• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.383-394
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• 2013

As a way of augmenting constrained resources of mobile devices such as CPU and memory, many works on mobile cloud computing (MCC), where mobile devices utilize remote resources of cloud services or PCs, have been proposed. Typically, in MCC, many nodes with different operating systems and platform and diverse mobile applications or services are located, and a central manager autonomously performs several management tasks to maintain a consistent level of MCC overall quality. However, as there are a larger number of nodes, mobile applications, and services subscribed by the mobile applications and their interactions are extremely increased, a traditional management method of MCC reveals a fundamental problem of degrading its overall performance due to overloaded management tasks to the central manager, i.e. a bottle neck phenomenon. Therefore, in this paper, we propose a clustering-based optimization method to solve performance-related problems on large-scaled MCC and to stabilize its overall quality. With our proposed method, we can ensure to minimize the management overloads and stabilize the quality of MCC in an active and autonomous way.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.39 no.2
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• pp.39-49
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• 2021

This study was conducted to establish practical goals for the viewing environment and interpretation and delivery system of cultural heritage and to create an viewing environment according to the classification of cultural heritage types, and the conclusions reached are as follows. First, five goals were set based on the international basic principles of the cultural heritage viewing environment and interpretation and delivery system. Second, based on the set goals, cultural heritage was classified into the first type 'disappeared and hidden heritage', the second type 'stuffed memory heritage', and the third type 'living memory heritage'. Third, the directions for creating the viewing environment for each type of cultural heritage were suggested. The first type has to be able to properly convey cultural heritage to visitors through excavation and digital technology. The second type needs a plan to deliver tangible and intangible values by combining various digital technologies with actual cultural heritage. The third type should emphasize the role of local residents in effectively enjoying the tangible and intangible values ??that already exist. Fourth, it proposed comprehensive considerations in the establishment of the cultural heritage viewing environment and interpretation and delivery system. Based on dynamic and sustainable heritage management, cultural heritage viewing should be valuable, satisfying and enjoyable. In addition, local communities should be actively involved, and tourism and conservation activities should be able to benefit the community. Establishment of a viewing environment should protect and strengthen the authenticity of cultural heritage.

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.19-28
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• 2004

The major problems in workflow system which controls business process arise with the difficulty of managing a vast volume of data. In this paper, a more reasonable method to manage workflow data is proposed after analyzing the data being used in workflow system. The data used in workflow system can be classified to model data, control data, workitem data and relevant data. The prime accent is placed on the workflow model data, as the model data is normally consistent and referenced more frequently that if the data is used efficiently, it is anticipated to give a good performance to workflow system. Relying on an intensive study, this paper designs and develops a model data system. This model data system is based on memory and manages versions, consistency, dynamic modification, and etc

• Journal of the Korea Computer Industry Society
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• v.5 no.1
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• pp.87-100
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• 2004

XML has recently considered as a new standard for data presentation and exchange on the web, many researches are on going to develop applications and index mechanism to store and retrieve XML documents efficiently. In this paper, design a Main-Memory based XML storage system for efficient management of XML document. And propose structured retrieval of XML document tree which reduce the traverse of XML document tree using element type information included user queries. Proposed indexing mechanism has flexibilities for dynamic data update. Finally, for query processing of XML document include Link information, design a index structure of table type link information on observing XLink standards.

• Proceedings of the IEEK Conference
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• summer
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• pp.204-208
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• 2004

Embedded business will be expanded market more and more since customers seek more wearable and ubiquitous systems. Cellular telephones, PDAs, notebooks and portable multimedia devices could bring higher microprocessor revenues and more rewarding improvements in performance and functions. Increasing battery capacity is still creeping along the roadmap. Until a small practical fuel cell becomes available, microprocessor developers must come up with power-reduction methods. According to MPR 2003, the instruction and data caches of ARM920T processor consume $44\%$ of total processor power. The rest of it is split into the power consumptions of the integer core, memory management units, bus interface unit and other essential CPU circuitry. And the relationships among CPU, peripherals and caches may change in the future. The processor working on higher operating frequency will exact larger cache RAM and consume more energy. In this paper, we propose advanced low power trace cache which caches traces of the dynamic instruction stream, and reduces cache access times. And we evaluate the performance of the trace cache and estimate the power of the trace cache, which is compared with conventional cache.

