• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2491-2499
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• 2015

Recently, the most popular technique to determine the Genotype, genetic features of individual organisms, is the GBS based on SNP from sequences determined by NGS. As analyzing the sequences by the GBS, TASSEL is the most used program to identify the genotypes. But, TASSEL has limitation that it uses only the partial sequences that is obtained by NGS. We tried to improve the efficiency in use of the sequences in order to solve the limitation. So, we constructed new data sets by quality checking, filtering the unused sequences with error rate below 0.1% and clipping the sequences considering the location of barcode and enzyme. As a result, approximately over 17% of the SNP detection efficiency was increased. In this paper, we suggest the method and the applied programs in order to detect more SNPs by using the disused sequences.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.11
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• pp.1170-1181
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• 2012

Wireless Sensor Networks(WSNs) are used in diverse applications. In general, sensor nodes that are easily deployed on specific areas have many resource constrains such as battery power, memory sizes, MCUs, RFs and so on. Hence, first of all, the efficient energy consumption is strongly required in WSNs. In terms of event states, event-driven deliverly model (i.e. surveillance and reconnaissance applications) has several characteristics. On the basis of such a model, clustering algorithms can be mostly used to manage sensor nodes' energy efficiently owing to the advantages of data aggregations. Since a specific node collects packets from its child nodes in a network topology and aggregates them into one packet to relay them once, amount of transmitted packets to a sink node can be reduced. However, most clustering algorithms have been designed without considering can be reduced. However, most clustering algorithms have been designed without considering characteristics of event-driven deliverly model, which results in some problems. In this paper, we propose enhanced clustering algorithms regarding with both targets' movement and energy efficiency in order for applications of surveillance and reconnaissance. These algorithms form some clusters to contend locally between nodes, which have already detected certain targets, by using a method which called CHEW (Cluster Head Election Window). Therefore, our proposed algorithms enable to reduce not only the cost of cluster maintenance, but also energy consumption. In conclusion, we analyze traces of the clusters' movements according to targets' locations, evaluate the traces' results and we compare our algorithms with others through simulations. Finally, we verify our algorithms use power energy efficiently.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12A
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• pp.1225-1232
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• 2008

In this paper, we describe a compensation method of diurnal effect which is one of the factors giving large effect on the performance when using ground-wave signals like Loran-C for a backup and substitute navigation system of global satellite navigation system such as GPS, and currently many researches of the topics are doing in USA and in Europe. In order to compensate diurnal effect, we find periodic frequency components by using the Least Square Spectral Analysis (LSSA) method at first and then compensate the effect by subtracting the estimated compensation signal, obtained by using the estimated amplitude and phase of the individual frequency component, from the original signal. In this paper, we propose a simple compensation algorithm and analysis the performance through simulations. From the results, it is observed that the amplitude and phase can be estimated with under 5 % and 0.17 % in a somewhat poor receiving situation with 0 dB Signal to Noise Ratio (SNR). Also, we analyze the obtainable performance improvement after compensation by using the measured Loran-C data. From the results, it is observed that we can get about 22 % performance improvement when a moving average with 5 minutes interval is employed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.15-23
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• 2017

The person Re-identification is the most challenging part of computer vision due to the significant changes in human pose and background clutter with occlusions. The picture from non-overlapping cameras enhance the difficulty to distinguish some person from the other. To reach a better performance match, most methods use feature selection and distance metrics separately to get discriminative representations and proper distance to describe the similarity between person and kind of ignoring some significant features. This situation has encouraged us to consider a novel method to deal with this problem. In this paper, we proposed an enhanced recurrent neural network with three-tier hierarchical network for person re-identification. Specifically, the proposed recurrent neural network (RNN) model contain an iterative expectation maximum (EM) algorithm and three-tier Hierarchical network to jointly learn both the discriminative features and metrics distance. The iterative EM algorithm can fully use of the feature extraction ability of convolutional neural network (CNN) which is in series before the RNN. By unsupervised learning, the EM framework can change the labels of the patches and train larger datasets. Through the three-tier hierarchical network, the convolutional neural network, recurrent network and pooling layer can jointly be a feature extractor to better train the network. The experimental result shows that comparing with other researchers' approaches in this field, this method also can get a competitive accuracy. The influence of different component of this method will be analyzed and evaluated in the future research.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.165-172
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• 2013

Convergence is increasingly prevalent in the IT world which generally refers to the combination of two or more different technologies in a single device. Especially, the spectrum scarcity is becoming a big issue because there are exponential growth of broadcasting and communication systems in the spectrum demand. Cognitive radio (CR) is a convergence technology that is envisaged to solve the problems in wireless networks resulting from the limited available spectrum and the inefficiency in the spectrum usage by exploiting the existing wireless spectrum opportunistically. However, the very process of convergence is likely to expose significant security issues due to the merging of what have been separate services and technologies and also as a result of the introduction of new technologies. The main purpose of this research is focused on devising an adaptive security framework based on carousel for CR networks as a distinct telecommunication convergence application, which are still at the stage of being developed and standardized with the lack of security concerns. The framework uses a secure credential, named as carousel, initialized with the location related information from objects position, which is used to design security mechanisms for supporting privacy and various securities based on it. The proposed adaptive security framework could be used as a security building block for the CR network standards and various convergence applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12B
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• pp.1022-1036
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• 2004

