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Data collected by fitness trackers could play an important role in improving the health and well-being of the individuals who wear them. Many insurance companies even offer monetary rewards to participants who meet certain steps or calorie goals. However, in order for it to be useful, the collected data must be accurate and also reflect real-world performance. While previous studies have compared...
In this study, we compared several classifiers for the supervised distinction between normal elderly and Alzheimer's disease individuals, based on resting state electroencephalographic markers, age, gender and education. Three main preliminary procedures served to perform features dimensionality reduction were used and discussed: a Support Vector Machines Recursive Features Elimination, a Principal...
Nowadays, more and more applications are moving to cloud computing. How to deploy these applications optimally is a great challenge. Many cloud applications, such as scientific applications, are large-scale distributed systems that are deployed on a lot of distributed cloud nodes, and there are a lot of communications between these nodes. Therefore, taking the communication latency between cloud nodes...
It is well known that a decline of arousal level causes of poor performance of movements or judgments. Our previous study indicates that microsaccade (MS) rates and pupil fluctuations change before slow eye movements (SEMs) (Honda et al. 2013). However, SEM detection of this study was obscure and insufficient. In this study, we propose a new SEM detection method and analyze MS rates and pupil fluctuations...
In this paper, a new method for automatic identification of ground control points (GCPs) on optical remote sensing images is presented. An elastic Radial Basis Function (RBF) neural network based model for nonlinear coordinate transformation and image rectification is proposed. The new method can be used to produce dense fields of about thousands of GCPs per image to train highly deformable transformation...
In this paper, a modified partial least-squares (PLS) regression modeling method is proposed. The proposed method can build a modified regression model to extract the useful information in residual subspace, which is helpful to predict the output variables. With this method, more accurate quality variables are predicted. In simulation experiment, penicillin fermentation process is used to test the...
With cloud computing, a cycle of fault diagnosis and recovery becomes the norm. There is a large amount of monitoring data and log events available, but it is hard to figure out which events or metrics are critical in fault diagnosis. Other approaches model faults as a deviation from normal behaviors, and thus are less applicable in cloud where changes in the environment may impact what is considered...
This Activity monitoring of workers in installations such as industries, underground tunnels, sewerage lines, remote field deployments etc. is a daunting task. Due to lack of communication systems and scarce energy resources, these scenarios pose great challenges in developing a monitoring system for workers. The design of activity recognition system for workers, using a single tri-axial accelerometer...
Botnet has become one of the most serious threats to Internet security. Compared with network-based bot detection approaches, host-based approaches can discover more insights of unknown bots, and we may completely eliminate bots if we can successfully detect them on end-host. Host-based approaches mainly include signature and behavior-based detection approaches. In this paper we propose a behavior...
Distributed state monitoring plays a critical role in Cloud datacenter management. One fundamental problem in distributed state monitoring is to minimize the monitoring cost while maximizing the monitoring accuracy at the same time. In this paper, we present Volley, a violation likelihood based approach for efficient distributed state monitoring in Cloud datacenters. Volley achieves both efficiency...
The focus of this paper is to characterize the behavior of large, evolving networks, in terms of central nodes to identify patterns that may be conducive to persistent threat structures over time and geo-spatial regions. We propose an approach to monitor central nodes to determine Consistency and Inconsistency (CoIn) in their availability across time periods. Our approach also identifies the time...
Internet threat monitoring systems are studied and developed to comprehend the malicious activities on the Internet. On the other hand, it is known that attackers devise a technique that locates the deployment of sensors that constitute the monitoring system. This technique is called as localization attacks to Internet threat monitors. If attackers can detect sensors, they can evade them when they...
The worldwide prevalence of obesity is considered as a serious issue because obesity is one of the main causes of diabetes, heart disease, and cancer. Obesity is associated with various habits of our daily life, e.g. short sleep duration, high alcohol intake, and nonparticipation in physical exercise. Therefore, changing these habits in order to reduce body weight is recognized as an effective solution...
Driven by the large-scale growth of applications deployment in data centers and complicated interactions between service components, automated application dependency discovery becomes essential to daily system management and operation. In this paper, we present ADD, which extracts dependency paths for each application by decomposing the application-layer connectivity graph inferred from passive network...
The electrocardiogram (ECG) is a new and promising modality for biometric recognition. This signal is typically collected within welfare monitoring environments along with other vital signals. As opposed to static biometric modalities like the iris or the fingerprints, ECG is time-dependent thereby presenting the opportunity of continuously authenticating subjects in such environments. However, ECG...
While there is a lot of research on change detection based on the streaming classification error, finding changes in multidimensional unlabelled streaming data is still a challenge. Here we propose to apply principal component analysis (PCA) to the training data, and mine the stream of selected principal components for change in the distribution. A recently proposed semi-parametric log-likelihood...
In order to research the sensitivity of the ERP component P300 to mental workload which was related to flight task, a dual task was performed. In the primary task, the subjects needed to accomplish the whole dynamic process of flight simulation in a flight simulator, including take off, cruise and landing. During the process of flight simulation, subjects needed to monitor the information targets...
Continuous glucose monitoring systems are an integral component of diabetes management. Efforts to improve the accuracy and robustness of these systems are at the forefront of diabetes research. Towards this goal, a multi-sensor approach was evaluated in hospitalized patients. In this paper, we report on a multi-sensor fusion algorithm to combine glucose sensor measurements in a retrospective fashion...
Backscatter coefficients (σ0) of PALSAR increase about 3 to 4 dB the cultivation period of paddy rice, and correlation was seen in the height of paddy rice and σ0. However it is difficult to specific planted paddy rice and to estimate the amount of rice growth because the difference of σ0 at each fields were large. Unsupervised classification (K-means method) was carried out using Dbl and Odd components...
In the field of service computing, reputation of a Web service is usually calculated using feedback ratings provided by service users. However, the existing of malicious ratings and different preferences of different service users often lead to a bias towards positive or negative ratings. In this paper, we propose a novel reputation measure method for Web services. The proposed method employs two...
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