• Journal of Environmental Science International
• /
• v.32 no.11
• /
• pp.811-820
• /
• 2023

This study investigated the protective effects of shade nets on Abies koreana seedlings subjected to high temperature and luminosity stress, which are pertinent for plant survival in climate change scenarios. This study, conducted at Konkuk University, compared the growth, survival, and soil conditions of 3-year-old specimens across natural, greenhouse, and shaded settingsfrom July to September 2022. Our findings demonstrated that shade nets significantly enhanced seedling survival by moderating soil temperature and moisture. This is particularly evident in high-temperature conditions, where shade nets mitigate stress on seedlings and safeguard them from excessive sunlight exposure. Proper net installation height and location are crucial for optimal temperature and humidity control, suggesting broader applicability for various species and offering strategies to combat the ecological impacts of climate change.

• Honam Mathematical Journal
• /
• v.33 no.2
• /
• pp.279-300
• /
• 2011

For a subset system M on any poset, M-Scott notions, such as M-way below relation,M-continuity,M-Scott convergence (of nets and filters respectively) and M-Scott topology are proposed Any approximating auxiliary relation on a poset can be represented by an M-way below relation such that this poset is M-continuous. It is shown that a poset is M-continuous iff the M-Scott topology is completely distributive. The topology induced by the M-Scott convergence coincides with the M-Scott topology. If the M-way below relation satisfies the property of interpolation then a poset is M-continuous if and only if the M-Scott convergence coincides with the M-Scott topological convergence. Also, M-continuity is characterized by a certain Galois connection.

• Journal of the Korea Convergence Society
• /
• v.7 no.2
• /
• pp.85-91
• /
• 2016

This study is related with support system plans of public-private convergence for emergency recovery services to fire victims. The current issues are analysed from the condition and problem analysis results of emergency recovery activities for fire victims. And building plans of an integrated support system based on the government and private sector cooperation are proposed. Overall, the system shows that the government is responsible for the functionality of management and supervision for the system operation, and the private is responsible for the functionality of specialized agencies for practical emergency recovery. Consequently, support system plans include with infrastructure maintenance of laws and regulations, contracting-out of the support system, stable supply of operating budget and function strengthening of public-private convergence for emergency recovery. Especially, plan for stable supply of operating budget in detail including with establishment of the fund and self-financing composition of private corporations for emergency recovery services is proposed. The results of this study will lead strengthening of fire safety welfare and social safety nets at future.

• Journal of the Institute of Convergence Signal Processing
• /
• v.4 no.4
• /
• pp.81-86
• /
• 2003

Current growth of VLSI design depends critically on the research and development of automatic layout tool. Automatic layout is composed of placement assigning a specific shape to a block and arranging the block on the layout surface and routing finding the interconnection of all the nets. Algorithms performing placement and routing impact on performance and area of VLSI design. Switchbox routing is a problem interconnecting each terminals on all four sides of the region, unlike channel routing. In this paper we propose a genetic algorithm searching solution space for switchbox routing problem. We compare the performance of proposed genetic algorithm(GA) for switchbox routing with that of other switchbox routing algorithm by analyzing the results of each implementation. Consequently experimental results show that out proposed algorithm reduce routing length and number of the via over the other switchbox routing algorithms.

• International Journal of Contents
• /
• v.10 no.3
• /
• pp.84-89
• /
• 2014

The mass-spring model has been typically employed in physical-based simulators for clothes or patches. The mass-spring model frequently utilizes equal mass and the gravity factor. The model structure of masses supports a shape applicable to fishing nets. Therefore, to create a simulation model of a fishing net, we consider the mass-spring model and adopt the tidal-current and buoyancy effects in underwater environments. These additional factors lead to a more realistic visualization of fishing-net simulations. In this paper, we propose a new mass-spring model for a fishing-net and a method to simplify the calculation equations for a real-time simulation of a fishing-net model. Our 3D mass-spring model presents a mesh-structure similar to a typical mass-spring model except that each intersection point can have different masses. The motion of each mass is calculated periodically considering additional dynamics. To reduce the calculation time, we attempt to simplify the mathematical equations that include the effect of the tidal-current and buoyancy. Through this research, we expect to achieve a real-time and realistic simulation for the fishing net.

