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In our economic society, future stock price trend is very hot focus that the investors concern about. Challenges still exist in stock price prediction model regarding significant time-effectiveness of prediction, the complexity of methods and selection of feature index variables. In this paper, we present a new approach based on Logistic Regression to(More)
Traffic information acquisition is often implemented by video cameras or inductive loops, which is expensive or inconvenient from installation and maintenance perspectives. We designed and implemented a pervasive traffic information acquisition system based on wireless sensor networks called EasiTia. Unlike existing solutions, the implementation of the(More)
Traditional Chinese Pulse Diagnosis is a convenient and noninvasive method for disease diagnosis and healthcare. We have designed and implemented a Chinese wrist-pulse retrieval system based on the principle of Traditional Chinese Pulse Diagnosis (TCPD), called EasiCPRS. It is designed to be small in size, low in cost, with flexibility in deployment, and(More)
Pulse Diagnosis Theory (PDT) has the advantages of non-invasive treatment and disease prevention. Combining these merits with Wireless Sensor Network(WSN), we propose a novel networked low-cost and wearable healthcare monitoring system, namely PDhms, for pulse data collection, pulse analysis and pulse diagnosis. Some practical challenges still exist in(More)
With the rapid growth of spatial data, traditional cause-effect analysis and conditional retrieval fall short in the era of big data. Associative retrieval is more reasonable and feasible. To promote the associative retrieval of spatial big data, this paper investigates the combination of the spreading activation (SA) algorithm and spatial ontology model.(More)
Friend recommendation is a fundamental service in both social networks and practical applications, and is influenced by user behaviors such as interactions, interests, and activities. In this study, we first conduct in-depth investigations on factors that affect recommendation results. Next, we design Friend++, a hybrid multi-individual recommendation model(More)