• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.101-107
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• 2014

With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.37-44
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• 2008

Data entered into RFID tags are used for saving costs and enhancing competitiveness in the development of applications in various industrial areas. RFID readers perform the identification and search of hundreds of objects, which are tags. RFID technology that identifies objects on request of dynamic linking and tracking is composed of application components supporting information infrastructure. Despite their many advantages, existing applications, which do not consider elements related to real.time data communication among remote RFID devices, cannot support connections among heterogeneous devices effectively. As different network devices are installed in applications separately and go through different query analysis processes, there happen the delays of monitoring or errors in data conversion. The present study implements a RFID database handling system in semantic Web environment for integrated management of information extracted from RFID tags regardless of application. Users’ RFID tags are identified by a RFID reader mounted on an application, and the data are sent to the RFID database processing system, and then the process converts the information into a semantic Web language. Data transmitted on the standardized semantic Web base are translated by a smart browser and displayed on the screen. The use of a semantic Web language enables reasoning on meaningful relations and this, in turn, makes it easy to expand the functions by adding modules.

• Journal of the Korean association of regional geographers
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• v.21 no.3
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• pp.474-488
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• 2015

Conflicts in the construction of large public facilities carried out as national projects are crucial issues we have to deal with. There are growing concerns for and oppositions to large construction projects in terms of environmental deterioration and the dissolution of local communities. In the case of projects that promise the creation of jobs and investment, the competition and disputes are increasing and being intensified. Therefore, there is a considerable amount of study on the competitions and conflicts between regions. Previous studies have focused on the procedures of public policy, governance structure, the role of local media. Contrary to the previous studies, this study investigates the spatial ways of constructing conflicts. Based on the analysis of the project of "Southeastern New International Airport", there is a mismatch between the spatial boundary of cost/benefit and agents (regions) of disputes. The agents of conflicts also show the politics of multiple scales by constructing alliances and breaking the network in the process of the airport project. The findings suggest that the conflicts on regional development should be understood as the construction of dynamic regional politics on regional development rather than as the by-product in the practice of policies.

• International Commerce and Information Review
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• v.13 no.3
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• pp.229-248
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• 2011

The increasing complexity of business and social settings bas lead to innovation becoming a strategic imperative. The need for innovation in the quest for competitive advantage also means that firms must be dynamic and flexible. This is often achieved through collaborative arrangements such as strategic alliances or strategic network Many organizations form alliances by leveraging their resources to gain access to the partner's skills and capabilities; ultimately to enhance innovation and performance. We demonstrate empirically that the "chain of innovation" is central to the process of innovation in global alliances. This chain comprises the creativity and learning processes and knowledge stock in alliances. Our empirical analysis is based on a survey of alliances that resulted in 114 responses. For management, this research bas significant potential in guiding attention to the chain of innovation, to better manage the overall process of innovation in alliances. Our work shows that more effective creativity and learning processes and a greater knowledge stock lead to a more effective alliance innovation process. Managers therefore, need to concentrate on creating environments wherein the processes of creativity and learning are fostered, increasing the alliance knowledge stock and in turn, increasing innovative output via an effective innovation process.

• The KIPS Transactions:PartC
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• v.15C no.3
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• pp.157-166
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• 2008

The ubiquitous service environment is poor in reliability of connection and also has a high probability that the intrusion against a system and the failure of the services may happen. Therefore, It is very important to guarantee that the legitimate users make use of trustable services from the viewpoint of security without discontinuance or obstacle of the services. In this paper, we point out the problems in the standard Jini service environment and analyze the Jgroup/ARM framework that has been developed in order to help fault tolerance of Jini services. In addition, we propose a secure Jini service architecture to satisfy the security, availability and quality of services on the basis of the analysis. The secure Jini service architecture we propose in this paper is able to protect a Jini system not only from faults such as network partition or server crash, but also from attacks exploiting flaws. It provides security mechanism for dynamic trust establishment among the service entities. Moreover, our secure Jini service architecture does not incur high computation costs to merge the user service states because of allocation of the replica based on each session of a user. Through the experiment on a test-bed, we have confirmed that proposed secure Jini service architecture is able to guarantee the persistence of the user service states at the level that the degradation of services quality is ignorable.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.1-16
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• 2012

