• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1384-1390
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• 2008

The TCP protocol is originally designed for wired network, however it performs very poor in wireless network due to different nature of wireless network from wired networks. In terms of TCP performance improvement in wireless Ad-hoc network, many researches show that small congestion window size of TCP connection can improve TCP performance. We propose a new TCP algorithm to improve TCP performance in wireless Ad-hoc network. The basic idea of our approach is that TCP receiver estimates the optimum window size and then sets congestion window limit of TCP sender to an optimum value by using the advertised window field in TCP ACK packet. From extensive computer simulation, the proposed algorithm shows superior performance than traditional TCP protocols in terms of packet delivery ratio and packet loss.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.927-934
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• 2019

Recently, mobile devices have evolved into small computers with various functions according to user requirements. Careful attention must be paid to the design of the power supply network for the stable operation of the application processor (AP), the wireless communication modem, the high performance camera, and the various interfaces of the mobile device to implement various functions of the mobile device. In this paper, we analyzed and verified the method of optimizing the design parameters such as the position, capacity, and number of decoupling capacitors to meet the target impedance required by the driver IC chip to ensure the stability of the power supply network of mobile devices that should be designed as wiring type due to mounting density limitation. The proposed wired power supply network design method can be applied to various applications including high-speed signal transmission line in addition to mobile applications.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.901-906
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• 2019

UAV (Unmanned Aerial Vehicle) is widely used in various areas such as civil and military applications including entertainment industries. Among them, UAV based communication system is also one of the important application areas. Relays have been received much attention in communication system due to its benefits of performance enhancement and coverage extension. In this paper, we investigate UAVs as relays especially focusing on physical layer. First, we introduce the research on UAV application for the relays, then the basic performance of relay networks in dual-hop communication system is analyzed by adopting decode-and-forward (DF) relaying protocol. The performance is represented using symbol error rate (SER) and UAV channels are applied by assuming asymmetric environments. Based on the performance analysis, we discuss performance enhancement issues by considering physical layer.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.5
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• pp.329-339
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• 2019

Recently, the advancement of information and communication technology(ICT) is expanding the connectivity through Internet of Things(IoT), and the media of connection is also expanding from wire/cable transmission to broadband wireless communication, which has significantly improved mobility. This hyperconnectivity has become a key element of the fourth industrial revolution, whereas the supervisory control network of purification plants in korea is operated as a communication network separated from the outside, thereby lagging in terms of connectivity. This is considered the best way to ensure security, and thus there is hardly any consideration of establishing alternatives to operate an efficient and stable communication network. Moreover, security for management of a commercialized communication network and network management solution may be accompanied by immense costs, making it more difficult to make new attempts. Therefore, to improve the conditions for the current supervisory control network of purification plants, this study developed a industrial security L2 switch that supports modbus TCP(Transmission Control Protocol) communication and encryption function of the transmission section. As a result, the communication security performance improved significantly, and the cost for implementing the network management system using Historical Trend and information of HMI(Human Machine Interface) could be reduced by approximately KRW 200 million. The results of this study may be applied to systems for gas, electricity and social safety nets that are infrastructure communication networks that are similar to purification plants.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.9
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• pp.373-378
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• 2019

Since many programming sources are open online, problems with reckless plagiarism and copyrights are occurring. Among them, source codes produced by repeated authors may have unique fingerprints due to their programming characteristics. This paper identifies each author by learning from a Google Code Jam program source using deep neural network. In this case, the original creator's source is to be vectored using a pre-processing instrument such as predictive-based vector or frequency-based approach, TF-IDF, etc. and to identify the original program source by learning by using a deep neural network. In addition a language-independent learning system was constructed using a pre-processing machine and compared with other existing learning methods. Among them, models using TF-IDF and in-depth neural networks were found to perform better than those using other pre-processing or other learning methods.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.595-618
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• 2010

This paper describes the application of a wireless sensor network to a 31 meter-tall medieval tower located in the city of Trento, Italy. The effort is motivated by preservation of the integrity of a set of frescoes decorating the room on the second floor, representing one of most important International Gothic artworks in Europe. The specific application demanded development of customized hardware and software. The wireless module selected as the core platform allows reliable wireless communication at low cost with a long service life. Sensors include accelerometers, deformation gauges, and thermometers. A multi-hop data collection protocol was applied in the software to improve the system's flexibility and scalability. The system has been operating since September 2008, and in recent months the data loss ratio was estimated as less than 0.01%. The data acquired so far are in agreement with the prediction resulting a priori from the 3-dimensional FEM. Based on these data a Bayesian updating procedure is employed to real-time estimate the probability of abnormal condition states. This first period of operation demonstrated the stability and reliability of the system, and its ability to recognize any possible occurrence of abnormal conditions that could jeopardize the integrity of the frescos.

