• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.2
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• pp.304-309
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• 2019

This paper presents a CMOS RF-to-DC converter for video surveillance disposable IoT applications. It widely harvests RF energy of 3G/4G cellular low-band frequency range by employing a tunable impedance matching network. The proposed converter consists of the differential-drive cross-coupled rectifier and the matching network with a 4-bit capacitor array. The proposed converter is designed using 130-nm standard CMOS process. The designed energy harvester can rectify the RF signals from 700 MHz to 900 MHz. It has a peak RF-to-DC conversion efficiency of 72.25%, 64.97%, and 66.28% at 700 MHz, 800 MHz, and 900 MHz with a load resistance of 10kΩ, respectively.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.12
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• pp.1337-1342
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• 2012

In this paper, we propose a novel reconfigurable antenna that can change the electrical shape of the matching network using RF switches of PIN diodes. The designed antenna operates at two different modes that are Mode 1 (HSDPA band, 2.1~2.2 GHz) and Mode 2(WiBro WiFi band, 2.3~2.5 GHz). The antenna is built on both sides of a polyarcylate substrate. The measured reflection coefficient shows a matching bandwidth of 547 MHz($S_{11}$ <-3 dB, 2.035~2.582 GHz) for Mode 1 and 600 MHz($S_{11}$ <-3 dB, 2.2~2.8 GHz) for Mode 2, and it shows average vertical gains of -4.4 dBi and -4.5 dBi in x-y plane, respectively.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.93-104
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• 2005

Recently, RFID/USN is one of fundamental technologies in information and communications networks. Low-Rate WPAN, IEEE802.15.4 is a low-cost communication network that allows wireless connectivity in applications with limited Power and relaxed throughput requirements. Its applications are building automation, personal healthcare, industrial control, consumer electronics, and so on. Some applications require location information. Of course location awareness is useful to improve usability of data Low-Rate WPAN Is regarded as a key specification of the sensor network with the characteristics of wireless communication, computing, energy scavenging, self-networking, and etc. Unfortunately ZigBee alliance propose a lot of applications based on location aware technologies, but the specification and low-rate WPAN devices don't support anything about location-based services. RSSI ( Received Signal Strength indication) is for energy detection to associate, channel selection, and etc. RSSI is used to find the location of a potable device in WLAN. In this paper we studied indoor location awareness using vector matching of RSSI in low-Rate wireless PAN. We analyzed the characteristics of RSSI according to distance and experimented location awareness. We implemented sensor nodes with different shapes and configured the sensor network for the location awareness with 4 fixed nodes and a mobile node. We try to contribute developing location awareness method using RSSI in 3-dimension space.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.1
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• pp.122-130
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• 2012

In this paper, we propose a broadband vehicle antenna that can operate at the WiBro band(2.3~2.4 GHz) for a wireless internet service. The feeding of the proposed antenna consists of two T-matching networks on both side of the polyarcylate substrate, and the two T-matching networks are connected through via holes. The designed antenna was built and installed on a rear window of a commercial sedan, and the antenna performances, such as the reflection coefficients and the radiation gain are measured in the open-sight area. The received signal strength of the designed antenna was also tested in a strong field area as well as in a weak field area. The measurement results show the matching bandwidth($S_{11}$ <10 dB) of about 300 MHz in the WiBro band and the average gain of about -5.13 dBi along the azimuth direction.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.140-146
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• 2023

Resource allocation is one of the top challenges in Internet of Things (IoT) networks. This is due to the scarcity of computing, energy and communication resources in IoT devices. As a result, IoT devices that are not using efficient algorithms for resource allocation may cause applications to fail and devices to get shut down. Owing to this challenge, this paper proposes a novel algorithm for managing computing resources in IoT network. The fog computing devices are placed near the network edge and IoT devices send their large tasks to them for computing. The goal of the algorithm is to conserve energy of both IoT nodes and the fog nodes such that all tasks are computed within a deadline. A bi-partite graph-based algorithm is proposed for stable matching of tasks and fog node computing units. The output of the algorithm is a stable mapping between the IoT tasks and fog computing units. Simulation results are conducted to evaluate the performance of the proposed algorithm which proves the improvement in terms of energy efficiency and task delay.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.114-114
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• 2020

