• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.60-68
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• 2012

In recent years, the requirements on the high quality environment monitoring by using the sensor nodes which can handle the multimedia data in WSN have been increased. However, because the volume of multimedia data is tremendous, the limited bandwidth of a wireless channel may incur the bottleneck of a system. To solve such a problem, most of the existing distributed multi-path routing protocols based on multimedia data just focused on overcoming the limited bandwidth in order to enhance the energy efficiency and the transmission rate. However, because the existing methods can not apply a key-based technique to encrypt the multimedia data, they are very weak for the security. In this paper, we propose a secure disjointed multipath routing scheme for multimedia data transmission. Since our proposed scheme divides multimedia data(eg. image) into pixels and sends them through disjointed multipath routing, it can provide security to the whole network without using the key-based method. Our experimental results show that our proposed scheme reduces about 10% the amount of the energy consumption and about 65% the amount of the missed data packets caused by malicious nodes over the existing methods on average.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.73-80
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• 2010

A wireless sensor network which is deployed in hostile environment can be easily compromised by attackers. The selective forwarding attack can jam the packet or drop a sensitive packet such as the movement of the enemy on data flow path through the compromised node. Xiao, Yu and Gao proposed the checkpoint-based multi-hop acknowledgement scheme(CHEMAS). In CHEMAS, each path node enable to be the checkpoint node according to the pre-defined probability and then can detect the area where the selective forwarding attacks is generated through the checkpoint nodes. In this scheme, the number of hops is very important because this parameter may trade off between energy conservation and detection capacity. In this paper, we used the fuzzy rule system to determine adaptive threshold value which is the number of hops for the ACK packets. In every period, the base station determines threshold value while using fuzzy logic. The energy level, the number of compromised node, and the distance to each node from base station are used to determine threshold value in fuzzy logic.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.7-15
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• 2002

This paper is concerned with remote environment monitoring & control for the breeding house as scattering far and wide. The environment data is detected in the breeding house that is collected to one processor. It's adapted to the PSTN(public switch tele-phone network) and multi-processing for exchange the environment data and the control data in between the manager and a breeding house by micro-processor. We have designed the algorithm of the communication sequence through the experimental research. This system is composed of sensor interface, FSK communications, LED display, data latch and MCS-51 single-chip. The S/W is composed with data acquisition by multi-processing, data communication and interrupt. And this paper is Proposed the DB structure algorithm concern to a mount scale using web design. The subject is a performance of effective management for the breeding house.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.319-325
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• 2015

Remarkable advances in wireless communication technology have enabled communications among people who are far away from each other. In recent, the needs of local area voice communication using a wireless system based on low-cost and simple hardware are rapidly rising. However, since these applications require that the multi-users communicate on the same wireless channel in a small area, the existing voice technologies are not suitable for directly applying to these applications. Therefore, in this paper I propose a novel idea enabling multi-user voice communication. In particular, as a short range wireless solution, I employ the IEEE 802.15.4 based on low power and low cost. However, since originally the standard is not developed for voice communication, we extend the original scheme to be suitable for the voice communication by utilizing the extended concept of GTS. The capacity and validity of the proposed scheme are evaluated through quantitative analysis in various voice compression rates.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.624-629
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• 2018

The current study was conducted to develop a portable composite gas detector allowing the detection of both $CO_2$ and $CH_4$ gases by means of the Non Dispersive Infra-Red (NDIR) method. The gas detector is configured to radiate infrared waves using infrared lamps, where the wavelength of the infrared light is reduced due to absorption throughout the chamber, and this reduction (absorption) is detected by the absorption detector, before being converted and amplified to a 3.5V~6V electrical signal, providing as accurate a measurement as possible. The conventional singe sensor method measures the relative measurement by absorbing only specified wavelengths of infrared radiation, which in the case of gas detection leads to problems with accuracy due to the lack of a reference sensor when detecting light with a wavelength of only $4.26{\mu}m$. The dual sensor employed in this study provides a comparative measurement between the reference value derived from the wavelength of $3.91{\mu}m$, which is not influenced by other gas sources, and the measurement value derived from the wavelength of $4.26{\mu}m$, in order to reduce the errors and enhance the reliability, thereby allowing low power consumption for portable devices and multi-gas detection for both $CO_2$ and $CH_4$ gases. The portable composite gas detector developed herein provides a measurement rage of 0ppm~5,000ppm for $CO_2$ gas, and 0.5%vol for $CH_4$, which allows the determination of whether the $CO_2$ and $CH_4$ contents in indoor air are less than 1,000ppm or not. The current study established that the composite gas detector can be interlinked with firefighting appliances through portable devices or home automation, and is anticipated to be very effective in fire prevention.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1540-1560
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• 2022

