A Dynamic k-Nearest Neighbor Method for WLAN-Based Positioning Systems

The static k-Nearest Neighbor (k-NN) method for localization has limitations in accuracy due to the fixed k value in the algorithm. To address this problem, and achieve better accuracy, we propose a new dynamic k-Nearest Neighbor (Dk-NN) method in which the optimal k value changes based on the topologies and distances of its nearest neighbors. The proposed method has been validated using the WLAN-fingerprint data sets collected at COEX, one of the largest convention centers in Seoul, Korea. The proposed method significantly reduced both the mean error distances and the standard deviations of location estimations, leading to a significant improvement in accuracy by ~ 23% compared to the cluster filtered k-NN (CFK) method, and ~ 17% compared to the k-NN (k = 1) method.     

Divergence of knowledge production strategies for emerging technologies between late industrialized countries: Focusing on quantum technology

Traditional wisdom on how late industrialized countries follow the technology trajectories of preceding economies is in need of reformation as these countries have attained industrial leadership in a growing number of fields. However, current understandings about these countries' development of their emerging technologies have yet to investigate the divergence of idiosyncratic technology trajectories. The aim of this paper was to explore how their knowledge production strategies in emerging technology sectors are diverging. Specifically, this research examines the changing patterns of knowledge production in quantum technology in South Korea and China by developing a knowledge portfolio and knowledge strategic diagram. According to the knowledge portfolio, the relative literature position differs. In the knowledge strategic diagram, there are diverging patterns in the emerging keywords sector. This paper contributes to the literature by demonstrating the diverging strategies of late industrialized countries in their transition from catch-up to post-catch-up paradigms and provides policy implications for countries developing an idiosyncratic trajectory in emerging technology sectors.     

Knowledge production patterns of China and the US: quantum technology

Scientometrics - This paper addresses knowledge production patterns in the research and development of quantum technologies, perhaps one of the most promising advances in modern times. Using a...     

Fast and Accurate Detection of Malicious Users in Cooperative Spectrum Sensing Network

Cooperative spectrum sensing allows users to detect available spectrum and utilize it. However, it is known that a few users can easily affect the cooperative decision at the fusion center by reporting falsified sensing data. The problem of detecting malicious users in cooperative spectrum sensing has been studied by numerous researchers. The basic approach is to compute the credibility of the reported data of each user and declare those with low credibility (below some threshold) as malicious. The computation of credibility can be based on several things such as pattern of historic behavior, entropy of the reported data, signal-to-noise ratio, etc. The credibility of the reported data of some user node can be expressed as an attack probability of that node. A node with higher attack probability will have lower credibility while a node with lower attack probability a higher credibility. Then, the problem of computing credibility of a node becomes the problem of computing attack probability of a node given a set of reported data. We can enumerate a list of all possible attack probability vectors for a set of nodes and the list of all possible energy level vectors of the channel for the observed time period, and compute which combination of attack probability and channel energy level vector can have the maximum probability to produce the reported channel energy level. However, the search space is quite large and grows exponentially as the number of user nodes and the number of time slots to observe increase. In this paper, we suggest algorithms that reduce the search space considerably and detect malicious users in linear time instead of exponential time. The suggested algorithms have been implemented and show promising results.