• KSCI Review
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• v.14 no.1
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• pp.265-271
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• 2006

In this paper, we propose a new automatic fingerprint identification system that identifies individuals in large databases. The algorithm consists of three steps: preprocessing, classification, and matching, in the classification, we present a new classification technique based on the statistical approach for directional image distribution. In matching, we also describe improved minutiae candidate pair extraction algorithm that is faster and more accurate than existing algorithm. In matching stage, we extract fingerprint minutiaes from its thinned image for accuracy, and introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection in comparison stage of two fingerprints quickly. This algorithm is invariant to translation and rotation of fingerprint. The proposed system was tested on 1000 fingerprint images from the semiconductor chip style scanner. Experimental results reveal false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.1020-1033
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• 2021

Nowadays, online or mobile social network services (SNS) are very popular and widely spread in our society and daily lives to instantly share, disseminate, and search information. In particular, SNS such as YouTube, Flickr, Facebook, and Amazon allow users to upload billions of images or videos and also provide a number of multimedia information to users. Information retrieval in multimedia-rich SNS is very useful but challenging task. Content-based media retrieval (CBMR) is the process of obtaining the relevant image or video objects for a given query from a collection of information sources. However, CBMR suffers from the dimensionality curse due to inherent high dimensionality features of media data. This paper investigates the effectiveness of the kernel trick in CBMR, specifically, the kernel principal component analysis (KPCA) for dimensionality reduction. KPCA is a nonlinear extension of linear principal component analysis (LPCA) to discovering nonlinear embeddings using the kernel trick. The fundamental idea of KPCA is mapping the input data into a highdimensional feature space through a nonlinear kernel function and then computing the principal components on that mapped space. This paper investigates the potential of KPCA in CBMR for feature extraction or dimensionality reduction. Using the Gaussian kernel in our experiments, we compute the principal components of an image dataset in the transformed space and then we use them as new feature dimensions for the image dataset. Moreover, KPCA can be applied to other many domains including CBMR, where LPCA has been used to extract features and where the nonlinear extension would be effective. Our results from extensive experiments demonstrate that the potential of KPCA is very encouraging compared with LPCA in CBMR.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.71-77
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• 2021

Recently, there is a demand for efficient program development of an IoT application support frameworks considering heterogeneous hardware characteristics. In addition, the scope of hardware support is expanding with the development of neuromorphic architecture that mimics the human brain to learn on their own and enables autonomous computing. However, most existing IoT IDE(Integrated Development Environment), it is difficult to support AI(Artificial Intelligence) or to support services combined with various hardware such as neuromorphic architectures. In this paper, we design an AI component abstract model that supports the second-generation ANN(Artificial Neural Network) and the third-generation SNN(Spiking Neural Network), and implemented an autonomous IoT IDE based on the proposed model. IoT developers can automatically create AI components through the proposed technique without knowledge of AI and SNN. The proposed technique is flexible in code conversion according to runtime, so development productivity is high. Through experimentation of the proposed method, it was confirmed that the conversion delay time due to the VCL(Virtual Component Layer) may occur, but the difference is not significant.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.10
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• pp.269-276
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• 2021

Recently, smart sensors are used in various environments, and the implementation of ad-hoc sensor networks (ASNs) is a hot research topic. Unfortunately, traditional sensor network routing algorithms focus on specific control issues, and they can't be directly applied to the ASN operation. In this paper, we propose a new routing protocol by using the Q-learning technology, Main challenge of proposed approach is to extend the life of ASNs through efficient energy allocation while obtaining the balanced system performance. The proposed method enhances the Q-learning effect by considering various environmental factors. When a transmission fails, node penalty is accumulated to increase the successful communication probability. Especially, each node stores the Q value of the adjacent node in its own Q table. Every time a data transfer is executed, the Q values are updated and accumulated to learn to select the optimal routing route. Simulation results confirm that the proposed method can choose an energy-efficient routing path, and gets an excellent network performance compared with the existing ASN routing protocols.