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21.
Geo-demographic analysis is an essential part of a geographical information system (GIS) for predicting people’s behavior based on statistical models and their residential location. Fuzzy Geographically Weighted Clustering (FGWC) serves as one of the most efficient algorithms in geo-demographic analysis. Despite being an effective algorithm, FGWC is sensitive to initialize when the random selection of cluster centers makes the iterative process falling into the local optimal solution easily. Artificial Bee Colony (ABC), one of the most popular meta-heuristic algorithms, can be regarded as the tool to achieve global optimization solutions. This research aims to propose a novel geo-demographic analysis algorithm that integrates FGWC to the optimization scheme of ABC for improving geo-demographic clustering accuracy. Experimental results on various datasets show that the clustering quality of the proposed algorithm called FGWC-ABC is better than those of other relevant methods. The proposed algorithm is also applied to a decision-making application for analyzing crime behavior problem in the population using the US communities and crime dataset. It provides fuzzy rules to determine the violent crime rate in terms of linguistic labels from socioeconomic variables. These results are significant to make predictions of further US violent crime rate and to facilitate appropriate decisions on prevention such the situations in the future. 相似文献
22.
Son S.H. Mukkamala R. David R. 《Knowledge and Data Engineering, IEEE Transactions on》2000,12(6):865-879
Database systems for real-time applications must satisfy timing constraints associated with transactions in addition to maintaining data consistency. In addition to real-time requirements, security is usually required in many applications. Multi-level security requirements introduce a new dimension to transaction processing in real-time database systems. In this paper, we argue that, due to the conflicting goals of each requirement, tradeoffs need to be made between security and timeliness. We first define mutual information, a measure of the degree to which security is being satisfied by a system. A secure two-phase locking protocol is then described and a scheme is proposed to allow partial violations of security for improved timeliness. Analytical expressions for the mutual information of the resultant covert channel are derived, and a feedback control scheme is proposed that does not allow the mutual information to exceed a specified upper bound. Results showing the efficacy of the scheme obtained through simulation experiments are also discussed 相似文献
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Recently many statistical learning techniques have been applied to the prediction of financial variables. The aim of this paper is to conduct a comprehensive study of the applications of statistical learning techniques to predict the trend of the return of high-frequency Korea composite stock price index (KOSPI) 200 index data using the information from the one-minute time series of spot index, futures index, and foreign exchange rate. Through experiments, it is observed that the spot index change is better predictable with high-frequency time series data and the futures index information significantly improves the prediction accuracy of the return trends of the spot index for high-frequency index data, while the information of exchange rate does not. Also, dimension reduction process before training helps to increase the accuracy and dramatically for some classifiers. In addition, the trained classifiers with which a virtual trading strategy is applied to, noticeable better profits can be achieved than just a buy-and-hold-like strategy. 相似文献
25.
This paper provides generalized analysis of active filters used as electromagnetic interference (EMI) filters and active-power filters. Insertion loss and impedance increase of various types of active-filter topologies are described with applicable requirements and limitations as well as the rationale for selecting active-filter topology according to different applications. 相似文献
26.
Kang K.-D. Son S.H. Stankovic J.A. 《Knowledge and Data Engineering, IEEE Transactions on》2004,16(10):1200-1216
The demand for real-time data services is increasing in many applications including e-commerce, agile manufacturing, and telecommunications network management. In these applications, it is desirable to execute transactions within their deadlines, i.e., before the real-world status changes, using fresh (temporally consistent) data. However, meeting these fundamental requirements is challenging due to dynamic workloads and data access patterns in these applications. Further, transaction timeliness and data freshness requirements may conflict. We define average/transient deadline miss ratio and new data freshness metrics to let a database administrator specify the desired quality of real-time data services for a specific application. We also present a novel QoS management architecture for real-time databases to support the desired QoS even in the presence of unpredictable workloads and access patterns. To prevent overload and support the desired QoS, the presented architecture applies feedback control, admission control, and flexible freshness management schemes. A simulation study shows that our QoS-aware approach can achieve a near zero miss ratio and perfect freshness, meeting basic requirements for real-time transaction processing. In contrast, baseline approaches fail to support the desired miss ratio and/or freshness in the presence of unpredictable workloads and data access patterns. 相似文献
27.
Jiwon Kim Hyeoncheol Francis Son Sungmin Hwang Gyeongtaek Gong Ja Kyong Ko Youngsoon Um Sung Ok Han Sun-Mi Lee 《International journal of molecular sciences》2022,23(9)
Yarrowia lipolytica, the non-conventional yeast capable of high lipogenesis, is a microbial chassis for producing lipid-based biofuels and chemicals from renewable resources such as lignocellulosic biomass. However, the low tolerance of Y. lipolytica against furfural, a major inhibitory furan aldehyde derived from the pretreatment processes of lignocellulosic biomass, has restricted the efficient conversion of lignocellulosic hydrolysates. In this study, the furfural tolerance of Y. lipolytica has been improved by supporting its endogenous detoxification mechanism. Specifically, the endogenous genes encoding the aldehyde dehydrogenase family proteins were overexpressed in Y. lipolytica to support the conversion of furfural to furoic acid. Among them, YALI0E15400p (FALDH2) has shown the highest conversion rate of furfural to furoic acid and resulted in two-fold increased cell growth and lipid production in the presence of 0.4 g/L of furfural. To our knowledge, this is the first report to identify the native furfural detoxification mechanism and increase furfural resistance through rational engineering in Y. lipolytica. Overall, these results will improve the potential of Y. lipolytica to produce lipids and other value-added chemicals from a carbon-neutral feedstock of lignocellulosic biomass. 相似文献
28.
Similarity measuring strategy of image patterns based on fuzzy entropy and energy variations in intelligent robot’s manipulative task 总被引:1,自引:1,他引:0
Changman Son 《Applied Intelligence》2013,38(2):131-145
A similarity measuring strategy of image patterns based on fuzzy entropy and energy variations, using an intelligent robot’s part macro-assembly (part-bringing) as an example, is presented. A part macro-assembly, locating various shaped assembly holes (targets) in a workspace corresponding to shapes of parts and then bringing a part to a corresponding target for the purpose of part mating despite existing obstalces, is introduced. This is accomplished by cooperating a neural network system with a fuzzy optimal control. Fuzzy entropy and energy functions, which are useful measures of variability and information in terms of uncertainty, are introduced to measure its overall performance of task execution related to the part-bringing task. An interrelation among learning, fuzzy entropy, and energy variations used as a measuring tool for a degree of similarity of image patterns is described. Through variations of fuzzy entropy and energy, a degree of similarity between input and desired output image patterns of neural network can be measured. The proposed technique is not only a useful tool to measure a degree of similarity between image patterns, but applicable to a wide range of robotic tasks including motion planning, manufacturing, maneuvering around workspace, and part mating with various shaped parts and targets. 相似文献
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30.
A Highly Planar Fluorinated Benzothiadiazole‐Based Conjugated Polymer for High‐Performance Organic Thin‐Film Transistors 下载免费PDF全文