• Journal of Korea Port Economic Association
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• v.37 no.3
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• pp.1-17
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• 2021

Forecasting the daily volume of container is important in many aspects of port operation. In this article, we utilized a machine-learning algorithm based on decision tree to predict future container throughput of Busan port. Accurate volume forecasting improves operational efficiency and service levels by reducing costs and shipowner latency. We showed that our method is capable of accurately and reliably predicting container throughput in short-term(days). Forecasting accuracy was improved by more than 22% over time series methods(ARIMA). We also demonstrated that the current method is assumption-free and not prone to human bias. We expect that such method could be useful in a broad range of fields.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1147-1161
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• 2023

The Internet of Things (IoT) requires a new processing model that will allow scalability in cloud computing while reducing time delay caused by data transmission within a network. Such a model can be achieved by using resources that are closer to the user, i.e., by relying on edge computing (EC). The amount of IoT data also grows with an increase in the number of IoT devices. However, building such a flexible model within a heterogeneous environment is difficult in terms of resources. Moreover, the increasing demand for IoT services necessitates shortening time delay and response time by achieving effective load balancing. IoT devices are expected to generate huge amounts of data within a short amount of time. They will be dynamically deployed, and IoT services will be provided to EC devices or cloud servers to minimize resource costs while meeting the latency and quality of service (QoS) constraints of IoT applications when IoT devices are at the endpoint. EC is an emerging solution to the data processing problem in IoT. In this study, we improve the load balancing process and distribute resources fairly to tasks, which, in turn, will improve QoS in cloud and reduce processing time, and consequently, response time.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.45-57
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• 2009

ETexture mapping is a technique used for adding reality to an image in 3D graphics. However. this technique becomes the bottleneck of the 3D graphics pipeline because it requires large processing power and high memory bandwidth. For reducing memory latency in texture mapping, texture cache is used. As portable devices become smaller and they have power constraint, it is important to reduce the area and the power consumption of the texture cache. In this paper we propose using a small texture cache to reduce the area and the power consumption of the texture cache. Furthermore, we propose techniques to keep a performance comparable to large texture caches by using prefetch techniques and a victim cache. Simulation results show the proposed small texture cache can reduce the area and the power consumption up to 70% and 60%, respectively, by using $1{\sim}2K$ bytes texture cache compared to the conventional 16K bytes cache while keeping the performance.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.169-177
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• 2024

Industrial Wireless Sensor Network (IWSN) is a key feature of Industrial IoT that enables industrial automation through process monitoring and control by connecting industrial equipment such as sensors, robots, and machines wirelessly, and must support the strict requirements of modern industrial environments such as real-time, reliability, and energy efficiency. To achieve these goals, IWSN uses reliable communication methods such as multipath routing, fixed redundant resource allocation, and non-contention-based scheduling. However, the issue of wasting redundant resources that are not utilized for communication degrades not only the efficiency of limited radio resources but also the energy efficiency. In this paper, we propose a scheme that utilizes reinforcement learning in communication scheduling to periodically identify unused wireless resources and reallocate them to save energy consumption of the entire industrial network. The experimental performance evaluation shows that the proposed approach achieves about 30% improvement of resource efficiency in scheduling compared to the existing method while supporting high reliability. In addition, the energy efficiency and latency are improbed by more than 21% and 38%, respectively, by reducing unnecessary communication.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.353-356
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• 2005

In this paper, the proposed $gamma({\gamma})$ line system is developed for reducing the error between non-linear gamma curve produced by a formula and result produced by hardware implementation. The proposed algorithm and system is based on the specific gamma value 2.2, namely the formula is represented by {0,1}$^{2.2}$ and the bit width of input and out data is 10bit. In order to reduce the error, the system is using least squares polynomial of the numerical method which is calculating the best fitting polynomial through a set of points. The proposed gamma line is consisting of nine kinds of quadratic equations, each with their own overlap sections to get more precise. Based on the algorithm verified by $MATLAB^{TM}$ 7.0, the proposed system is implemented by using Verilog-HDL. The proposed system has 2 clock latency; 1 result per clock. The error range (LSB) is -4 and +3. Its standard deviation is 1.287956238. The total gate count of system is 2,083 gates and the maximum timing is 15.56[ns].