Latest technological innovation in the development of compact lower power radios has led to the explosion of Internet of Things. With Wi-Fi, Zigbee and other physical layer protocols offering short coverage area there was a need for a RF protocol that had a larger coverage area with low power consumption. LoRa offers Long Range with lower power consumption. LoRa offers point to point and point to multipoint connections. with Single hop communication in place the need for routing protocols are eliminated. LoRa Wide Area Network stack can accommodate thousands of nodes under a single LoRa gateway with a single hop communication between the end nodes and LoRaWAN gateway. This paper takes an experimental approach to analyze the basic physical layer parameters of LoRa and the practical coverage offered by a LoRaWAN under highly dense urban conditions with variable topography. The insights gained from the practical deployment of the LoRaWAN network, and the subsequent performance analysis is used to design a novel public utility monitoring platform. The second half of the papers is designing a robust platform to integrate both existing wired sensor water meters, current and future generation wireless water meters. The Common Automated Metering Platform is designed to integrate both wired sensors and wireless (LoRaWAN and Wi-Fi) supported water meters. This integrated platform reduces the number of nodes under each LoRaWAN gateway and thus improves the scalability of the network. This architecture is currently designed to accommodate one utility application but can be modified to integrate multi-utility applications.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.205-214
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• 2015

In this study, a novel land-cover classification framework for multi-temporal SAR data is presented that can combine multiple features extracted through data transforms and multiple classifiers. At first, data transforms using principle component analysis (PCA) and 3D wavelet transform are applied to multi-temporal SAR dataset for extracting new features which were different from original dataset. Then, three different classifiers including maximum likelihood classifier (MLC), neural network (NN) and support vector machine (SVM) are applied to three different dataset including data transform based features and original backscattering coefficients, and as a result, the diverse preliminary classification results are generated. These results are combined via a majority voting rule to generate a final classification result. From an experiment with a multi-temporal ENVISAT ASAR dataset, every preliminary classification result showed very different classification accuracy according to the used feature and classifier. The final classification result combining nine preliminary classification results showed the best classification accuracy because each preliminary classification result provided complementary information on land-covers. The improvement of classification accuracy in this study was mainly attributed to the diversity from combining not only different features based on data transforms, but also different classifiers. Therefore, the land-cover classification framework presented in this study would be effectively applied to the classification of multi-temporal SAR data and also be extended to multi-sensor remote sensing data fusion.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.94-104
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• 2000

The accuracy and reliability of the target tracking is very critical issue in the design of automotive collision warning radar A significant problem in multi-target tracking (MTT) is the target-to-measurement data association If an incorrect measurement is associated with a target, the target could diverge the track and be prematurely terminated or cause other targets to also diverge the track. Most methods for target-to-measurement data association tend to coalesce neighboring targets Therefore, many algorithms have been developed to solve this data association problem. In this paper, a new multi-target data association method based on order statistics is described The new approaches. called the order statistics probabilistic data association (OSPDA) and the order statistics joint probabilistic data association (OSJPDA), are formulated using the association probabilities of the probabilistic data association (PDA) and the joint probabilistic data association (JPDA) filters, respectively Using the decision logic. an optimal or near optimal target-to-measurement data association is made A computer simulation of the proposed method in a heavy cluttered condition is given, including a comparison With the nearest-neighbor CNN). the PDA, and the JPDA filters, Simulation results show that the performances of the OSPDA filter and the OSJPDA filter are superior to those of the PDA filter and the JPDA filter in terms of tracking accuracy about 18% and 19%, respectively In addition, the proposed method is implemented using a developed digital signal processing (DSP) board which can be interfaced with the engine control unit (ECU) of car engine and with the d?xer through the controller area network (CAN)

• Journal of Internet Computing and Services
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• v.11 no.4
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• pp.11-22
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• 2010

In case that group communication protocols assume every process is interested in all events occurring in a large scale group, the events multicasting to a subset of a large process group, such as a sensor network, potentially varying for every event based on their interests might lead to very high communication overhead on each individual process. Moreover, despite the importance of both guaranteeing message delivery order and supporting overlapped group using gossip based group communication for multicasting in sensor or P2P networks, there exist little research works on development of gossip-based protocols to satisfy all these requirements. In this paper, we present a new gossip-based causal message order guaranteeing multicast protocol based on local views and delegates representing subgroups and fully utilizing multi-group features to improve scalability. In the proposed protocol, the message delivery order in overlapped groups has been guaranteed consistently by all corresponding members of the groups including delegates. Therefore, these features of the proposed protocol might be significantly scalable rather than those of the protocols guaranteeing atomic order dependencies between multicast messages by hierarchical membership list of dedicated groups like traditional committee protocols and much stronger rather than fully decentralized protocols guaranteeing dependencies between multicast messages based on only local views. And the proposed protocol is a hybrid approach improving the inherent scalability of multicast nature by gossip-based technique in all communications.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.