• Journal of the Korean Institute of Rural Architecture
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• v.25 no.1
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• pp.35-44
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• 2023

This study aimed to understand the driver change of recent research in relation to rural and migrant and draw overarching issues as well as to provide implications to contribute to migrants' social integration in Korean rural areas. As for the scope and method of the study, data through quantitative bibliographic analysis (quantitative data) and research keywords by period were derived. To address the aim this study employed bibliometric analysis utilising netwok mapping interface analysis by VOSviewer and topic modeling analysis by Netminer. The findings were revealed that firstly mental health issues in abroad research and employment and discrimination in domestic research both derived from migrant mobility constituted staple key issues, secondly internal and external research differed two issues in health and violence where Korea has overlooked the issues seriously. Therefore this study presented implications which are about first, health and violence-related sections for migrants should be specified into domestic law, second domestic-focused MIPEX index should be developed in which the two issues are over-weighted and last such newly emerging approach 'inclusive formation of social psychological mechanisms should be widely spread. Concluding remark is that delivering the implications can be foster to migrants' integration in rural area underlining that this will ultimately contribute to migrants' quality of life.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.510-519
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• 2020

Within an intelligent automated cyber-physical system, the realization of the autonomous mechanism for data collection, data integration, and data analysis plays a critical role in the design, development, operation, and maintenance of such a system. This construct is particularly vital for fault-tolerant route-finding systems that rely on the imprecise GPS location of the vehicles to properly operate, timely plan, and continuously produce informative feedback to the user. More essentially, the integration of digital twins with cyber-physical route-finding systems has been overlooked in intelligent transportation services with the capacity to construct the network routes solely from the locations of the operating vehicles. To address this limitation, the present study proposes a conceptual architecture that employs digital twin to autonomously maintain, update, and manage intelligent transportation systems. This virtual management simulation can improve the accuracy of time-of-arrival prediction based on auto-generated routes on which the vehicle's real-time location is mapped. To that end, first, an intelligent transportation system was developed based on two primary mechanisms: 1) an automated route finding process in which predictive data-driven models (i.e., regularized least-squares regression) can elicit the geometry and direction of the routes of the transportation network from the cloud of geotagged data points of the operating vehicles and 2) an intelligent mapping process capable of accurately locating the vehicles on the map whereby their arrival times to any point on the route can be estimated. Afterward, the digital representations of the physical entities (i.e., vehicles and routes) were simulated based on the auto-generated routes and the vehicles' locations in near-real-time. Finally, the feasibility and usability of the presented conceptual framework were evaluated through the comparison between the primary characteristics of the physical entities with their digital representations. The proposed architecture can be used by the vehicle-tracking applications dependent on geotagged data for digital mapping and location tracking of vehicles under a systematic comparison and simulation cyber-physical system.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.37-51
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• 2023

Spatial information is essential for interpreting urban phenomena. Methodologies for spatializing urban information, especially when it lacks location details, have been consistently developed. Typical methods include Geocoding using structured address information or place names, spatial integration with existing geospatial data, and manual tasks utilizing reference data. However, a vast number of documents produced by administrative agencies have not been deeply dealt with due to their unstructured nature, even when there's demand for spatialization. This research utilizes the natural language processing model BERT to spatialize public documents related to urban planning. It focuses on extracting sentence elements containing addresses from documents and converting them into structured data. The study used 18 years of urban planning public announcement documents as training data to train the BERT model and enhanced its performance by manually adjusting its hyperparameters. After training, the test results showed accuracy rates of 96.6% for classifying urban planning facilities, 98.5% for address recognition, and 93.1% for address cleaning. When mapping the result data on GIS, it was possible to effectively display the change history related to specific urban planning facilities. This research provides a deep understanding of the spatial context of urban planning documents, and it is hoped that through this, stakeholders can make more effective decisions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2750-2763
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• 2012

The Domain Name System (DNS) is a critical Internet infrastructure that provides name to address mapping services. In the past decade, Denial-of-Service (DoS) attacks have targeted the DNS infrastructure and threaten to disrupt this critical service. While the flooding DoS attacks may be alleviated by the DNS caching mechanism, we show in this paper that flooding DoS attacks utilizing name error queries is capable of bypassing the cache of resolvers and thereby impose overwhelming flooding attacks on the name servers. We analyze the impacts of such DoS attacks on both name servers and resolvers, which are further illustrated by May 19 China's DNS Collapse. We also propose the detection and defense approaches for protecting DNS servers from such DoS attacks. In the proposal, the victim zones and attacking clients are detected through monitoring the number of corresponding responses maintained in the negative cache. And the attacking queries can be mitigated by the resolvers with a sample proportion adaptive to the percent of queries for the existent domain names. We assess risks of the DoS attacks by experimental results. Measurements on the request rate of DNS name server show that this kind of attacks poses a substantial threat to the current DNS service.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.1-7
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• 2017