• The KIPS Transactions:PartA
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• v.14A no.1 s.105
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• pp.47-54
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• 2007

In this paper we present a translation lookaside buffer (TLB) system with low power consumption for imbedded processors. The proposed TLB is constructed as multiple banks, each with an associated block buffer and a corresponding comparator. Either the block buffer or the main bank is selectively accessed on the basis of two bits in the block buffer (tag buffer). Dynamic power savings are achieved by reducing the number of entries accessed in parallel, as a result of using the tag buffer as a filtering mechanism. The performance overhead of the proposed TLB is negligible compared with other hierarchical TLB structures. For example, the two-cycle overhead of the proposed TLB is only about 1%, as compared with 5% overhead for a filter (micro)-TLB and 14% overhead for a same structure without continuos accessing distinction algorithm. We show that the average hit ratios of the block buffers and the main banks of the proposed TLB are 95% and 5% respectively. Dynamic power is reduced by about 95% with respect to with a fully associative TLB, 90% with respect to a filter-TLB, and 40% relative to a same structure without continuos accessing distinction algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.5 s.335
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• pp.63-72
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• 2005

This paper describes a new approach for the operating system level power management to reduce the energy consumed in the IO devices in a robot platform, which provides various functions such as navigation, multimedia application, and wireless communication. The policy proposed in the paper, which was named the Energy-Aware Job Schedule (EAJS), rearranges the jobs scattered so that the idle periods of the devices are clustered into a time period and the devices are shut down during their idle period. The EAJS selects a schedule that consumes the minimum energyamong the schedules that satisfy the buffer and time constraints. Note that the burst job execution needs a larger memory buffer and causes a longer time delay from generating the job request until to finishing it. A prototype of the EAJS is implemented on the Linux kernel that manages the robot system. The experiment results show that a maximum $44\%$ power saving on a DSP and a wireless LAN card can be obtained with the EAJS.

• Journal of Biomedical Engineering Research
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• v.11 no.2
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• pp.305-314
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• 1990

In this paper we have implemented and tested TPN which is system to supply sufficent nutrition to nutritionally deficient patient by means of ES (expert system) a kind of A.1 (artificial intelligence) . This system affords to evaluation of nutritional state of patient which is essential to physi- cian. who performs TPN, decision of performing TPN and management of patient-data & calculation of information needing to making TPN fluid. The features were as follolv 1. we input data, take ideal weight of patient and 24hr's creatlnln In urine according to chart in system compare TSF (triceps skin fold), MAC (mid-arm circumference), AMC (arm muscle circumference) to 5th, 15th, 50th percentile and evaluate the nutritional state of patient. 2. Calculation of protein & nonprotein calorie needing to treament of patient can be made exactly by stress factor, activity factor and body temperature. 3. patient's personal recording needing to management of patient date name of chief doc- tor, name of department of admission, chart number, history can by taken very easily. 4. The way of system operating is pull-down Menu one, It can be processing very efficiently. 5. Date processing in system, we can manage memory volume of computer verlr efficiently using of dynamic allocation variables. 6. We can make it very easy to edit & revise the input data, processed data is saved to diskette in 2 files (TDF, THF) , these are semipermanent preservation.

• The KIPS Transactions:PartA
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• v.13A no.1 s.98
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• pp.79-86
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• 2006

Recently the tagSNP selection problem has been researched for reducing the cost of association studies between human's diversities and SNPs. General approach for this problem is that all of SNPs are separated into appropriate blocks and then tagSNPs are chosen in each block. Marsel in this paper is the system that involved the concept of linkage disequilibrium for overcoming the problem that the existing block partitioning approaches have short of biological meanings. In most approaches, the contiguous regions, which recombinations have LD coefficient |D'| and then tagSNP selection step is performed. And MarSel guarantees the minimum tagSNP selection using entropy-based optimal selection algorithm when tagSNPs are chosen in each block, and enables chromosome-level association studies using efficient memory management technique when input is very large-scale dataset that is impossible to be processed in the existing systems.