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Remote sensing has much to gain from citizen sensing. This is particularly evident in relation to the provision of ground reference data for use in the training and testing stages of supervised image classification analyses used to generate thematic maps from remotely sensed data. Citizens are able to provide data over large geographical areas inexpensively, addressing potential problems connected...
As unmanned aerial systems (UASs) become ever more ubiquitous with National Airspace (NAS) commercial and civilian operations, test sites and proving grounds need to be developed and heavily researched. Small UASs are being used as remote sensing systems, on demand, at the personal level, thus “personal remote sensing” scientific data drones urgently need Ground Truthing Test Sites beyond compliance...
This paper addresses the problem of adaptive chemical detection, using the Receptor Density Algorithm (RDA), an immune inspired anomaly detection algorithm. Our approach is to first detect when and if something has changed in the environment and then adapt the RDA to this change. Statistical hypothesis testing is used to determine whether there has been concept drift in consecutive time windows of...
In the health care domain up to the 70% of the revenues can be due to the staff workload costs, which are rerouted to health care insurances and patients. Therefore, it is of paramount importance to determine how much of these costs are really due to the patient care. Some hospitals adopted Real Time Location System solutions in order to optimize staff workload. However, even though these systems...
In this paper we present a methodology as a proof-of-concept for recognizing fundamental movements of the human arm (extension, flexion and rotation of the forearm) involved in 'making-a-cup-of-tea', typical of an activity of daily-living (ADL). The movements are initially performed in a controlled environment as part of a training phase and the data are grouped into three clusters using k-means clustering...
Emulation of electric machines - during development or power train testing - is getting increased importance. While, in the beginning, the focus was mainly to act as an artificial load for converter tests, future requirements include realistic testing of dynamic response, harmonics and harsh failure scenarios. According to these needs, a universal, scalable converter system is described.
Sleep apnea is a common sleep disorder in which patient sleep patterns are disrupted due to recurrent pauses in breathing or by instances of abnormally low breathing. Current gold standard tests for the detection of apnea events are costly and have the addition of long waiting times. This paper investigates the use of cheap and easy to use sensors for the identification of sleep apnea events. Combinations...
Physical activity has a positive impact on people's well-being and it can decrease the occurrence of chronic disease. To date, there has been a substantial amount of research studies, which focus on activity recognition using accelerometer and gyroscope-based sensors. However, many of these studies adopt a single sensor approach and focus on proposing novel features combined with complex classifiers...
Advances in sensing, portable computing devices, and wireless communication has lead to an increase in the number and variety of sensing enabled devices (e.g. smartphones or sensing garments). Pervasive computing and activity recognition systems should be able to take advantage of these sensors, even if they are not always available or appear in runtime. These sensors can be integrated into an ensemble...
False positives are a common problem for interfaces that rely on gesture recognition. Often a gesture can seem fine in development but is found to trigger accidentally during an initial deployment of the interface, restarting development and increasing expense. In this work we introduce MAGIC 2.0, a technique for false positive prediction and prevention that can be used interactively during the interface...
This study concentrated on real-time monitoring of a worker using wearable-sensor-based activity recognition. An inertial measurement unit was attached to both wrists of the worker and, by using acceleration and angle speed information, the activities performed by the worker were recognized. Online recognition was done using the sliding window method to divide the data into two-second intervals, and...
Recognizing the human activities of daily living (ADL) is an important research issue in the pervasive environment. Activity recognition is treated as a classification problem and the multi-class classifier is often used. Though the multi-class classifier can obtain high classification accuracy, it can not detect the noise activities and unknown activities, and the system has no extendable recognition...
This paper analyzes the influence of amplitude error and quadrature error of Inductosyn on the measurement accuracy in detail, researches the detection and correction method of the two kinds of error, and proposes a multi-position error detection method. That is linearizing Nonlinear equations through search methods, measuring amplitude and quadrature errors by using the least squares fitting method,...
In many real applications such as target detection and classification, there exist severe overlaps between different classes due to various reasons. Traditional classifiers with crisp decision often produce high rates of mis-classifications for patterns in overlapping regions. In this paper, we propose to use soft decision strategy with an optimized overlapping region detection to address the overlapping...
In some machine learning problems, the dataset has multiple views which may be obtained using different sensors or applying different sampling techniques. These views may have sufficient or partial information about the target concept. In this paper, a method that we called parallel interacting multiview learning (PIML) is proposed in which the views interact during the training process using the...
The neural network based method of individual conversion characteristic identification of multisensor using reduced number of its calibration/testing results is proposed in this paper. The proposed method is based on reconstruction of surface points of multisensor conversion characteristic by modular neural network. Each neural network module reconstructs separate point of the surface. The simulation...
To achieve good generalization in supervised learning, the training and testing examples are usually required to be drawn from the same source distribution. In this paper, we propose a method to relax this requirement in the context of logistic regression. Assuming Dp and Da are two sets of examples drawn from two different distributions T and A (called concepts, borrowing a term from psychology),...
It has been promising to provide personalized services for improving our living environment in support of information technologies. Sitting is one of the natural actions in our daily life. We focus on sitting behavior as a cue for providing such services. We used a pressure sensor seat on a chair for identifying sitting postures. In the experiments, we classified nine postures, including leaning forward...
Soft errors caused by ionizing radiation have emerged as a major concern for current generation of CMOS technologies and the trend is expected to get worse. Soft error rate (SER) measurement, expressed as number of failures encountered per billion hours of device operation, is time consuming and involves significant test cost. The cost stems from having to connect a device-under-test to a tester for...
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