Recently, NAND flash memory, which is used as a storage medium, is replacing HDD (Hard Disk Drive) at a high speed due to various advantages such as fast access speed, low power, and easy portability. In order to apply NAND flash memory to a computer system, a Flash Translation Layer (FTL) is indispensably required. FTL provides a number of features such as address mapping, garbage collection, wear leveling, and hot data identification. In particular, hot data identification is an algorithm that identifies specific pages where data updates frequently occur. Hot data identification helps to improve overall performance by identifying and managing hot data separately. MHF (Multi hash framework) technique, known as hot data identification technique, records the number of write operations in memory. The recorded value is evaluated and judged as hot data. However, the method of counting the number of times in a write request is not enough to judge a page as a hot data page. In this paper, we propose hot data identification which considers not only the number of write requests but also the persistence of write requests.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.1
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• pp.59-67
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• 2012

In this paper, we designed an inter-operation architecture of 10G G-PON(Gigabit passive optical network) network and NGN(Next generation network) architecture. And, we proposed mechanism of dynamic GEM(G-PON encapsulation mode) Port-ID allocation. This is able to solve a problem of 10G G-PON inter-operation. The mechanism of dynamic GEM Port-ID allocation has OMCI(ONT management control and interface) mapping table for IP address and port number. That architecture is able to support per flow QoS(Quality of service) as well as QoS of NGN requirement. So that can improve the resource efficiency of QoS than the existing G-PON architecture.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.6
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• pp.808-816
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• 2016

As the number of CPU/GPU cores and IPs in SOC increases and applications require explosive memory bandwidth, simultaneously achieving good throughput and fairness in the memory system among interfering applications is very challenging. Recent works proposed priority-based thread scheduling and channel partitioning to improve throughput and fairness. However, combining these different approaches leads to performance and fairness degradation. In this paper, we analyze the problems incurred when combining priority-based scheduling and channel partitioning and propose dynamic priority thread scheduling and adaptive channel partitioning method. In addition, we propose dynamic address mapping to further optimize the proposed scheme. Combining proposed methods could enhance weighted speedup and fairness for memory intensive applications by 4.2% and 10.2% over TCM or by 19.7% and 19.9% over FR-FCFS on average whereas the proposed scheme requires space less than TCM by 8%.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2000.05a
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• pp.322-328
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• 2000

This study discusses cognition as a computable mapping in cognitive system and relates G del's Incompleteness Theorems to the computability of cognition from a metamathematical perspective. Understanding cognition as a from of computation requires not only Turing machine models but also neural network models. In previous studies of computation by cognitive systems, it is remarkable to note how little serious attention has been given to the issue of computation by neural networks with respect to G del's Incompleteness Theorems. To address this problem, first, we introduce a definition of cognition and cognitive science. Second, we deal with G del's view of computability, incompleteness and speed-up theorems, and then we interpret G del's disjunction on the mind and the machine. Third, we discuss cognition as a Turing computable function and its relation to G del's incompleteness. Finally, we investigate cognition as a neural computable function and its relation to G del's incompleteness. The results show that a second-order representing system can be implemented by a finite recurrent neural network. Hence one cannot prove the consistency of such neural networks in terms of first-order theories. Neural computability, theoretically, is beyond the computational incompleteness of Turing machines. If cognition is a neural computable function, then G del's incompleteness result does not limit the compytational capability of cognition in humans or in artifacts.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.209-217
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• 2014

Of several approaches for future Internet, separating two properties of IP address into locator and identifier, is being considered as a highly likely solution. IETF's LISP (Locator ID Separation Protocol) is proposed for this architecture. In particular, the LISP model easily allows for device mobility through simple update of information at MS (Mapping Server) without a separate protocol. In recent years, some of the models supporting device mobility using such LISP attributes have emerged; however, most of them have the limitation for seamless mobility support due to the frequent MS information updates and the time required for the updates. In this paper, PMIPv6 (Proxy Mobile IPv6) model is applied for mobility support in LISP model. PMIPv6 is a method that can support mobility based on network without the help of device; thus, this we define anew the behavior of functional modules (LMA, MAG and MS) to fit this model to the LISP environment and present specifically procedures of device registration, data transfer, route optimization and handover. In addition, our approach improves the communication performance using three tunnels identified with locators between mobile node and corresponding node and using a route optimized tunnel between MN's MAG and CN's MAG. Finally, it allows for seamless mobility by designing a sophisticated handover procedure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4412-4428
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• 2018

The purpose of this work is to solve the problem of representing an entire video using Convolutional Neural Network (CNN) features for human action recognition. Recently, due to insufficient GPU memory, it has been difficult to take the whole video as the input of the CNN for end-to-end learning. A typical method is to use sampled video frames as inputs and corresponding labels as supervision. One major issue of this popular approach is that the local samples may not contain the information indicated by the global labels and sufficient motion information. To address this issue, we propose a binary hashing method to enhance the local feature extractors. First, we extract the local features and aggregate them into global features using maximum/minimum pooling. Second, we use the binary hashing method to capture the motion features. Finally, we concatenate the hashing features with global features using different normalization methods to train the classifier. Experimental results on the JHMDB and MPII-Cooking datasets show that, for these new local features, binary hashing mapping on the sparsely sampled features led to significant performance improvements.