In mobile cellular network the ever-changing location of a mobile host necessitates the continuous tracking of its current position and efficient management of location information. A database called Home Location Register(HLR) plays a major role in location management in this distributed environment, providing table management, index management, and backup management facilities. The objectives of this paper are to identify the p개blems of the current HLR system through rigorous analysis, to suggest solutions to them, and to propose a new architecture for the HLR system. In the HLR system, a main memory database system is used to provide real-time accesses and updates of subscriber's information. Thus it is suggested that the improvement bemade to support better real-time facilities, to manage subscriber's information more reliably, and to accommodate more subscribers. In this paper, I propose an efficient backup method that takes into account the characteristics of HLR database transactions. The retrieval speed and the memory usage of the two-level index method are better than those of the T-tree index method. Insertion md deletion overhead of the chained bucket hashing method is less than that of modified linear hashing method. In the proposed backup method, I use two kinds of dirty flags in order to solve the performance degradation problem caused by frequent registration-location operations. Performance analysis has been performed to evaluate the proposed techniques based on a system with subscribers. The results show that, in comparison with the current techniques, the memory requirement is reduced by more than 62%,directory operations, and backup operation by more than 80%.

• Korean Journal of Construction Engineering and Management
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• v.17 no.4
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• pp.49-56
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• 2016

Recent research has been ongoing for modular buildings in the country and interest increases. However, the activation of modular building projects is obstructed in the construction industry. There are many reasons to identity for this obstruction but one issue should be focussed. Modular buildings require to change the existing construction production system to a new construction production system, which is factory production - transportation - erection. However, the existing project delivery system in the public sector could not be adapted for this new construction production system due to the obligation of multi prime contract use, such as electrical, communication, fire fighting contracts by Law. Therefore, modular buildings in the existing project delivery system are separately contracted by multi prime contracts and modular units composed of the buildings are contracted by an architectural prime contractor as a commodity. As results, construction costs are increased, potential quality problems are raised and the existing project delivery system is finally an obstacle not to maximize benefits of the modular buildings. In this paper, we propose a new project delivery system for the modular buildings to adapt then ew construction production system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2714-2726
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• 1997

In this paper, adaptive symbol changes-based medical image compression method is presented. First, the differenctial image domain is obtained using the differentiation rules or obaptive predictors applied to original mdeical image. Also, the algorithm determines the context associated with the differential image from the domain. Then prediction symbols which are thought tobe the most probable differential image values are maintained at a high value through the adaptive symbol changes procedure based on estimates of the symbols with polarity coincidence between the differential image values to be coded under to context and differential image values in the model template. At the coding step, the differential image values are encoded as "predicted" or "non-predicted" by the binary adaptive arithmetic encoder, where a binary decision tree is employed. The simlation results indicate that the prediction hit ratios of differential image values using the proposed algorithm improve the coding gain by 25% and 23% than arithmetic coder with ISO JPEG lossless predictor and arithmetic coder with differentiation rules or adaptive predictors, respectively. It can be used in compression part of medical PACS because the proposed method allows the encoder be directly applied to the full bit-planes medical image without a decomposition of the full bit-plane into a series of binary bit-planes as well as lower complexity of encoder through using an additions when sub-dividing recursively unit intervals.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.370-376
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• 2020

In this study, we consider a group-based random access method for group connection and delivery by grouping devices when H2H devices and large-scale M2M devices coexist in a cell in NB-IoT environment. H2H devices perform individual random access, but M2M devices are grouped according to a NPRACH transmission period, and a leader of each group performs random access. The preamble is allocated using the variable preamble allocation algorithm of the Disjoint Allocation(DA) method. The proposed preamble allocation algorithm is an algorithm that preferentially allocates preambles that maximizes throughput of H2H to H2H devices and allocates the rest to M2M devices. The access distribution of H2H and M2M devices was set as Poisson distribution and Beta distribution, respectively, and throughput, collision probability and resource utilization were analyzed. As the random access transmission slot is repeated, the proposed preamble allocation algorithm decreases the collision probability from 0.93 to 0.83 and 0.79 when the number M2M device groups are 150. In addition, it was found that the amount of increase decreased to 33.7[%], 44.9[%], and 48.6[%] of resource used.

• Smart Media Journal
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• v.6 no.2
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• pp.42-49
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• 2017

It is important to realize automation services by communicating in IoT with humans, objects & objects, and forming a common network. People used web like the most powerful network way to sharing things and communication. Therefore the efficiency method communication between each device and the web in IoT could be different from ones. The best method for high quality software product in web applications is software reuse ; Modules, classes, patterns, frameworks, and business components are reusable elements of various perspectives. Components is plugged with others through well-defined interfaces, which can overcome the operation and complexity of application development. A web-based distributed environment for IoT applications is a standard architecture use information collected from various devices for developing and using applications. For that reason, the network management which manages the constituent resources for the best service control in IoT application is required as a sub-layer support service in most applications as well as individual applications. In this paper, we measure to develop a network management system based not only by components but on heterogeneous internetworks. For procedure this, we clarify a component architecture for classifying and classify also the component needed in the IOT and network domain or order the type of real network management system.