• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.37-47
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• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.11-20
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• 2019

Numerous enterprises, organizations and individual users are exposed to large DDoS (Distributed Denial of Service) attacks. DDoS attacks are performed through a BotNet, which is composed of a number of computers infected with a malware, e.g., zombie PCs and a special computer that controls the zombie PCs within a hierarchical chain of a command system. In order to detect a malware, a malware detection software or a vaccine program must identify the malware signature through an in-depth analysis, and these signatures need to be updated in priori. This is time consuming and costly. In this paper, we propose a botnet detection scheme that does not require a periodic signature update using an artificial neural network model. The proposed scheme exploits Word2Vec and accelerated hierarchical density-based clustering. Botnet detection performance of the proposed method was evaluated using the CTU-13 dataset. The experimental result shows that the detection rate is 99.9%, which outperforms the conventional method.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.72-78
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• 2017

Prior art search is a core process of technology management performed by inventors and applicants, patent examiners, and employees in the patent industry. As a result of insufficient academic research on a systematic prior art search methodology, the process has been often carried out depending on the subjective judgment of researchers. Previous studies on exploring prior arts based on semantics have also have the risk of underestimating the similarity of major prior arts due to the nature of patent documents where the same technical ideas are expressed in various terms. In this study, we propose an effective prior art search methodology based on hierarchical citation analysis, which provides a clear criterion for selecting core prior arts by calculating weights according to the relative importance of the collected patents. In order to verify the feasibility of the proposed methodology, a case study was conducted to explore the core prior art of one patent in the display field. As a result, 10 core prior art candidates were selected out of the 206 precedent patents.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.123-133
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• 2007

This study analyzed whether a transit network with hierarchy is efficient or not, and if transit network hierarchy has cost efficiency, then which condition guarantees the efficiency of the transit network hierarchy. The authors modeled the total cost of the transit network and suggested the conditions in which the transit network hierarchy has cost efficiency through comparing the cost of the transit network with and without hierarchy. The efficiency of transit network hierarchy is guaranteed when the travel cost savings induced by using a higher hierarchy transit network is larger than the increasing non-travel cost, which is the sum of access cost, waiting cost, and operating cost, induced by the introduction of a higher hierarchy transit network. This result is consistent with common sense and with the concept of cost and benefit analysis. If a passenger traveling within the area divided by a higher hierarchy transit network uses only a lower hierarchy transit network and the passenger traveling out of the area divided by the higher hierarchy transit network uses both lower and higher hierarchy transit networks, the travel demand using the higher hierarchy transit network is inversely proportional to the square of the line spacing. This means that the transit network becomes more efficient and small increases of travel demand guarantee the efficiency of the transit network hierarchy as the connectivity of the network becomes higher. This result shows that transit networks have economies of aggregation. This study is the first analytical research on transit network hierarchy and is expected to be a basis for numerical research. However, numerical research should complement this study, since analytical research has some limitations for considering a real network.

• Journal of the Korean Institute of Gas
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• v.21 no.4
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• pp.47-61
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• 2017

The preconditions of the usefulness of an operator safety training model in large plants are the versatility and accuracy of operational procedures, obtained by detailed analysis of the various types of risks associated with the operation, and the systematic representation of knowledge. In this study, we consider the artificial intelligence planning method for the generation of operation procedures; classify them into general actions, actions and technical terms of the operator; and take into account the sharing and reuse of knowledge, defining a knowledge expression ontology. In order to expand and extend the general operations of the operation, we apply a Hierarchical Task Network (HTN). Actual boiler plant case studies are classified according to operating conditions, states and operating objectives between the units, and general emergency shutdown procedures are created to confirm the applicability of the proposed method. These results based on systematic knowledge representation can be easily applied to general plant operation procedures and operator safety training scenarios and will be used for automatic generation of safety training scenarios.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.3
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• pp.157-168
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• 2014

From a complex systems perspective, ecohydrological systems in forests may be characterized with (1) large networks of components which give rise to complex collective behaviors, (2) sophisticated information processing, and (3) adaptation through self-organization and learning processes. In order to demonstrate such characteristics, we applied the recently proposed 'process networks' approach to a temperate deciduous forest in Gwangneung National Arboretum in Korea. The process network analysis clearly delineated the forest ecohydrological systems as the hierarchical networks of information flows and feedback loops with various time scales among different variables. Several subsystems were identified such as synoptic subsystem (SS), atmospheric boundary layer subsystem (ABLS), biophysical subsystem (BPS), and biophysicochemical subsystem (BPCS). These subsystems were assembled/disassembled through the couplings/decouplings of feedback loops to form/deform newly aggregated subsystems (e.g., regional subsystem) - an evidence for self-organizing processes of a complex system. Our results imply that, despite natural and human disturbances, ecosystems grow and develop through self-organization while maintaining dynamic equilibrium, thereby continuously adapting to environmental changes. Ecosystem integrity is preserved when the system's self-organizing processes are preserved, something that happens naturally if we maintain the context for self-organization. From this perspective, the process networks approach makes sense.

