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For the low-speed diesel engine monitoring with multi-sensor information on ship, the on-line anomaly detection as the fault symptom pre-warning is mainly considered in this paper. The stable operating condition is firstly identified by the ADF test. Then, the on-line anomaly detection with baseline deviation is modeled by the Auto associative Kernel Regression (AAKR) method, where the baseline is...
An efficient people occupancy detection, tracking, and behavior recognition method is introduced in this study. The problem of monitoring wide field can be achieved using the programmable camera network instated of the typical fixed cameras. In addition, based on the depth image feature, the shape feature of the occupant can be used to the activity recognition more accurately.
Today's datacenter is shared among various applications with different QoS requirements, which poses a great challenge to deliver low delay transport with high throughput. Most of works address this challenge by reducing the in-network delay, but assumes a negligible local delay. However, we show that this assumption does not hold for a multi-tenant datacenter that a physical machine is shared by...
In areas of ecological interest, the detection and control of seaweed such as Posidonia Oceanica is usually performed by divers. Due to the limited capacity of the scuba tanks and the human security protocols, this task involves several short immersions leading to poor temporal and spatial data resolution. Thus, it is desirable to automate this task by means of underwater robots. This paper describes...
Most Wi-Fi based localization algorithms are cooperative as user device is required to associate with an AP. However, user may not associate with AP in scenarios such as supermarkets which calls for non-cooperative localization. In this paper, the probe request (PR) frame sent by device is analyzed and the weighted kernel density estimation assisted Bayes (w-KAB) algorithm is utilized for localization...
The step-down unit (SDU) is a high-acuity hospital environment, to which patients may be sent after discharge from the intensive care unit (ICU). About 1- in-7 patients will deteriorate in the SDU and require emergency readmission to the ICU. Upon readmission, these patients experience significantly higher mortality risks and lengths of stay. Gaussian process regression (GPR) models are proposed as...
Cloud computing is a new IT delivery paradigm that offers computing resources as on-demand services over the Internet. Like all forms of outsourcing, cloud computing raises serious concerns about the security of the data assets that are outsourced to providers of cloud services. Security issues of cloud platform have gradually drawn the attention of research institutions and various security companies...
Operating systems serve as executing platforms and resource manager and supervisors for the applications in running phase. With the development of more complex computer systems and applications, the required operating systems become complex too. But the proper management of such complex operating systems by human beings has shown to be impractical. Nowadays, self-managing concepts provide the basis...
Most of security measures for network computing are provided by service provider itself. However, this kind of methods cannot be trusted radically by the user for lacking the ability to control the resource directly. The computing environment for the user is unable to know what software will be provided. To address this problem, we present a security scheme, named Cleanroom Monitoring System (CMS),...
Fault detection and severity classification are critical to gearbox structural health monitoring. A common approach to fault severity classification is to identify the patterns associated with features extracted from raw sensor data that vary with fault deterioration. Since however features only represent partial information contained in the raw data, they may indicate different interactions as faults...
Application of the benefits of modern computing technology to improve the efficiency of agricultural fields is inevitable with growing concerns about increasing world population and limited food resources. Computing technology is crucial not only to industries related to food production but also to environmentalists and other related authorities. It is expected to increase the productivity, contribute...
Although electronic system has entered the digital age, analog circuit is still an essential part. Therefore the performance monitoring or evaluation of analog circuit is extremely important. However some problems about analog circuit performance monitoring is being, such as data acquisition online of the industry field with uncertainty, performance monitoring timeliness. Here an online performance...
Memory error exploits rank among the most serious security threats. Of the plethora of memory error containment solutions proposed over the years, most have proven to be too weak in practice. Multi-Variant eXecution (MVX) solutions can potentially detect arbitrary memory error exploits via divergent behavior observed in diversified program variants running in parallel. However, none have found practical...
Aiming at the multimode industrial process monitoring problem, this paper proposes a fault detection method based on local entropy principal component analysis (LEPCA) algorithm. Firstly, in order to deal with the multimode characteristic of operating data, k nearest neighbor Parzen window (kNN-Parzen) method is used to estimate each sample's local probability density. Then, a local relative density...
Considering the health monitoring requirement of Electronic System, two indexes, such as detection speed and detection reliability, are indispensable. Here a data driven dynamic health monitoring (DDDHM) method is presented. The main idea of DDDHM is to employ a robust learning machine robust least square support vector regression (LSSVR) to monitor quality of electronic system. As to obtain more...
Recent years witness the successful adoption of Cloud computing. However, security remains the top concern for cloud users. The fundamental issue is that cloud providers cannot convince cloud users the trustworthiness of cloud platforms. In this paper, we propose a cloud auditing framework, named CloudAuditor, to examine the behaviors of cloud platforms. By leveraging nested virtualization technology,...
Error data collected at runtime play a key role for dependability analysis and improvement of software systems. The use of monitoring frameworks for legacy mission-critical systems is hindered by limited intervention degree and low intrusiveness requirements. We present the design and experimentation of an error monitoring service for a legacy large-scale critical system in the Air Traffic Control...
To monitor virtual machines and applications in IaaS cloud environments, cloud providers require installing agents in tenants' virtual machines. It is inconvenient for users and is prone to cyber attacks. In this paper, we propose oMon, a out-of-the-box application monitoring framework for cloud applications. oMon does not requires installing any agent in the guest OS of tenants' virtual machines,...
Recently, wireless sensor networks are being increasingly integrated with consumer electronic devices to deliver more intelligent services. Usually, the wireless sensor networks are expected to provide continuous, unattended service for months or even years. However, hardware reliability poses a major challenge to this expectation. To address this issue, this paper designs and implements a software-based...
Quality monitoring and prediction plays a key role in improving product quality and achieving automated quality control in manufacturing processes such as the abrasion-resistant material manufacturing process. Traditional methods that rely on the use of first-principle models are difficult to formulate due to the increasing complexity and high dimensionality of manufacturing processes. Data-driven...
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