• Proceedings of the Korean Information Science Society Conference
• /
• 2007.10d
• /
• pp.240-243
• /
• 2007

Geographic routing has been considered as an efficient simple, and scalable routing protocol for wireless sensor networks since it exploits pure location information instead of global topology information to route data packets. Geographic routing requires the sources nodes to be aware of the location of the sinks. In this paper, we propose a scheme named Sink Location Service for geographic routing in wireless Sensor Networks, in which the source nodes can get and update the location of sinks with low overhead. In this scheme, a source and a sink send data announcement and query messages along two paths respectively by geographic routing. The node located on the crossing point of the two paths informs the source about the location of the sink. Then the source can send data packet to the sink by geographic routing. How to guarantee that these two paths have at least one crossing point in any irregular profile of sensor network is the challenge of this paper.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.12
• /
• pp.2800-2807
• /
• 2012

An ad-hoc wireless network provides self-organizing data networking while they are routing of packets among themselves. Typically multi-hop and control packets overhead affects the change of route of transmission. There are numerous routing protocols have been developed for ad hoc wireless networks as the size of the network scale. Hence the scalable routing protocol would be needed for energy efficient various network routing environment conditions. The number of depth or layer of hierarchical clustering nodes are analyzed the different clustering structure with topology in this paper. To estimate the energy efficient number of cluster layer and energy dissipation are studied based on distributed homogeneous spatial Poisson process with context-awareness nodes condition. The simulation results show that CACHE-R could be conserved the energy of node under the setting the optimal layer given parameters.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.49 no.2
• /
• pp.1-6
• /
• 2012

In recent years global climate change of hurricanes and torrential rains are going to significantly, that increase damages to property and human life. The disasters have been several claimed in every field. In future, climate changes blowing are keen to strike released to the world like in several movies. Reducing the damage of long-term weather phenomena are emerging with predicting changes in weather. In this study, it is shown how to predict the red tide phenomenon with multiple linear regression analysis and artificial neural network techniques. The red tide phenomenon causing risk could be reduced by filtering sensor data which are transmitted and forecasted in real time. It could be ubiquitous driven custom marine information service system, and forecasting techniques to use throughout the meteorological disasters to minimize damage.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.1
• /
• pp.20-26
• /
• 2008

As they have more and more intelligence robots or computers these days, so the interaction between intelligence robot(computer) - human is getting more and more important also the emotion recognition and expression are indispensable for interaction between intelligence robot(computer) - human. In this paper, firstly we extract emotional features at speech signal and facial image. Secondly we apply both BL(Bayesian Learning) and PCA(Principal Component Analysis), lastly we classify five emotions patterns(normal, happy, anger, surprise and sad) also, we experiment with decision fusion and feature fusion to enhance emotion recognition rate. The decision fusion method experiment on emotion recognition that result values of each recognition system apply Fuzzy membership function and the feature fusion method selects superior features through SFS(Sequential Forward Selection) method and superior features are applied to Neural Networks based on MLP(Multi Layer Perceptron) for classifying five emotions patterns. and recognized result apply to 2D facial shape for express emotion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2016.05a
• /
• pp.638-640
• /
• 2016

Recently, Humanity enter the super-connection generation that linking human and things as a result of the development ICT technologies. IoT technology is growing rapidly as a result of IoT technology appearance and development of smart device, technology expansion, the spread of smart sensors, spread diffusion of smart devices, construction of a variety of network. These techniques are applied to those having a mobility is growing importance of network technology. Real-time service and features, such as the accuracy of the data it became important. In order to implement the IoT will need to take into account IP, security, a lot of things such as a service model, but in this paper, want to discuss mobility, for the tracking technology of routing path for efficient service delivery of the host. Therefore, in this paper, the routing path that is currently study examined the tracking technology, we try to refer to routing method of the future of the mobile host.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.4
• /
• pp.797-802
• /
• 2020

Over the past few years, smart devices, including smartphones, have been continuously required by users based on portability. The performance is improving. Ubiquitous computing environment and sensor network are also improved. Due to various network connection technologies, mobile terminals are widely used. Smart terminals need technology to make energy monitoring more detailed for more stable operation during use. The smart terminal which is light in small size generates the power shortage problem due to the various multimedia task among the terminal operation. Various estimation hardwares have been developed to prevent such situation in advance and to operate stable terminals. However, the method and performance of estimating the remaining amount are not relatively good. In this paper, we propose a method for estimating the remaining amount of smart terminals. The Capacity Estimation of lithium ion cells for stable operation was estimated based on machine learning. Learning the characteristics of lithium ion cells in use, not the existing hardware estimation method, through a map learning algorithm using machine learning technique The optimized results are estimated and applied.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.11
• /
• pp.1177-1184
• /
• 2014

An wired ship area network has functionality of remote control and autonomous management of various sensors and instruments embedded or boarded in a ship. For such environment, the DiffServ (Differentiated Services) realizes that the high-speed real-time flow with the higher priority has the guaranteed minimum data rate and is delivered faster. As a result of this DiffServ effect, the intelligent Ship Area Networks can be implemented. In this paper, an packet drop technique is proposed to outperform the previous RIO (RED In and Out) drop mechanism for DiffServ in ship area networks. the proposed packet drop technique does not manage the individual flows and divides them into several flow groups according to a criterion. And it guarantees the fairness between individual flows in the same QoS class through the group-based control. In simulation results of the proposed packet drop technique, the link utilization decreases than RIO. But it guarantees more data rates to DiffServ flows passing multiple bottleneck links.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.10
• /
• pp.1485-1490
• /
• 2013

The demonstration project of the electrical grid for Smart grid is progressed, the smart digital appliances AV technology, Smart home energy management technology charging the management function of complex energy for the automation management of air conditioning and heating, humidity and air, the health care technology charging the design of housing for the elderly and disabled and the measurement of individual bio information, and the Smart home security technology dealing with the biometric security and motion sensors, etc. have been studied. The power monitoring terminal which uses a variety of wired and wireless networks and protocol is the target additionally to be considered in addition to the security vulnerabilities that was occurred in the existing terminal. In this research paper, the author analyzes the cryptographic techniques corresponding to the smart meter occurred by the problems that are exposed on the outside which are vulnerable to physical attacks, and intends to propose the design of the security systems for the Smart meter terminal being able to maximize the efficiency of the terminal.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.9 no.1
• /
• pp.9-14
• /
• 2016

Recently the number of the elderly who live alone are increasing more and more as the average life span is prolonged. The elderly are probably in danger at home without being helped due to external aggressions or sudden health problems. Accordingly, more and more interests are taken in medical welfare for the healthy life of the seniors. In this paper, we have developed a mobility and vitality signal monitoring system based on ZigBee-PSTN gateway for the elderly. This combination of ZigBee wireless sensor network and PSTN can be easily established even in the poor internet infrastructure as is usually common for the elderly, with the advantage of providing non-constrained monitoring feature. The research result can be extended to the future tele-medicine system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.3
• /
• pp.418-424
• /
• 2018

Detection and classification of underwater targets is an important issue for both military and non-military purposes. Recently, many performance improvements are being reported in the field of pattern recognition with the development of deep learning technology. Among the results, DBN showed good performance when used for pre-training of DNN. In this paper, DBN was used for the classification of underwater targets using active sonar, and the results are compared with that of the conventional BPNN. We synthesized active sonar target signals using 3-dimensional highlight model. Then, features were extracted based on FrFT. In the single aspect based experiment, the classification result using DBN was improved about 3.83% compared with the BPNN. In the case of multi-aspect based experiment, a performance of 95% or more is obtained when the number of observation sequence exceeds three.