• Proceedings of the Korean Society of Computer Information Conference
• /
• 2011.06a
• /
• pp.213-216
• /
• 2011

Cloud Network에서 Computing과 마찬가지로 원격지 전력IT기기에 대한 경제성과 산업기술에 대한 평가가 필요하다. 또한 Computer와 Network에서는 기술적인 연구가 필요하다. 본 연구에서는 원격지에서 전력IT기기 제품의 성능평가와 제품인증을 받기 위한 연구이다. 원격지 전력IT 기기의 제품별 기능, 모듈별 기능, 전력전송효율 평가값, 성능값, 허용오차 값 등의 대량 데이터가 존재하여, 전력IT 기기의 평가설계 및 DB, 웹환경에서 개발된 제조사, 평가기관, 인증기관의 주체가 원격지에서 실시간으로 표준화된 원격지 전력IT기기에 대한 평가 인증 프로세스와 평가 인증 값을 국제표준화에 맞출 수 있도록 연구한다.

• Journal of Internet Computing and Services
• /
• v.22 no.5
• /
• pp.9-16
• /
• 2021

Recently, the traffic volume of mobile communications increases rapidly and the small-cell is one of the solutions using two offload schemes, i.e., local IP access (LIPA) and selected IP traffic offload (SIPTO), to reduce the end-to-end delay and amount of mobile data traffic in the core network (CN). However, 3GPP describes the concept of LIPA and SIPTO and there is no decision algorithm to decide the path from source nodes (SNs) to destination nodes (DNs). Therefore, this paper proposes a dynamic mobile data traffic offload scheme using small-cells to decide the path based on the SN and DN, i.e., macro user equipment, small-cell user equipment (SUE), and multimedia server, and type of the mobile data traffic for the real-time and non-real-time. Through analytical models, it is shown that the proposed offload scheme outperforms the conventional small-cell network in terms of the delay of end-to-end mobile data communications and probability of the mobile data traffic in the CN for the heterogeneous networks.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.157.1-157
• /
• 2001

A new methodology is presented to diagnose faults in equipment plasma. This is accomplished by using neural networks as a pattern recognizer of radio frequency(rf) impedance match data. Using a realtime match monitor system, the match data were collected. The monitor system consisted mainly of a multifunction board and a signal flow diagram coded by Visual Designer. Plasma anomaly was effectively represented by electrical match positions. Twenty sets of fault-symptom patterns were experimentally simulated with experimental variations in process factors, which include rf source power, pressure, Ar and O$_2$ flow rates. As the inputs to neural networks, two means and standard deviations of positions were used ...

• Journal of the Korea Institute of Military Science and Technology
• /
• v.24 no.4
• /
• pp.392-400
• /
• 2021

Unlike optical equipment, SAR(Synthetic Aperture Radar) has the advantage of obtaining images in all weather, and object detection in SAR images is an important issue. Generally, deep learning-based object detection was mainly performed in real-valued network using only amplitude of SAR image. Since the SAR image is complex data consist of amplitude and phase data, a complex-valued network is required. In this paper, a complex-valued ResNet network is proposed. SAR image object detection was performed by combining the ROI transformer detector specialized for aerial image detection and the proposed complex-valued ResNet. It was confirmed that higher accuracy was obtained in complex-valued network than in existing real-valued network.

• International Journal of Computer Science & Network Security
• /
• v.22 no.4
• /
• pp.394-400
• /
• 2022

The radio resources available in a wireless network system are limited. Therefor, job of managing resources is not easy task. Because the resources are shared among the UEs that are connected, the process of assigning resources must be carefully controlled. The packet scheduler in an LTE network is in charge of allocating resources to the user equipment (UE). Femtocells networks are being considered as a promising solution for poor channel performance for mulitple environments. The implementation of femtocells into a macrocell (traditional base station) would boost the capacities of the cellular network. To increase femtocells network capacity, a reliable Packet Scheduler mechanism should be implemented. The Packet Scheduler technique is introduced in this paper to maximize capacity of the network while maintaining fairness among UEs. The proposed solution operates in a manner consistent with this principle. An analysis of the proposed scheme's performance is conducted using a computer simulation. The results reveal that it outperforms the well-known PF scheduler in terms of cell throughput and average throughput of UEs.

• Journal of Drive and Control
• /
• v.5 no.2
• /
• pp.24-31
• /
• 2008

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2011.04a
• /
• pp.385-386
• /
• 2011

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2007.06a
• /
• pp.465-466
• /
• 2007

• Proceedings of the KSRS Conference
• /
• 2009.03a
• /
• pp.246-249
• /
• 2009

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38A no.12
• /
• pp.1135-1144
• /
• 2013

Deploying small cells is a reliable and influential solution to handle the skyrocketing traffic increase in the cellular network, and the small cell technology is evolving to ultra-dense network (UDN). In this paper we propose a small cell on/off algorithm with a simple but essential framework composed of access point (AP), user equipment (UE), and small cell controller (SCC). We propose Device-Assisted Networking for Cellular grEening (DANCE) algorithms that save the energy consumption by tying to minimize the number of turned-on APs while maintaining the network throughput. In doing so, SCC firstly gathers the feedback messages from UEs and then makes a decision including a set of turned-on APs and user association. DANCE algorithm has several variations depending on the number of bits of the UE's feedback message (1 bit vs. N bit), and is divided into AP-first, UE-first, or Proximity ON according to the criteria of selecting the turned-on APs. We perform extensive simulations under the realistic UDN environment, and the results confirm that the proposed algorithms, compared to the baseline, can significantly enhance the energy efficiency, e.g., more than a factor of 10.