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Pulse transit time (PTT) has been widely studied as an index of blood pressure (BP) changes. In recent years, some prototypes of PTT-based wearable BP measurement devices have been developed, which can relieve users from the discomfort caused by the inflating cuff used in auscultatory and oscillometric BP measurement techniques. However, in the common practice for PTT detection, multi-site sensor...
Telemetry data, containing the data of multiple subsystems such as power system, implies the on-orbit operation status information of the satellite. We can obtain performance characteristics and fault symptom of the satellite subsystems through analyzing these data. Using classification algorithm we can provide normal data for anomaly detection and find the data from various subsystems which have...
Multi-objective optimization problems with many objective functions (≫3) are difficult to solve. This is because the time complexity of optimization algorithms often grows fast with the number of objective functions and the results of many objective optimization algorithms (Pareto front approximation) require large memory and their interpretation can be difficult for the decision maker. It is therefore...
Advanced Persistent Threat (APT) poses a serious threat to cyber security, and its unique high unpredictability, deep concealment and grave harmfulness make the traditional network monitoring technology facing unprecedented challenges in the background of massive and complicated network traffic. This paper aimed for the urgent demand of APT network monitoring. Relying on the rapid development of big...
Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users' influence scores. They rarely consider a person's expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand...
In the task of action recognition, object and scene can provide rich source of contextual information for analyzing human actions, as human actions often occur under particular scene settings with certain related objects. Therefore, we try to utilize the contextual object and scene for improving the performance of action recognition. Specifically, a latent structural SVM is introduced to build the...
Properly utilizing the spatial correlation of regions benefits for improving the performance of label localization task. However, we could not obtain this information directly since we do not have the region level ground truth. In this paper, we propose a weakly spatial constrained graph propagation by mining the spatial correlation from unlabeled regions and integrating it into the graph propagation...
The multi-layer urban logistics facilities location is not only influenced by service radius, but also be readily influenced by the capacity of the facilities and the relationship of different demand points. Therefore, considering the constraints of capacity and correlation, the multi-level urban logistics infrastructures location model with constraints of capacity and correlation is developed based...
With the permeation of Web 2.0, large-scale user contributed images with tags are easily available on social websites. How to align these social tags with image regions is a challenging task while no additional human intervention is considered, but a valuable one since the alignment can provide more detailed image semantic information and improve the accuracy of image retrieval. To this end, we propose...
In this paper, we present a new method for facial age estimation based on ordinal discriminative feature learning. Considering the temporally ordinal and continuous characteristic of aging process, the proposed method not only aims at preserving the local manifold structure of facial images, but also it wants to keep the ordinal information among aging faces. Moreover, we try to remove redundant information...
The traditional Principal Component Analysis (PCA) can only remove first- and second-order correlation between various components of data. To solve this problem and gain the features sensitive to the high-order information, two different architectures of independent principle component analysis (ICA) for palm-dorsa vein recognition are discussed, ICA architecture I based on statistically independent...
The bag-of-visual-words (BoW) representation has received wide application and public acceptance for visual categorization. However, the histogram based image representation ignores the spatial information and correlations among visual words. To tackle these problems, in this paper, we propose to use some image regions called ‘components’, as the higher-level visual elements to represent an image...
The power spectral density function and the ambiguity function(AF) properties of Combination of Chirp Modulation and Pseudonoise Phase Modulation (PN-chirp) pulse signal is analyzed. According to the AF definition of a given finite energy signal, the AF of PN-chirp signal is deduced, and the autocorrelation function of the signal is also obtained. The AF of PN-chirp signal and Pseudonoise Phase Modulation...
An important aspect of airlift problems is to find the smallest fleet of aircraft to move cargo from one or more locations to a destination. In critical airlift operations, such as emergency evacuations, disaster relief and defence operations, a compromise needs to be struck between minimizing the time needed for completing all tasks and minimizing the size of the fleet. Usually, the time to complete...
Network damage evaluation is a hot research topic in network security area. This paper reviews previous works in the area of network damage evaluation. These studies focus on building an index system and computing the damage by the entropy before and after attacks without taking the correlation of index into consideration, which could results in damage increased, and it cannot express the variable...
Currently, the bag of visual words (BOW) representation has received wide applications in object categorization. However, the BOW representation ignores the dependency relationship among visual words, which could provide informative knowledge to understand an image. In this paper, we first design a simple method to discover this dependency through computing the spatial correlation between visual words...
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