• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5357-5381
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• 2018

Cloud computing offers a wide range of on-demand resources over the internet. Utility-based resource allocation in cloud data centers significantly increases the number of cloud users. Heavy usage of cloud data center encounters many problems such as sacrificing system performance, increasing operational cost and high-energy consumption. Therefore, the result of the system damages the environment extremely due to heavy carbon (CO2) emission. However, dynamic allocation of energy-efficient resources in cloud data centers overcomes these problems. In this paper, we have proposed Energy and Service Level Agreement (SLA) Aware Resource Allocation Heuristic Algorithms. These algorithms are essential for reducing power consumption and SLA violation without diminishing the performance and Quality-of-Service (QoS) in cloud data centers. Our proposed model is organized as follows: a) SLA violation detection model is used to prevent Virtual Machines (VMs) from overloaded and underloaded host usage; b) for reducing power consumption of VMs, we have introduced Enhanced minPower and maxUtilization (EMPMU) VM migration policy; and c) efficient utilization of cloud resources and VM placement are achieved using SLA-aware Modified Best Fit Decreasing (MBFD) algorithm. We have validated our test results using CloudSim toolkit 3.0.3. Finally, experimental results have shown better resource utilization, reduced energy consumption and SLA violation in heterogeneous dynamic cloud environment.

• Smart Structures and Systems
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• v.30 no.5
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• pp.433-446
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• 2022

Despite efforts to reduce unexpected accidents at confined construction sites, choking accidents continue to occur. Because of the poorly ventilated atmosphere, particularly in long, confined underground spaces, workers are subject to dangerous working conditions despite the use of artificial ventilation. Moreover, the traditional monitoring methods of using portable gas detectors place safety inspectors in direct contact with hazardous conditions. In this study, a long-range (LoRa)-based wireless safety monitoring system that features the network organization, fault-tolerant, power management, and a graphical user interface (GUI) was developed for underground construction sites. The LoRa wireless data communication system was adopted to detect hazardous gases and oxygen deficiency within a confined underground space with adjustable communication range and low power consumption. Fault tolerance based on the mapping information of the entire wireless sensor network was particularly implemented to ensure the reliable operation of the monitoring system. Moreover, a sleep mode was implemented for the efficient power management. The GUI was also developed to control the entire safety-monitoring system and to manage the measured data. The developed safety-monitoring system was validated in an indoor testing and at two full-scale water pipeline construction sites.

• Journal of Energy Engineering
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• v.17 no.2
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• pp.54-66
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• 2008

After the Kyoto Protocol has been ratified in Feb. 16 2005, the developed countries which is involved in Annex-1 have tried to mitigate GHG to the reduction objective. To accomplish this objective, EU developed EU-ETS, CDM project, and so on. Korea has faced pressure to be a member of Annex-1, because Korea and Mexico are only non-Annex-1 countries in the OECD nations. In this study, we simulated power plant expansion plan and calculated $CO_2$ emission with changing Carbon Tax. Especially, we focused on the competitiveness of IGCC and carbon capture technology. In our result, even though carbon tax rise, nuclear power plant does not always increase, it increase up to minimum load. LNG combined cycle power plants substitute the coal fired power plants. If there are many alternatives like IGCC, these substitute a coal fired power plant and we can reduce more $CO_2$ and save mitigation cost.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.74-79
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• 2017

In this paper, we propose a system model that predicts the original signal transmitted from the transmitter using the received signal in the power line communication system based on the multi - layer perceptron which is one of the machine learning algorithms. Power line communication system using communication system using power network has more noise than communication system using general communication line. It causes a problem that the performance of the power line communication system is degraded. In order to solve this problem, the communication system model proposed in this paper minimizes the influence of noise through original signal prediction and mitigates the performance degradation of the power line communication system. In this paper, we prove that the original signal is predicted by applying the proposed communication system model to the white noise environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.1
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• pp.10-15
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• 2009

With the development of techniques, robots are getting smaller, and the number of robots needed for application is greater and greater. How to coordinate large number of autonomous robots through local interactions has becoming an important research issue in robot community. Swarm Robot Systems (SRS) is a system that independent autonomous robots in the restricted environments infer their status from pre-assigned conditions and operate their jobs through the cooperation with each other. In the SRS, a robot contains sensor part to percept the situation around them, communication part to exchange information, and actuator part to do a work. Especially, in order to cooperate with other robots, communicating with other robots is one of the essential elements. Because Bluetooth has many advantages such as low power consumption, small size module package, and various standard protocols, it is rated as one of the efficient communicating technologies which can apply to small-sized robot system. In this paper, we will develop Bluetooth communicating system for autonomous robots. And we will discuss how to construct and what kind of procedure to develop the communicating system for group behavior of the SRS under intelligent space.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.701-706
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• 2006

