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This paper proposes a human activity monitoring system using accelerated sensors based on wireless sensor networks. By implementing SVM on embedded sensor node and using pitch roll, the direction of human activities can also be classified. By using two 3-axis accelerated sensors and ZigBee protocol, the human activity system can be monitored on-line real-time and recorded the human activities in the...
The advances in the wearable devices and Artificial Intelligence domains highlight the need for ICT systems that aim in the improvement of human's quality of life. In this paper we present the sleeping tracking component of an activity and sleeping tracking system. We present the sleep quality assessment based on EEG processing and support vector machines with sequential minimal optimization classifiers...
several methods of Statistical Process Control (SPC) are used to analyze process measurements with the purpose to detect faults that affect the process stability. SPC has a major drawback because it indicates the presence of faults without explaining which ones and where are the faults. In practical applications, SPC just analyses univariate signals limiting the study of multiple measures. Nowadays,...
There is a growing need for the effective fermentation monitoring during the manufacture of wine due to the rapid pace of change in the industry. In this study, the potential of attenuated total reflectance mid-infrared (ATR-MIR) spectroscopy to monitor time-related changes during Chinese rice wine (CRW) fermentation was investigated. Interval partial least-squares (i-PLS) and support vector machine...
We present industrial experience on software health monitoring. Our goal was to determine whether we can predict abnormal behavior, based on data captured from software system interfaces. To analyze the system state and predict software health problems, we used Support Vector Machine (SVM) based analysis. To train the SVM, we exploited random testing with feedback and swarm testing with feedback to...
This paper describes an effective solution to the task of a remote monitoring of super-extended objects (oil and gas pipeline, railways, national frontier). The suggested solution is based on the principle of simultaneously monitoring of seismoacoustic and optical/infrared physical fields. The principle of simultaneous monitoring of those fields is not new but in contrast to the known solutions the...
The rational allocation of water resources has become an important prerequisite for the protection of national economic and social sustainable development as the China economic develops rapidly, therefore establishing water security environment monitoring and evaluation mechanisms is a good way for providing services and solutions for regional environmental management and accident pollution. Considering...
With Android terminal into the life of people, the spread of Android malware seriously affected people's life. As a result of the Android security flaws, attackers can easily collect private information of users, and the information can be utilized in APT attacks. It is not only a threat to the end user, but also poses a threat to industrial control systems and mobile Internet. In this paper, we propose...
Inductive bias represents an important factor in learning theory, as it can shape the generalization properties of a learning machine. This paper shows that biased regularization can be used as inductive bias to effectively tackle the semi-supervised classification problem. Thus, semi-supervised learning is formalized as a supervised learning problem biased by an unsupervised reference solution. The...
A portable & wearable falling monitoring system is proposed in this paper, which is based on microcontroller and triaxial accelerometer, and used for real-time monitoring of human body motion state. Its purpose is to make real-time judgments during the falling, and enable airbags or other protective devices before the body impacts with the ground, preventing or reducing the damage of falling to...
UV/vis spectrometric quantification is widely applied in water quality monitoring systems. The UV/vis spectrum contains a huge amount of information about the water composition so that it can be used to measure the density of substances. However, the traditional methods to estimate densities using spectrum based on Lambert-Beer's law become invalid in UV/vis spectrum because of the strong correlation...
A Dynamic Energy Management (DEM) controller which is capable of taking decisions based on the status of the grid-connected smart microgrid has been developed using Support Vector Machine (SVM) and Artificial Neural Networks (ANN). The proposed control strategy involves the decisions for the dynamic charge-discharge transactions in the energy storage systems like battery and pumped hydro (PH) units...
In Machine Learning applications, the selection of the classification algorithm depends on the problem at hand. This paper provides a comparison of the performance of the Support Vector Machine (SVM) and the Artificial Neural Network (ANN) for food intake detection. A combination of time domain (TD) and frequency domain (FD) features, extracted from signals captured using a jaw motion sensor, were...
Along with the fast development of economy, the rational allocation of water resources has become one of the prerequisites which ensure the sustainable development of a country. Building a water quality surveillance and evaluation mechanism serving for managing regional water environment and addressing sudden contamination accident is of great importance. Based on the monitoring data on water quality,...
Microarray technology, as a revolutionary tool for biomedical research, has been widely used to analyze the gene expression level. Image segmentation is an important step of microarray technology. In this paper, we have presented an improved SVM method, which combined the SVM with the canny algorithm, the morphological algorithm and the fixed circle method, to obtain a better segmentation result....
Urban green space plays an important and positive role in global carbon cycle, and it is very important for improving the ecological environment of the city, reducing the urban heat island effect, promoting the harmonious relationship between human and nature. In order to overcome the disadvantages of the existing method to extract green space information and solve the problem that consume much time...
A monitoring system based on multiple microelectromechanical systems (MEMS) has been developed to maintain human healthcare. Using such a MEMS based monitoring system, several kinds of numerical data from several types of sensors can be measured. Our goal is to develop a intelligent monitoring system with small size. In order to microminiaturize the monitoring system, we need to minimize the power...
Numerous accidents from crowd stampedes have been recorded in human history, Therefore, the public has set high priority on the safety of public places. Surveillances systems aim to use artificial intelligence to address this problem, so that the crowd accident can be significantly reduced. We adopt a low cost camera to gather visual data and propose a cellular model for data interpretation. Based...
In this paper, we present a system for Chinese news program management based on cross media video analysis. Audio, caption text and video frames are all important for a person to understand the meaning of the video. Given these facts, we devised a system integrating continuous Chinese speech recognition (ASR), video caption text recognition (VOCR) and object/scene recognition (OR). The news program...
As the Session Initiation Protocol (SIP) becomes more and more the core of the communication networks convergence, there is urgent need to manage the critical problem of SIP service availability under extreme overload. This paper proposes a novel solution to control SIP overload. We demonstrate the efficiency of the approach compared with a well known SIP overload control algorithm. The solution builds...
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