In this paper, we propose a cost-effective location and service management scheme in LTE (Long Term Evolution) networks, which a per-user service proxy is created to serve as a gateway between the mobile user and all client-server applications engaged by the mobile user. The service proxy is always co-located with the mobile user's location database such that whenever the MU's location database moves during a location hand-off, a service hand-off also ensues to co-locate the service proxy with the location database. This allows the proxy to know the location of the mobile user all the time to reduce the network communication cost for service delivery. We analyze four integrated location and service management schemes. Our results show that the centralized scheme performs the best when the mobile user's SMR (service to mobility ratio) is low and ${\upsilon}$(session to mobility ratio) is high, while the fully distributed scheme performs the best when both SMR and ${\upsilon}$ are high. In all other conditions, the dynamic anchor scheme is the best except when the service context transfer cost is high under which the static anchor scheme performs the best. Through analytical results, we demonstrate that different users with vastly different mobility and service patterns should adopt different integrated location and service management methods to optimize system performance.

• Journal of the Korean Institute of Gas
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• v.2 no.1
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• pp.59-65
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• 1998

Morphology and thermal properties of polyurethane synthesized from 4,4'-diphenylmethane diisocyanate (MDI), polyester polyol, and 1,4-butane diol are investigated using fourier transform infrared spectroscopy (FT-IR), differential scanning calorimeter (DSC), and dynamic mechanical thermal analysis (DMTA). From the FT-IR study, it is found that the stretching peaks of hydrogen bonded N-H and C=O are shifted to the low frequencies with the increase of hard segment content of the polyurethanes. The shift of the stretching peaks of hydrogen bonded N-H and C=O indicates that the degree of hydrogen bonding is increased. From the DSC study, it appears that the glass transition temperature ($T_g$) of the polyurethanes is increased with the increase of the hard segment content. Also, it is found that the polyurethanes investigated in this study have the homogeneous network structure due to the high functionality of the MDI. From the DMTA study, transition of the soft segment was not found. Therefore it is concluded that the polyurethanes investigated in this study have the one-phase morphology which is consistent with the DSC results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.499-510
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• 2023

Recently, an intelligent and advanced cyber attack attacks a computer network of a public institution using a file containing malicious code or leaks information, and the damage is increasing. Even in public institutions with various information protection systems, known attacks can be detected, but unknown dynamic and encryption attacks can be detected when existing signature-based or static analysis-based malware and ransomware file detection methods are used. vulnerable to The detection method proposed in this study extracts the detection result data of the system that can detect malicious code and ransomware among the information protection systems actually used by public institutions, derives various attributes by combining them, and uses a machine learning classification algorithm. Results are derived through experiments on how the derived properties are classified and which properties have a significant effect on the classification result and accuracy improvement. In the experimental results of this paper, although it is different for each algorithm when a specific attribute is included or not, the learning with a specific attribute shows an increase in accuracy, and later detects malicious code and ransomware files and abnormal behavior in the information protection system. It is expected that it can be used for property selection when creating algorithms.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.65-76
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• 2024

With the recent activation of the offshore wind power industry, there has been a development of power plants with a scale exceeding 400MW, comparable to traditional thermal power plants. Renewable energy, characterized by intermittency depending on the energy source, is a prominent feature of modern renewable power generation facilities, which are structured based on controllable inverter technology. As the integration of renewable energy sources into the grid expands, the grid codes for power system connection are progressively becoming more defined, leading to active discussions and evaluations in this area. In this paper, we propose a method for selecting optimal reactive power compensation capacity when multiple offshore wind farms are integrated and connected through a shared interconnection facility to comply with grid codes. Based on the requirements of the grid code, we analyze the reactive power compensation and excessive stability of the 400MW wind power generation site under development in the southwest sea of Jeonbuk. This analysis involves constructing a generation site database using PSS/E (Power System Simulation for Engineering), incorporating turbine layouts and cable data. The study calculates reactive power due to charging current in internal and external network cables and determines the reactive power compensation capacity at the interconnection point. Additionally, static and dynamic stability assessments are conducted by integrating with the power system database.