• Journal of the Korea Society of Computer and Information
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• v.20 no.11
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• pp.63-68
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• 2015

In this paper, we propose a new energy efficient scheme which can prolong the life of sensor networks, it should be able to reduce the number of sensing. We use the concept of safe zone for manage the appropriate range of properties. We measure the distance between the sensed temperature value and the center of the zone, and calculate the next sensing interval based on this distance. We name our proposed scheme "VIS". To assess the performance of the proposed scheme the actual temperature data was collected using the sensor node. The algorithm was implemented through the programming and was evaluated in a variety of settings. Experimental results show that the proposed algorithm is to significantly reduce the number of sensing in terms of energy efficiency while having the ability to know the state of the sensor nodes periodically. Our VIS algorithm can be useful in applications which will require the ability of control to the temperature within a proper range.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.49-57
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• 2016

In this paper we propose the resource allocation scheme for the overlaid macro-femtocell networks, which considers the type of handovers such as the inter-macrocell, macrocell-to-femtocell, femtocell-to-macrocell, or inter-femtocell in order to guarantee Quality of Service (QoS) and expand the accommodation capacity. Our proposed scheme takes into account the movement of mobile terminals, the QoS degradation, or the load control which trigger handovers in the overlaid networks, before it allocates resources dynamically. Moreover it considers QoS requirements of realtime or non-realtime mobile multimedia services such as video communication, Video on Demand (VoD) and dataa services. Simulation results show that our scheme provides better performances than the conventional one with respect to the outage probability, data transmission throughput and handover failure rate.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.247-253
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• 2007

In this paper, downlink capacity of time duplex division (TDD) based cellular wireless networks utilizing fixed hopping stations is investigated. In the network, a number of fixed subscriber stations act as hopping transmission stations between base stations and far away subscribers, forming a cellular and ad hoc mobile network model. At the radio layer, TDD code division multiple access (CDMA) is selected as the radio interface due to high efficiency of frequency usage. In order to improve the system performance in terms of downlink capacity, we propose different time slot allocation schemes with the usage of fixed hopping stations, which can be selected by either random or distanced dependent schemes. Performance results obtained by computer simulation demonstrate the effectiveness of the proposed network to improve downlink system capacity.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.693-712
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• 2012

The paper presents three machine learning based keyphrase extraction methods that respectively use Decision Trees, Na$\ddot{i}$ve Bayes, and Artificial Neural Networks for keyphrase extraction. We consider keyphrases as being phrases that consist of one or more words and as representing the important concepts in a text document. The three machine learning based keyphrase extraction methods that we use for experimentation have been compared with a publicly available keyphrase extraction system called KEA. The experimental results show that the Neural Network based keyphrase extraction method outperforms two other keyphrase extraction methods that use the Decision Tree and Na$\ddot{i}$ve Bayes. The results also show that the Neural Network based method performs better than KEA.

• Journal of Sensor Science and Technology
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• v.19 no.5
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• pp.342-348
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• 2010

The wireless sensor networks have been extensively researched. One of the issues in wireless sensor networks is a developing energy-efficient clustering protocol. Clustering algorithm provides an effective way to extend the lifetime of a wireless sensor networks. In this paper, we proposed an energy efficient clustering scheme by adjusting group size. In sensor network, the power consumption in data transmission between sensor nodes is strongly influenced by the distance of two nodes. And cluster size, that is the number of cluster member nodes, is also effected on energy consumption. Therefore we proposed the clustering scheme for high energy efficiency of entire sensor network by controlling cluster size according to the distance between cluster header and sink.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.126-137
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• 1994

Performance management of computer networks is intended to improve a given network performance in order for more efficient information exchange between subsystems of an integrated large-scale system. Importance of perfomance management is growing as many functions of the large- scale system depend on the quality of communication services provided by the network. The role of performance management is to manipulate the adjustable protocol parameters on line so that the network can adapt itself to a dynamic environment. This can be divided into two subtasks : performance evaluation to find how changes in protocol parameters affect the network performance and decision making to determine the magnitude and direction of parameter adjustment. This paper is the first part of the two papers focusing on conceptual design, development, and evaluation of performance management for token bus networks. This paper specifically deals with the task of performance evaluation which utilizes the principle of perturbation analysis of discrete event dynamic systems. The developed algorithm can estimate the network performance under a perturbed protocol parameter setting from observations of the network operations under a nominal parameter setting.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3250-3265
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• 2014

Integrated WiMAX and WiFi networks is of great potential for the future due to the wider coverage of WiMAX and the high data transport capacity of WiFi. However, seamless and secure handover (HO) is one of the most challenging issues in this field. In this paper, we present a novel vertical HO authentication scheme with privacy preserving for WiMAX-WiFi heterogeneous networks. Our scheme uses ticket-based and pseudonym-based cryptographic methods to secure HO process and to achieve high efficiency. The formal verification by the AVISPA tool shows that the proposed scheme is secure against various malicious attacks and the simulation result indicates that it outperforms the existing schemes in terms of communication and computation cost.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.276-283
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• 2021

In this paper, we propose an effective noise reduction method for photon counting imaging using a discrete wavelet transform. Conventional 2D photon counting imaging was used to visualize the object under dark conditions using statistical methods, such as the Poisson random process. The photons in the scene were estimated using a statistical method. However, photons which disturb the visualization and decrease the image quality may occur in the background where there is no object. Although median filters are used to reduce the noise, the noise in the scene remains. To remove the noise effectively, our proposed method uses the discrete wavelet transform, which removes the noise in the scene using a specific thresholding method that utilizes photon counting imaging characteristics. We conducted an optical experiment to demonstrate the denoising performance of the proposed method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.98-101
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• 2019

At present, deep convolutional neural networks have made a very important contribution in single-image super-resolution. Through the learning of the neural networks, the features of input images are transformed and combined to establish a nonlinear mapping of low-resolution images to high-resolution images. Some previous methods are difficult to train and take up a lot of memory. In this paper, we proposed a simple and compact deep recursive residual network learning the features for single image super resolution. Global residual learning and local residual learning are used to reduce the problems of training deep neural networks. And the recursive structure controls the number of parameters to save memory. Experimental results show that the proposed method improved image qualities that occur in previous methods.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.27-32
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• 2022

The fifth generation (5G) mobile communication technology is designed to meet all communication needs. Heterogeneous networks (HetNets) are a new emerging network structure. HetNets have greater potential for radio resource reuse and better service quality than homogeneous networks since they can evolve small cells into macrocells. Effective resource allocation techniques reduce inter-user interference while optimizing the utilization of limited spectrum resources in HetNets. This article discusses resource allocation in 5G HetNets. This paper explains HetNets and how they work. Typical cell types in HetNets are summarized. Also, HetNets models are explained in the third section. The fourth component addresses radio resource control and mobility management. Moreover, future study in this subject may benefit from this article's significant insights on how HetNets function.