Advancements in using a machine design project for teaching introductory electrical engineering

Project-based learning is commonly used in teaching electrical/electronic engineering content. This paper analyses a proposed course that used a Rube Goldberg machine design project for introductory electrical engineering teaching. To facilitate students' learning, two main enhancements of the original course development are described: i) a refurnished project vehicle and new curriculum-framing questions have been proposed to assist students achieving the course's learning outcomes, and ii) tools for idea cultivation, design progress monitoring and design/learning collaboration technologies have been proposed to assist students to direct their learning. © 2013 IEEE.published_or_final_versio

Utility-Oriented Placement of Actuator Nodes with a Collaborative Serving Scheme for Facilitated Business and Working Environments

Places to be served by cyber-physical systems (CPS) are usually distributed unevenly over the area. Thus, different areas usually have different importance and values of serving. In other words, serving power can be excessive or insufficient in practice. Therefore, actuator nodes (ANs) in CPS should be focused on serving around points of interest (POIs) with considerations of “service utility.” In this paper, a utility-oriented AN placement framework with a collaborative serving scheme is proposed. Through spreading serving duties among correctly located ANs, deployment cost can be reduced, utility of ANs can be fully utilized, and the system longevity can be improved. The problem has been converted into a binary integer linear programming optimization problem. Service fading, 3D placements, multiscenario placements, and fault-tolerant placements have been modeled in the framework. An imitated example of a CPS deployment in a smart laboratory has been used for evaluations.published_or_final_versio

Building a smart laboratory environment at a university via a cyber-physical system

Contemporary activities in laboratories have become versatile and complicated, and can be significantly affected by the environment of the laboratory. Thus, a smart laboratory environment is needed to interpret and manipulate (implicit) environmental quantities, for improving and retaining the performance of laboratory activities. This paper presents a deployment of a cyber-physical system (CPS) gathering and acting on relevant information about physical quantities in laboratories. In particular, the proposed CPS can measure, analyze and regulate the thermal comfort. Improvements have been proposed to enhance the functionality of the system. Evaluations of an on-site deployment indicate the functionality of the proposed CPS. © 2013 IEEE.published_or_final_versio

VLSI macromodeling and signal integrity analysis via digital signal processing techniques

Linear macromodeling has been applied to high-frequency circuit simulations to accelerate the global interconnect system simulation process. By approximating tabulated structure response data, reduced macromodels can be generated. However, conventional macromodeling approaches suffer from numerical robustness and convergence problems. This paper aims to apply digital signal processing techniques to facilitate the macromodeling process. Besides improving the existing widely adopted framework (called VFz) through introducing a robust discrete-time domain (z-domain) computation, alternative macromodeling methodology (called VISA) has also been developed, which significantly simplifies the computation procedure. Furthermore, universal pre-processing technique (frequency warping) is introduced for a numerically favorable computation of the macromodeling process. These techniques have been shown to significantly improve the robustness and convergence of the modeling process.postprintProceedings of the International MultiConference of Engineers and Computer Scientists 2011 (IMECS 2011), Hong Kong, 16-18 March 2011. In Lecture Notes in Engineering and Computer Science, 2011, v. 2188-2189 n. 2, p. 1031-103

Integration of a wireless sensor network project for introductory circuits and systems teaching

This paper presents an integration of a wireless sensor network design project in an introductory course about circuits and systems. In the project, students will design a wireless sensor network that constitutes of sensors, for a creative surveillance application. Through a versatile project vehicle, project-oriented learning modules, a comprehensive assessment strategy and public learning communities, students can learn contemporary concepts of circuits and systems from the system perspective, as well as develop ability to design a basic electronic system. © 2013 IEEE.published_or_final_versio