• Journal of Digital Convergence
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• v.13 no.11
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• pp.149-156
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• 2015

Due to a change of food culture, many patients suffering from various diseases such as hypertension, heart disease, stroke, cancer. However, it takes a long time in the hospital for many patients due to the administration before the patient care process. In this paper, we propose a m-Healthcare service model that patients can receive medical services without the inconvenience offers by reducing the administrative hospital treatment that can automatically recognize through the hospital installed RFID readers when the patient patients with various diseases are foreign to the hospital. In particular, the proposed model improves the operational efficiency of the existing healthcare system by shortening the treatment time for medical personnel to help patients in emergency situations can determine automatically the patient's status does not give the disease type and condition of the patient to health care personnel. Test results, service latency, efficiency, etc. patient satisfaction, and evaluate the existing health care system model results, the proposed method was improved service delay existing techniques average 16.5% efficiency was higher 27% of patients service satisfaction was improved by 22.4% on average.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.89-101
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• 2014

Recently, as domestic air traffic dramatically increases, the need of ATC(air traffic control) systems has grown for safe and efficient ATM(air traffic management). Especially, for smooth ATC, it is far more important that performance of display system which should show all air traffic situation in FIR(Flight Information Region) without additional latency is guaranteed. In this paper, we design a ASTERIX(All purpose STructured Eurocontrol suRveillance Information eXchange) parsing module to promote stable ATC by minimizing system loads, which is connected with reducing overheads arisen when we parse ASTERIX message. Our ASTERIX parsing module based on pattern matching creates patterns by analyzing received ASTERIX data, and handles following received ASTERIX data using pre-defined procedure through patterns. This module minimizes display errors by rapidly extracting only necessary information for display different from existing parsing module containing unnecessary parsing procedure. Therefore, this designed module is to enable controllers to operate stable ATC. The comparison with existing general bit level ASTERIX parsing module shows that ASTERIX parsing module based on pattern matching has shorter processing delay, higher throughput, and lower CPU usage.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.33-42
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• 2012

Rapid evolution of wired and wireless technologies results in various types of embedded systems, and the software to be embedded into those devices now needs the flexibility rather than the fixedness which was well-known property for the embedded software in the past. Mobile agent is one of the useful distributed technologies of reducing network load and latency because of its disconnected operations and high asynchrony. In this paper, a component-based mobile agent framework, called EmHUMAN, is designed and implemented for structural embedding into the devices showing different functions and resource constraints. It consists of 3 layers of components. Based on those components, a structural embedding, considering resource constraints of required functions, amount of storage space, computing power, network bandwidth, ${\ldots} $ etc can be performed. The components in each layer can be extended with addition of new components, removing some components and modifying components. EmHUMAN plays the role of a framework for developing mobile agent based distributed systems. It is also a mobile agent system by itself. EmHUMAN provides several utilities as built-in API's, and thus high effectiveness in programming mobile agents can be achieved.

• Journal of the Korea Society of Computer and Information
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• v.17 no.7
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• pp.1-11
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• 2012

As process technology scales down, the number of cores integrated into a processor increases dramatically, leading to significant performance improvement. Especially, the GPU(Graphics Processing Unit) containing many cores can provide high computational performance by maximizing the parallelism. In the GPU architecture, the access latency to the main memory becomes one of the major reasons restricting the performance improvement. In this work, we analyze the performance improvement of the 3D GPU architecture compared to the 2D GPU architecture quantitatively and investigate the potential problems of the 3D GPU architecture. In general, memory instructions account for 30% of total instructions, and global/local memory instructions constitutes 60% of total memory instructions. Therefore, the performance of the 3D GPU is expected to be improved significantly compared to the 2D GPU by reducing the delay of memory instructions. However, according to our experimental results, the 3D architecture improves the GPU performance only by 2% compared to the 2D architecture due to the memory bottleneck, since the performance reduction due to memory bottleneck in the 3D GPU architecture increases by 245% compared to the 2D architecture. This paper provides the guideline for suitable memory design by analyzing the efficiency of the memory architecture in 3D GPU architecture.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.1003-1012
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• 2005

The most significant difference of embedded systems from general purpose systems is that embedded systems are allowed to use only limited resources including battery and memory. Especially, the number of applications increases which deal with multimedia data. In those systems with high data computations, the delay of memory access is one of the major bottlenecks hurting the system performance. As a result, many researchers have investigated various techniques to reduce the memory access cost. Most programs generally have locality in memory references. Temporal locality of references means that a resource accessed at one point will be used again in the near future. Spatial locality of references is that likelihood of using a resource gets higher if resources near it were just accessed. The latest embedded processors usually adapt cache memory to exploit these two types of localities. Processors access faster cache memory than off-chip memory, reducing the latency. In this paper we will propose the enhanced dynamic allocation technique for structure-type data in order to eliminate unused memory space and to reduce both the cache miss rate and the application execution time. The proposed approach aggregates fields from multiple records dynamically allocated and consecutively remaps them on the memory space. Experiments on Olden benchmarks show $13.9\%$ L1 cache miss rate drop and $15.9\%$ L2 cache miss drop on average, compared to the previously proposed techniques. We also find execution time reduced by $10.9\%$ on average, compared to the previous work.