• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.70-73
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• 2014

In this paper, we measure and analyze strength of Beacon signal in Picocell environment by using the frequency of WiFi of ISM band. It is displaying the value what measured by using a beacon signal measurement smartphone app in using AP area, on Google maps using the PC application. the data measured by using mapped GPS signal and RSSI of beacon signal, and convert this data to Position coordinates for Google map in PC. when use this system, we can understand and analyze changes of radio signal through location where installed AP.

• Journal of Industrial Technology
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• v.28 no.A
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• pp.105-111
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• 2008

A typical AP (Access Point) selection policy is to select an AP based on the received signal strength indicator (RSSI), ignoring its load. If multiple stations are deployed densely at a particular area, a typical AP selection policy will bring about the overall network throughput degradation. This paper proposes a novel AP selection policy taking into consideration not only signal strength of the APs but also AP loads to avoid Hotspot congestion. An experiment on Alinker implementing proposed AP selection policy, demonstrates that the proposed policy achieves close to optimal load balancing and grants the maximum transmission rate to stations in comparison with SSF (Strongest-Signal-First) and LLF (Least-Loaded-First).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.6
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• pp.707-713
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• 2016

In the IEEE 802.11 Wireless LAN environment, the common Access Point (AP) selection of the existing terminal is based on signal strength. However, the signal strength-based AP selection method does not ensure an optimal data rate. Recently, several AP selection methods to solve this problem have been suggested. However, when we select AP, these have a latency problem and don't consider dense environments of AP. In this paper, we confirm the problem of the conventional AP selection about the signal strength and the throughput through the actual measurement, and propose algorithm that selects AP by scoring link speed and wireless round trip time to compensate the problem. Furthermore, the proposed AP selection algorithm through the actual experiment proves the improved performance as compared with the existing methods.

• Journal of KIISE:Information Networking
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• v.37 no.6
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• pp.489-493
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• 2010

In an indoor localization method taking the lateration-based approach, the distance between a target and an AP (Anchor Point) is estimated using RSS (Received Signal Strength) measurements. Since the characteristics of a radio signal randomly vary in time and space, errors are unavoidable in distance estimation with measured RSS. Since the accuracy of distance estimation affects the localization accuracy of a lateration-based method, additional APs hearing a target have been used for localization in the literature. However, lots of experimental results show that the accuracy of a lateration-based method is improved by using carefully selected APs measuring the high quality RSSs which the distances estimated is close to the actual distances between nodes as reference APs, not using merely more APs. In this paper, we focus on selection method of reference AP and distance estimation method reflecting on environmental dynamics. We validate our method by implementing an indoor localization system and evaluating the accuracy of our method in the various experimental environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.2
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• pp.181-188
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• 2013

In this paper, we present a system design for location determination inside the ship. Since the GPS signal can not be received in the interior of the large vessel, we use the vessel wireless AP (Access Point) RSSI (received signal strength indication) to accurately measure the position. We convert the RSSI for the 3 AP's into distance through the Friis formula and get the location through triangulation. The signal strength varies irregularly due to noise making it difficult to obtain the exact location. Thus Kalman filter is used to real-time position correction, that is store in a server database.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.59-61
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• 2022

Among indoor positioning system techniques using wireless APs, fingerprint techniques collect Mac information and reception strength of APs before performing positioning, build a radio map, and compare it with AP information collected during positioning. However, the existing Radio Map construction method has a problem in that signal interference occurs due to collisions of numerous APs depending on the indoor environment, and the signal strength search result is not always constant. Therefore, this paper compares the existing fixed radio map construction method and the variable radio map construction technique that actively analyzes and constructs the measurement area itself according to signal strength.

• Proceedings of the Korean Society of Toxicology Conference
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• 2001.10a
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• pp.29-30
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• 2001

MAP kinase/ AP-1 signal transduction components are rapidly initiated by many extracellular stimuli, especially environmental carcinogens. We have investigated the role of MAP kinases (Erks, JNKs, and p38 kinases) and AP-1 signal transduction pathways in the process of cell transformation and carcinogenesis. Incubation of Cl 41 cells with tumor promoters such as TPA, EGF, arsenic, or TNF-$\alpha$ led to cell transformation and activation of MAP kinases.(omitted)

• The Journal of Korean Association of Computer Education
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• v.15 no.5
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• pp.55-62
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• 2012

With the development of mobile communications and Internet technology, there is a strong need to provide seamless and fast connectivity for roaming devices. Generally, the mobile host (MH) may have several available networks when entering a new wireless area. However, the standard of decision for user's internet connection is provided only the subsystem identification (SSID) and signal strength of access point (AP). These two standards could not enough to decide optimal AP to the MH. Therefore, to decide the optimal AP, more information is needed. In this paper, we present additional information such as status of MH, capacity, current load, and depth of network hierarchy, by router advertisement message at layer 3. Also, we proposed decision engine (DE) on the MH that analyzes APs and decides the optimal AP automatically by AP's status information. For the MH, wireless connection period is increased, the power consumption is decreased, and the signaling overhead is reduced. For AP and router, the load balancing is provided and the network topology can also be more efficient.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1204-1208
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• 2014

As required performance of UAV (Unmanned Aerial Vehicle) becomes more complex and complicated, required positioning accuracy is becoming more and more higher. GPS is a reliable world wide positioning providing system. Therefore, UAV generally acquires position information from GPS. But when GPS is not available such as too weak signal or too less GPS satellites environments, UAV needs alternative positioning system such as network positioning system. RSSI (Received Signal Strength Indicator) based positioning, which is one method of network positioning technologies, determines its position using RSSI measurements containing distance information from AP (Access Point)s. In that method, a selected AP's configuration has strong and tight relationship with its positioning errors. In this paper, for, we additionally account AP's configuration information by adopting DOP (Dilution of Precision) into AP selection procedures and provide more accurate RSSI based positioning results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12B
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• pp.1442-1449
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• 2011

In this article, we propose a new method for precise WLAN (Wireless Area Network) AP (Access Point) localization using GPS information measured in the smart phone. The idea is that the possible area of WLAN AP location, called AP_Area, is first determined by measuring GPS information and the received signal strength in the smart phones. As the number of measurements from the smart phones increases, the AP_Area are successively narrowed down to the actual AP location. We have performed the simulation to evaluate the proposed algorithm. The simulation results show that the proposed algorithm can detect the Wi-Fi AP localization within 5 m (probability over than 90%).