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Risk recognition training is an important training in construction companies to avoid work-related accidents. The existing risk recognition training is usually conducted on an illustration including explicit risks. However, it is difficult to express dynamic scenarios and surroundings of the scene due to the still illustration. In this study, a video based risk recognition training tool with an eye...
Anomaly in Online Social Network can be referred as abnormal or unexpected behavior which deviates from majority of users. Due to popularity of social networking sites such as Facebook, Twitter etc., malicious activities have increased in recent past. Anomaly detection has become an important area for researchers to be looked upon. This survey gives an overview of existing techniques, which is further...
Poor sitting postures influence one's health and can cause upper limb and neck disorder. Current solutions for siting posture recognition, however, are impractical due to intrusiveness, high cost or low generalization capability. Particularly, most of the existing solutions are chair-dependent, which are highly coupled with certain types of chairs. In this paper, we design Postureware, a smart cushion,...
There is a growing need for Vehicular Ad-hoc Networks (VANETs), in which vehicles communicate with each other (i. e., Vehicle to Vehicle, V2V) or with the infrastructure (i. e., Vehicle to Infrastructure, V2I) on a wireless basis. This paper presents an improved traffic monitoring system for VANET applications via a proposed security scheme. Specifically, the proposed model analyzes the monitored...
Biological information can easily be monitored by installing sensors in a lavatory bowl. Lavatories are usually shared by several people, so users need to be identified. Because of the need for privacy, using cameras, microphones, or scales is not appropriate. Though personal identification can be done using a touch panel, the user may forget to use it because the action is not necessary. In this...
Asthma is among the most common condition, and it has been reported that it is currently poorly controlled. In this work, wheeze sound were analysed to classify different levels of asthma severity. Wheeze signals were obtained from patients with three asthma severity levels, namely mild, moderate and severe asthma. The wheeze sounds detected were then used for a feature extraction process using mel-frequency...
This paper presents a new nonintrusive load identification method to disaggregate the target load in a typical commercial building. For this purpose, experiments were carried out in the laboratory implementing real load switching activity and power measurements were made with a smart meter. Nonintrusive load monitoring is performed by analysing the power signals obtained from the smart meter and detecting...
Error-related potentials (ErrP) have been increasingly studied in psychophysical experiments as well as for brain-machine interfacing. In the latter case, the generalisation capabilities of ErrP decoders is a crucial element to avoid frequent recalibration processes, thus increasing their usability. Previous studies have suggested that ErrP signals are rather stable across recording sessions. Also,...
We propose a novel e-rehabilitation system based on a commercial RGB-D device. Differently from exergaming approaches, clinical objectives scores of each specific body part involved in the exercise are computed. Subjects performances are sent to the physiotherapists in order to support and improve decisions and therapies.
Studies have revealed that non-adherence to prescribed medication can lead to hospital readmissions, clinical complications, and a host of other negative patient outcomes. Though many techniques have been proposed to improve patient adherence rates, they suffer from clear drawbacks such as high complexity, user burden, and low accuracy. In this paper, we propose a two step system for detecting user...
Electricity load monitoring of appliances has become an important task considering the recent economic and ecological trends. In this game, machine learning has an important part to play, allowing for energy consumption understanding, critical equipment monitoring and even human activity recognition. This paper provides a survey of current researches on Intrusive Load Monitoring (ILM) techniques....
Masqueraders are people who use somebody else's computer account. Masquerade attacks are serious in nature in the case of an insider, who can cause considerable damage to an organization. The insider attack detection problem remains one of the more important research areas requiring new insights to alleviate against this threat. Detection of these attacks is done by monitoring significant changes...
In this paper, an approach to e-Health service adaptation, based on input data analysis is presented. The developed approach can be applied to various services, not only e-Health, however, the motivating scenario presents interesting aspects of the problem and a challenge for efficient service adaptation. The adaptation is presented here as an extension of service composition approach, allowing for...
Pedestrian counting is widely used in civilian surveillance. In this paper, we present a people counting system which estimates the number of people across multiple cameras with partial overlapping Fields Of Views (FOVs). The main contributions of this paper include: 1) we propose a multi-object detection and tracking method by means of synthesizing the local-feature-level information into object-level...
We present a new method to detect seizure onsets of tonic-clonic epileptic seizures based on surface electromyography (sEMG) data. The proposed method is generic and based on a single channel making it ideal for a small detection or monitoring device. The sEMG signal is high-pass filtered with a Butterworth filter with a cut-off frequency of 150 Hz. The number of zero-crossings with a hysteresis of...
Integrated health management (IHM) is an advanced technology which integrated artificial intelligence with advanced test and information technologies. Having gone through fault detection, isolation and reconfiguration and immerged with the state of arts reasoning technologies, IHM monitors and controls the function of critical systems and components in order to ensure safe and efficient operation...
Video-based surveillance and measuring have been employed more and more widely in traffic monitoring system because of the rich information content contained in video. The vehicles need to be segmented from the video images, the result of vehicles segmentation using background subtraction is not only vehicles but also shadows of vehicles, a method of shadow removing based on texture analysis is presented...
Advances in technology have led to the development of various sensing, computing and communication devices that can be woven into the physical environment of our daily lives. Such systems enable on-body and mobile health-care monitoring, can integrate information from different sources, and can initiate actions or trigger alarms when needed. In this paper, the system architecture of a health-care...
The 3 most important issues for anomaly detection based intrusion detection systems by using data mining methods are: feature selection, data value normalization, and the choice of data mining algorithms. In this paper, we study primarily the feature selection of network traffic and its impact on the detection rates. We use KDD CUP 1999 dataset as the sample for the study. We group the features of...
A new approach to fuzzy rule-based systems structure identification in on-line (possibly real-time) mode is described in this paper. It expands the so called evolving Takagi-Sugeno (eTS) approach by introducing self-learning aspects not only to the number of fuzzy rules and system parameters but also to the number of antecedent part variables (inputs). The approach can be seen as online sensitivity...
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