Improved two-stream model for human action recognition

This paper addresses the recognitions of human actions in videos. Human action recognition can be seen as the automatic labeling of a video according to the actions occurring in it. It has become one of the most challenging and attractive problems in the pattern recognition and video classification fields. The problem itself is difficult to solve by traditional video processing methods because of several challenges such as the background noise, sizes of subjects in different videos, and the speed of actions. Derived from the progress of deep learning methods, several directions are developed to recognize a human action from a video, such as the long-short-term memory (LSTM)-based model, two-stream convolutional neural network (CNN) model, and the convolutional 3D model.In this paper, we focus on the two-stream structure. The traditional two-stream CNN network solves the problem that CNNs do not have satisfactory performance on temporal features. By training a temporal stream, which uses the optical flow as the input, a CNN can have the ability to extract temporal features. However, the optical flow only contains limited temporal information because it only records the movements of pixels on the x-axis and the y-axis. Therefore, we attempt to design and implement a new two-stream model by using an LSTM-based model in its spatial stream to extract both spatial and temporal features in RGB frames. In addition, we implement a DenseNet in the temporal stream to improve the recognition accuracy. This is in-contrast to traditional approaches which typically utilize the spatial stream for extracting only spatial features. The quantitative evaluation and experiments are conducted on the UCF-101 dataset, which is a well-developed public video dataset. For the temporal stream, we choose the optical flow of UCF-101. Images in the optical flow are provided by the Graz University of Technology. The experimental result shows that the proposed method outperforms the traditional two-stream CNN method with an accuracy of at least 3%. For both spatial and temporal streams, the proposed model also achieves higher recognition accuracies. In addition, compared with the state of the art methods, the new model can still have the best recognition performance

Low-cost global MPPT scheme for photovoltaic systems under partially shaded conditions

Maximum Power Point Tracking (MPPT) is a technique applied to improve the efficiency of power conversion in Photovoltaic (PV) systems. Under partially shadowed conditions, the Power-Voltage (P-V) characteristic exhibits multiple peaks and the existing MPPT methods such as the Perturb and Observe (P&O) are incapable of searching for the Global Maximum Power Point (GMPP). This paper proposes a low-cost on-line MPPT scheme to overcome this drawback. By using hybrid numerical searching process, the operating point approaches Local Maximum Power Points (LMPPs) gradually and the GMPP is caught by comparing all the LMPPs. Simulation results prove the effectiveness and correctness of the proposed method. © 2013 IEEE.published_or_final_versio

Haplotypes in the urotensin II gene and urotensin II receptor gene are associated with insulin resistance and impaired glucose tolerance

We studied single nucleotide polymorphisms (SNPs) and haplotypes in the urotensin-II (UTS2) and urotensin-II receptor gene (UTS2R) in Hong Kong Chinese (224 hypertensive and 306 normotensive unrelated subjects) and their relation to hypertension and the metabolic syndrome. For UTS2, the GGT haplotype (-605G, 143G and 3836T) was associated with higher plasma level of U-II and insulin, and higher homeostasis model assessment of insulin resistance index and β-cell function. For UTS2R, the AC haplotype (-11640A and -8515C) was associated with higher 2 h plasma glucose after a 75 g oral glucose load. Therefore, U-II and its receptor may play a role in insulin resistance. © 2006 Elsevier Inc. All rights reserved.postprin

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How can the R.E.N.A.L. nephrometry scoring system aid management of a solid renal mass?

OBJECTIVES. To investigate use of the R.E.N.A.L. nephrometry score in relation to the choice of treatment and postoperative complications for renal masses. DESIGN. Case series. SETTING. A tertiary referral hospital in Hong Kong. PATIENTS. Data of patients undergoing nephrectomy were collected retrospectively from a clinical database and analysed. A R.E.N.A.L. nephrometry score was allocated to each renal tumour by a blinded qualified radiologist, utilising computerised imaging systems. Patient demographics, choice of surgery (radical vs partial), and approaches (open vs minimally invasive) were analysed with respect to their R.E.N.A.L. score. RESULTS. In all, 74 patients were included during the study period, of which 38 underwent partial nephrectomy and 36 underwent radical nephrectomy. No differences between the groups were found with respect to patient demographics. There were significant differences between the partial and radical nephrectomy groups in terms of their mean nephrometry score (6.9 vs 9.3, P<0.001). The mean nephrometry sum was also significantly different in the open approach versus the minimally invasive approach in patients having partial nephrectomy (7.8 vs 6.0, P=0.001). There was no difference in the postoperative 90-day morbidity and mortality in the partial nephrectomy and radical nephrectomy groups. CONCLUSIONS. The R.E.N.A.L. nephrometry score of a renal mass correlated significantly with our choice of surgery (partial vs radical) and our approach to surgery (open vs minimally invasive surgery), particularly in the partial nephrectomy group. It does not, however, correlate with postoperative complications. The nephrometry score provides a useful tool for objectively describing renal mass characteristics and enhancing better communication for the operative planning directed at renal masses.published_or_final_versio