stages are natural sub-network formation, determination of intial vertexes for each sub-network, determination of initial partition, and improvement of initial partition. Results of experiments show that the suggested algorithm provides near optimal solutions within very short computational time.

• Bulletin of the Korean Chemical Society
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• v.30 no.5
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• pp.1021-1025
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• 2009

A novel supramolecular network containing binuclear copper unit $[Cu(phen)_{2}({\mu}-ID\;A)Cu(phen){\cdot}(NO_{3})](NO_{3}){\cdot}4(H_{2}O)$ (1) was synthesized through the self-assembly of iminodiacetic acid ($H_2IDA$) and 1,10-phenanthroline (phen) in the condition of pH = 6. It has been characterized by the infrared (IR) spectroscopy, elemental analysis, single crystal X-ray diffraction, and thermogravimetric analysis (TGA). 1 shows a 2-D supramolecular structure assembled through strong and unique $\pi-\pi$ packing interactions. Density functional theory (DFT) calculations show that theoretical optimized structures can well reproduce the experimental structure. The TGA and powder X-ray diffraction (PXRD) curves indicate that the complex 1 can maintain the structural integrity even at the loss of free water molecules. The magnetic property is also reported in this paper.