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The classification of different odontocetes using écholocation clicks plays a significant role in tracking and detecting animals for research and protection purposes. Echolocation clicks were detected by an automatic method based on the Teager-Kaiser Energy Operator (TKEO). Then, these clicks were represented by their FFT magnitude spectrum. To reduce the influence of high similar clicks among species,...
In the spring of 2013, Alberta experienced significant flooding. According to the government of Alberta, this flood was “the largest and most expensive natural disaster in Alberta's history” [1]. Siksika Nation was severely impacted, with almost 170 homes devastated by the flood [2]. Recovery was slow, with many families left in temporary housing or without power for several years. A community engagement...
Service-learning has been proven to be a high-impact educational pedagogy in many disciplines. It addresses human, and community needs through engaging in community activities. With professional engineering expertise, integrating engineering into service-learning not only can make particularly impactful community service, especially in developing countries where engineering expertise is not always...
Faster R-CNN (R corresponds to “Region”) which combined the RPN network and the Fast R-CNN network is one of the best ways to object detection of R-CNN series based on deep learning. The proposal obtained by RPN is directly connected to the ROI Pooling layer, which is a framework for CNN to achieve end-to-end object detection. The feasibility of Faster R-CNN implementation of ResNet101 network and...
We propose a simple, yet powerful regularization technique that can be used to significantly improve both the pairwise and triplet losses in learning local feature descriptors. The idea is that in order to fully utilize the expressive power of the descriptor space, good local feature descriptors should be sufficiently “spread-out” over the space. In this work, we propose a regularization term to maximize...
Companies and public entities administer customer expectation and satisfaction surveys to identify business problems. However, devising and analyzing questionnaires is burdensome for investigators, and answering questionnaires imposes a burden on customers. Here, to address these problems, we attempt to estimate customer expectation and satisfaction using sensing technology. We hypothesize that satisfaction...
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...
The supervision of rehabilitation exercises is crucial for a successful therapy. Due to a lack of therapists, technical assistance systems have recently come into focus to assist patients during their exercises. Latest research proved that characteristic motion errors can be detected by using the Kinect skeleton joints in connection with Incremental Dynamic Time Warping (IDTW) and machine learning...
Nowadays, people have to face many challenges In order to become familiar with all the functionalities of electronical devices. The training process becomes thus essential, especially when we are referring to consumer electronics created for people with disabilities. Our paper presents the importance of training visually impaired people for an advanced sensory substitution device. By using the advantages...
Our research is initially motivated by a conversation we had with a group of cyber security analysts that are responsible for monitoring enterprise security at a large corporation who were experiencing day-to-day operational burdens. As a result, this paper focuses on the design and implementation of an Intelligent Cyber Security Assistant (ICSA) architecture that would provide intelligent assistance...
Many stroke survivors experience motor deficits. Rehabilitation is important for the maintenance and recovery of motor functions for activities of daily living. Motivated patients tend to show better rehabilitation effects. In this study, motor function was scored using the Simple Exercise Machine for Upper Limbs (SEMUL) rehabilitation system for upper limbs and the trainees were given feedback on...
The implementation of any project requires not only the development of project documents: the criteria for the project success, WBS-structure, the Matrix of Responsibilities, the budget, the Gantt diagram, etc., but also an unambiguous understanding of all these documents by all participants in the project process: stakeholders, project manager and movable context. As practice shows, this unambiguous...
The paper considers modern trends in the development of smart education in Europe and Asia. Various approaches to the management of smart education in universities are discussed. The specifics of the competence approach's application and distance formation of the training policy at Universities are analyzed. The case of the use of the distance education program in smart education is given based on...
This paper proposed a monocular vehicle detection for forward collision warning system. We use the active-learning framework to train a cascade classifier and use a two steps vehicle detection. We used five test data to quantify our detection performance, analyzing the two-stage vehicle detection improvement, and the overall detection rate and the false detection rate. In a good light condition, the...
Cognitive rehabilitation has been proposed as an alternative treatment for Alzheimer's disease (AD) as it helps to preserve brain functionality. However, gains of cognitive training or rehabilitation may be eliminated due to cognitive overload and mental fatigue. This paper reports the development of a functional near-infrared spectroscopy (fNIRS) — brain-computer interface (BCI) that can adjust task...
Deep structured of Convolutional Neural Networks (CNN) has recently gained intense attention in development due to its good performance in object recognition. One of the crucial components in CNN is the learning mechanism of weight parameters through backpropagation. In this paper, stochastic diagonal Approximate Greatest Descent (SDAGD) is proposed to train weight parameters in CNN. SDAGD adopts...
Stochastic Diagonal Approximate Greatest Descent (SDAGD) is proposed to manage the optimization in two stages, (a) apply a radial boundary to estimate step length when the weights are far from solution, (b) apply Newton method when the weights are within the solution level set. This is inspired by a multi-stage decision control system where different strategies is used at different conditions. In...
Accurate dialect identification technique helps in improving the speech recognition systems that exist in most of the present day electronic devices and is also expected to help in providing new services in the field of e-health and telemedicine which is especially important for older and homebound people. The accuracy of a dialect identification system is highly dependent on its speech corpora. Therefore,...
This paper presents a new discriminative learning framework to associate the relationship between the objects and the words in an image and perform template matching scheme for complex association patterns. The problem is first formulated as a bipartite graph matching problem. Thereafter, structural support vector machine (SVM) is employed to obtain the optimal compatibility function to encode the...
Several technical challenges should be taken into consideration when setting up hands-on laboratories, workshops and projects while the educational service providers need powerful, effective, stable and easy-to-use systems. In order to meet those requirements, such systems are designed and deployed as affordable services that request stability, reliability, availability, autonomy and resilience. This...
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