• The KIPS Transactions:PartC
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• v.16C no.3
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• pp.285-298
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• 2009

According to the development of ubiquitous technologies, sensor networks is used in various area. In particular, medical field is one of the significant application areas using sensor networks, and recently it has come to be more important according to standardization of the body sensor networks technology. There are special characteristics of their own for medical sensor networks, which are different from the one of sensor networks for general application or environment. In this paper, we propose a hierarchical medical sensor networks structure considering own properties of medical applications, and also introduce transmission mechanism based on hierarchical structure. Our mechanism uses the priority and threshold value for medical sensor nodes considering patient's needs and health condition. Through this way Cluster head can transmit emergency data to the Base station rapidly. We also present the new key establishment mechanism based on key management mechanism which is proposed by L. Eschenauer and V. Gligor for our proposed structure and transmission mechanism. We use key provisioning for emergency nodes that have high priority based on patients' health condition. This mechanism guarantees the emergency nodes to establish the key and transmit the urgent message to the new cluster head more rapidly through preparing key establishment with key provisioning. We analyze the efficiency of our mechanism through comparing the amount of traffic and energy consumption with analysis and simulation with QualNet simulator. We also implemented our key management mechanism on TmoteSKY sensor board using TinyOS 2.0 and through this experiments we proved that the new mechanism could be actually utilized in network design.

• Journal of KIISE:Databases
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• v.37 no.3
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• pp.127-136
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• 2010

With rapid growth of information and computer communication technologies, the numbers of digital documents including multimedia data have been recently exploded. In particular, news video database and news video mining have became the subject of extensive research, to develop effective and efficient tools for manipulation and analysis of news videos, because of their information richness. However, many research focus on browsing, retrieval and summarization of news videos. Up to date, it is a relatively early state to discover and to analyse the plentiful latent semantic knowledge from news videos. In this paper, we propose the news video mining system based on multi-modal approach and text mining, which uses the visual-textual information of news video clips and their scripts. The proposed system systematically constructs a taxonomy of news video stories in automatic manner with hierarchical clustering algorithm which is one of text mining methods. Then, it multilaterally analyzes the topics of news video stories by means of time-cluster trend graph, weighted cluster growth index, and network analysis. To clarify the validity of our approach, we analyzed the news videos on "The Second Summit of South and North Korea in 2007".

• Korean Journal of Culture and Social Issue
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• v.22 no.1
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• pp.87-118
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• 2016

The purpose of this present study was to investigate the influence of abusive supervision on strain-based work interference with family and interpersonal deviance. In addition, this study examined the mediating effect of subordinates' emotional labor toward supervisors and the moderating effect of hierarchical organizational climates on emotional labor, perceived organizational family support on strain-based work-family conflict, and social network on interpersonal deviance. The results are summarized as follows: (1) abusive supervision was positively related to subordinates' emotional labor toward supervisors. (2) Emotional labor was positively related to strain-based work-family conflict and interpersonal deviance. (3) Subordinates' emotional labor mediated the relationship between abusive supervision and the two outcome variables. (4) Hierarchical organizational climates moderated the relationship between abusive supervision and emotional labor. (5) Perceived organizational family did not have moderating effect between emotional labor and strain-based work-family conflict. (6) Social network had moderating effect but it did not influence interpersonal deviance as predicted by the hypothesis. Based on the results, implications of findings, limitations, and suggestions for future research were discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3472-3480
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• 2010

The Clustering technology of Energy efficiency wireless sensor network gets the energy efficiency by reducing the number of communication between sensor nodes and sink node. In this paper, First analyzed on the clustering technique of the distributed clustering protocol routing scheme LEACH (Low Energy Adaptive Clustering Hierarchy) and HEED (Hybrid, Energy-Efficient Distributed Clustering Approach), and based on this, new energy-efficient clustering technique is proposed for the cause the maximum delay of dead nodes and to increase the lifetime of the network. In the proposed method, the cluster head is elect the optimal efficiency node based on the residual energy information of each member node and located information between sink node and cluster node, and elected a node in the cluster head since the data transfer process from the data been sent to the sink node to form a network by sending the energy consumption of individual nodes evenly to increase the network's entire life is the purpose of this study. To verify the performance of the proposed method through simulation and compared with existing clustering techniques. As a result, compared to the existing method of the network life cycle is approximately 5-10% improvement could be confirmed.