• Journal of Digital Convergence
• /
• v.11 no.12
• /
• pp.479-485
• /
• 2013

Virtualization is a promising approach to consolidating multiple online services onto a smaller number of computing resources. A virtualized server environment allows computing resources to be shared among multiple performance isolated platforms called virtual machines. Through server virtualization software, applications servers are encapsulated into VMs, and deployed with APIs on top generalized pools of CPU and memory resources. Networking and security have been moved to a software abstraction layer that transformed computing, network virtualization. And it paves the way for enterprise to rapidly deploy networking and security for any application by creating the virtual network. Stochastic reward net (SRN) is an extension of stochastic Petri nets which provides compact modeling facilities for system analysis. In this paper, we develop SRN model of network virtualization based on virtual switch. Measures of interest such as switching delay and throughput are considered. These measures are expressed in terms of the expected values of reward rate functions for SRNs. Numerical results are obtained according to the virtual switch capacity and number of active VMs.

• International journal of advanced smart convergence
• /
• v.8 no.4
• /
• pp.75-81
• /
• 2019

Though recent advancement of deep learning methods have provided satisfactory results from large data domain, somehow yield poor performance on few-shot classification tasks. In order to train a model with strong performance, i.e. deep convolutional neural network, it depends heavily on huge dataset and the labeled classes of the dataset can be extremely humongous. The cost of human annotation and scarcity of the data among the classes have drastically limited the capability of current image classification model. On the contrary, humans are excellent in terms of learning or recognizing new unseen classes with merely small set of labeled examples. Few-shot learning aims to train a classification model with limited labeled samples to recognize new classes that have neverseen during training process. In this paper, we increase the backbone depth of the embedding network in orderto learn the variation between the intra-class. By increasing the network depth of the embedding module, we are able to achieve competitive performance due to the minimized intra-class variation.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1992.06a
• /
• pp.61-65
• /
• 1992

This paper presents a study on Neural Networks for Phoneme Recognition and performs phoneme recognition using TDNN(Time Delay Neural Network). Also, this paper proposes new training algorithm for speech recognition using neural nets that proper to large scale TDNN. Because phoneme recognition is indispensable for continuous speech recognition, this paper uses TDNN to get accurate recognition result of phoneme. And this paper proposes new training algorithm that can converge TDNN to optimal state regardless of the number of phoneme to be recognized. The result of recognition on three phoneme classes shows recognition rate of 9.1%. And this paper proves that proposed algorithm is a efficient method for high performance and reducing convergence time.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.42.3-42
• /
• 2001

A human is an expert in manipulation. We have acquired skills to perform dexterous operations based upon knowledge and experience attained over a long period of time. It is important in robotics to understand these human skills, and utilize them to bring about better robot control and operation It is hoped that the neurocontroller can be trained and organized by simply presenting human teaching data, which implicate human intention, strategy and expertise. In designing a neurocontroller, we must determine the size of neurocontroller. Improper size may not only incur difficulties in training neural nets, e.g. no convergence, but also cause instability and erratic behavior in machines. Therefore, it is necessary to determine the proper size of neurocontroller for human control transfer. In this paper, a new pruning method is developed, based on the penalty-term methods. This method makes ...

• Journal of the Institute of Convergence Signal Processing
• /
• v.4 no.4
• /
• pp.30-39
• /
• 2003

In this paper, we carried out the performance evaluation of HM-Net(Hidden Markov Network) speech recognition system for Korean speech databases. We adopted to construct acoustic models using the HM-Nets modified by HMMs(Hidden Markov Models), which are widely used as the statistical modeling methods. HM-Nets are carried out the state splitting for contextual and temporal domain by PDT-SSS(Phonetic Decision Tree-based Successive State Splitting) algorithm, which is modified the original SSS algorithm. Especially it adopted the phonetic decision tree to effectively express the context information not appear in training speech data on contextual domain state splitting. In case of temporal domain state splitting, to effectively represent information of each phoneme maintenance in the state splitting is carried out, and then the optimal model network of triphone types are constructed by in the parameter. Speech recognition was performed using the one-pass Viterbi beam search algorithm with phone-pair/word-pair grammar for phoneme/word recognition, respectively and using the multi-pass search algorithm with n-gram language models for sentence recognition. The tree-structured lexicon was used in order to decrease the number of nodes by sharing the same prefixes among words. In this paper, the performance evaluation of HM-Net speech recognition system is carried out for various recognition conditions. Through the experiments, we verified that it has very superior recognition performance compared with the previous introduced recognition system.