Groundwater heat pump systems are the oldest of the ground-souce systems and it has various type. Standing column well type are must be located in hard rock geology site and produce sufficient water for the conventional open loop system. These system are indirect type(the building circulating loop and ground water are intercept). Existence of the exchanger the foundation protect water quality to use of open loop. The design of open loop system are concern on the power requirements. An experimental study was analysis the extremely heating operation COP of ground water heat pump system. Operation efficiency of the 50RT systems shows that, COP $2.9{\sim}5.0$ in heating operation. And generally it shows 3.4.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.71-76
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• 2021

Digital decimation filters are used in various digital signal processing systems using ADCs, including digital communication systems and sensor network systems. When the sampling rate of digital data is reduced, aliasing occurs. So, an anti-aliasing filter is necessary to suppress aliasing before down-sampling the data. Since the anti-aliasing filter has to have a sharp transition band between the passband and the stopband, the order of the filter is very high. However, as the order of the filter increases, the complexity and area of the filter increase, and more power is consumed. Therefore, in this paper, we propose two types of decimation filters, focusing on reducing the area of the hardware. In both cases, the complexity of the circuit is reduced by applying the required down-sampling rate in two times instead of at once. In addition, CIC decimation filters without a multiplier are used as the decimation filter of the first stage. The second stage is implemented using a CIC filter and a down sampler with an anti-aliasing filter, respectively. It is designed with Verilog-HDL and its function and implementation are validated using ModelSim and Quartus, respectively.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.1
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• pp.15-23
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• 2021

The 4th industrial revolution technology has brought many changes not only in human life but also in the industrial field. ICT such as 5G and artificial intelligence and convergence/complex systems such as drones and robots are convenient for humans, and automation of all processes in the industrial field. However, these advanced information and communication technologies also have adverse functions. As advanced ICT was incorporated into military and terrorist weapon systems, more powerful and highly destructive weapon systems began to be developed. In particular, by applying advanced ICT to the production and use of terrorist tools, the terrorist method became more sophisticated and caused more damage. In this paper, we derive advanced ICT that can be abused according to the terror patterns in the 4th industrial revolution era, and present a method that is applied from preparation to execution of terrorism. The abuse of advanced ICT makes terrorism more stealthy and subtle, and increases its destructive power.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.1-6
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• 2024

Recently, artificial neural networks have been playing a crucial role and advancing across various fields. Artificial neural networks are typically categorized into feedforward neural networks and recurrent neural networks. However, feedforward neural networks are primarily used for processing static spatial patterns such as image recognition and object detection. They are not suitable for handling temporal signals. Recurrent neural networks, on the other hand, face the challenges of complex training procedures and requiring significant computational power. In this paper, we propose memristors suitable for an advanced form of recurrent neural networks called reservoir computing systems, utilizing a mask processor. Using the characteristic equations of Ti/TiOx/TaOy/Pt, Pt/TiOx/Pt, and Ag/ZnO-NW/Pt memristors, we generated current-voltage curves to verify their memristive behavior through the confirmation of hysteresis. Subsequently, we trained and inferred reservoir computing systems using these memristors with the NIST TI-46 database. Among these systems, the accuracy of the reservoir computing system based on Ti/TiOx/TaOy/Pt memristors reached 99%, confirming the Ti/TiOx/TaOy/Pt memristor structure's suitability for inferring speech recognition tasks.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.138-149
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• 2018

In this paper, we propose a system model which effectively mitigates impulsive noise that degrades the performance of power line communication. Recently, deep learning have shown effective performance improvement in various fields. In order to mitigate effective impulsive noise, we applied a convolution neural network which is one of deep learning algorithm to conventional system. Also, we used a successive interference cancellation scheme to mitigate impulsive noise generated from multi-users. We simulate the proposed model which can be applied to the power line communication in the Section V. The performance of the proposed system model is verified through bit error probability versus SNR graph. In addition, we compare ZF and MMSE successive interference cancellation scheme, successive interference cancellation with optimal ordering, and successive interference cancellation without optimal ordering. Then we confirm which schemes have better performance.