Water contamination in a water distribution network (WDN) is harmful since it directly induces the consumer's health problem and suspends water service in a wide area. Actions need to be taken rapidly to countermeasure a contamination event. A contaminant source ident ification (CSI) is an important initial step to mitigate the harmful event. Here, a CSI approach focused on determining the contaminant intrusion possible location and time (PLoT) is introduced. One of the methods to discover the PLoT is an inverse calculation to connect all the paths leading to the report specification of a sensor. A filtering procedure is then applied to narrow down the PLoT using the results from individual sensors. First, we spatially reduce the suspect intrusion points by locating the highly suspicious nodes that have similar intrusion time. Then, we narrow the possible intrusion time by matching the suspicious intrusion time to the reported information. Finally, a likelihood-score is estimated for each suspect. Another important aspect that needs to be considered in CSI is that there are inherent uncertainties, such as the variations in user demand and inaccuracy of sensor data. The uncertainties can lead to overlooking the real intrusion point and time. To reflect the uncertainties in the CSI process, the Monte-Carlo Simulation (MCS) is conducted to explore the ranges of PLoT. By analyzing all the accumulated scores through the random sets, a spread of contaminant intrusion PLoT can then be identified in the network.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.201-209
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• 2017

This paper is a smartphone object recognition system using hierarchical convolutional neural network. The overall configuration is a method of communicating object information to the smartphone by matching the collected data by connecting the smartphone and the server and recognizing the object to the convergence neural network in the server. It is also compared to a hierarchical convolutional neural network and a fractional convolutional neural network. Hierarchical convolutional neural networks have 88% accuracy, fractional convolutional neural networks have 73% accuracy and 15%p performance improvement. Based on this, it shows possibility of expansion of T-Commerce market connected with smartphone and broadcasting media.

• Journal of KIISE
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• v.44 no.10
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• pp.1071-1080
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• 2017

With today's complex networks, asset identification of network devices is becoming an important issue in management and security. Because these assets are connected to the network, it is also important to identify the network structure and to verify the location and connection status of each asset. This can be used to identify vulnerabilities in the network architecture and find solutions to minimize these vulnerabilities. However, in an IoT(Internet of Things) network with a small amount of resources, the Traceroute packets sent by the monitors may overload the IoT devices to determine the network structure. In this paper, we describe how we improved the existing the well-known double-tree algorithm to effectively reduce the load on the network of IoT devices. To balance the load, this paper proposes a new destination-matching algorithm and attempts to search for the path that does not overlap the current search path statistically. This balances the load on the network and additionally balances the monitor's resource usage.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1135-1139
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• 1989

Three layered neural network was applied for the pattern recognition problem of human spermatozoa in clinical test. The goodness of recognition rate was studied in relation to the number of hidden layer cells and of output layer cells. The proposed method provided better results than conventional template matching technique. Parallel processing of the back propagation learning algorithm was also studied using transputers and its performance was evaluated.

• Proceedings of the KIEE Conference
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• 2004.07c
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• pp.1933-1935
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• 2004

본 연구에서는 변압기형 플라즈마 전류 모델을 기초로 한 평판형 유도 결합 플라즈마 장치에 대한 회로를 분석하여 임피던스 매칭 특성을 조사하였다. 장치 임피던스는 collisional surface impedance를 기반으로 계산된 플라즈마 임피던스와 안테나 임피던스로 결정된다. 매칭 network에 사용된 회로는 Altcmatc-typc의 회로이고, 매칭 소자인 $C_T$와 $C_L$은 임피던스 매칭 조건을 이용하여 계산하였다. 완전 매칭의 경우에는 $C_T$와 $C_L$을 플라즈마 변수들의 함수로 표현하여 의존성을 분석하고, 불완전 매칭의 경우에는 반사파에 대한 반사계수, 반사율을 계산하였다.