The Internet technology has provided additional teaching strategies, with online education being one of the most exciting enhancements. A particular challenge for online education in engineering is how to extend the traditional hands-on laboratories to the Internet. Currently, there are two approaches to conducting labs online, virtual and remote labs. Virtual lab is based on software to simulate the lab environment while remote lab, by definition, is an experiment which is conducted and controlled remotely through the Internet. These experiments use real components or instrumentation at a different location from where they are being controlled or conducted. There are many emerging technologies which have been used to develop the virtual and remote laboratory. However, there are few papers that review the virtual and remote laboratory development. In this paper, a review of the different online delivery methods for virtual and remote laboratory development is presented. The open research issues and conclusion with possible future directions on the virtual and remote engineering laboratory development is also presented.

Concrete structures with various reinforcements, such as steel bars, composite material tendons, and recently steel plates, are commonly used in civil infrastructures. When an external force overcomes the strength of the bond between the reinforcement and the concrete, bond-slip will occur, resulting in a relative displacement between the reinforcing materials and the concrete. Monitoring bond health plays an important role in guaranteeing structural safety. Recently, researchers have recognized the importance of bond-slip monitoring and performed many related investigations. In this paper, a state-of-the-art review on various smart sensors based on piezoelectric effect and fiber optic technology, as well as corresponding techniques for bond-slip monitoring is presented. Since piezoelectric sensors and fiber-optic sensors are widely used in bond-slip monitoring, their principles and relevant monitoring methods are also introduced in this paper. Particularly, the piezoelectric-based bond-slip monitoring methods including the active sensing method, the electro-mechanical impedance (EMI) method and the passive sensing using acoustic emission (AE) method, and the fiber-optic-based bond-slip detecting approaches including the fiber Bragg grating (FBG) and the distributed fiber optic sensing are highlighted. This paper provides guidance for practical applications and future development of bond-slip monitoring.

Glass fiber-reinforced polymers (GFRPs) have received increasing attention in recent years due to their overall performance of light weight, low cost and corrosion resistance, and they are increasingly used as reinforcement in concrete structures. However, GFRP material has low elastic modulus and linear elastic properties compared with steel bars, which introduces different bonding characteristics between bars and concrete. Therefore, a reliable monitoring method is urgently needed to detect the bond slip in GFRP-reinforced concrete structures. In this paper, a piezoceramic-based active sensing approach is proposed and developed to find the debonding between a GFRP bar and the concrete structure. In the proposed method, we utilize PZT (lead zirconate titanate) as two transducers. One acts as an actuator which is buried in the concrete structure, and the other acts as a sensor which is attached to the GFRP bar by taking advantage of machinability of the GRRP material. Both transducers are strategically placed to face each other across from the interface between the GFRP bar and the concrete. The actuator provokes a stress wave that travels through the interface. Meanwhile, the PZT patch that is attached to the GFRP bar is used to detect the propagating stress wave. The bonding condition determines how difficult it is for the stress wave traveling through the interface. The occurrence of a bond slip leads to cracks between the bar and the concrete, which dramatically reduces the energy carried by the stress wave through the interface. In this research, two specimens equipped with the PZT transducers are fabricated, and pull-out tests are conducted. To analyze the active sensing data, we use wavelet packet analysis to compute the energy transferred to the sensing PZT patch throughout the process of debonding. Experimental results illustrate that the proposed method can accurately capture the bond slip between the GFRP bar and the concrete.

Many machine learning methods have been applied for short messaging service (SMS) spam detection, including traditional methods such as naïve Bayes (NB), vector space model (VSM), and support vector machine (SVM), and novel methods such as long short-term memory (LSTM) and the convolutional neural network (CNN). These methods are based on the well-known bag of words (BoW) model, which assumes documents are unordered collection of words. This assumption overlooks an important piece of information, i.e., word order. Moreover, the term frequency, which counts the number of occurrences of each word in SMS, is unable to distinguish the importance of words, due to the length limitation of SMS. This paper proposes a new method based on the discrete hidden Markov model (HMM) to use the word order information and to solve the low term frequency issue in SMS spam detection. The popularly adopted SMS spam dataset from the UCI machine learning repository is used for performance analysis of the proposed HMM method. The overall performance is compatible with deep learning by employing CNN and LSTM models. A Chinese SMS spam dataset with 2000 messages is used for further performance evaluation. Experiments show that the proposed HMM method is not language-sensitive and can identify spam with high accuracy on both datasets.

Flanged valves are ubiquitous in oil and gas pipeline networks. The valves help to both connect pipes together and control the flow of fluids. Depending on the location, the valve may experience high temperatures, high pressures, and corrosive agents, all of which degrade the integrity of the flange connection. Thus, flanged valves require regular inspection and maintenance. However, in cases where the valve is located in inaccessible areas, regular inspection can be difficult and costly. While certain methods are currently available for automatic inspection of flanged valves, they often suffer from impracticality issues, such as intrusiveness, unintuitive operation, or sensor fragility. Therefore, this paper introduces a sensing device that, as inspired by wearable technology, can be easily and noninvasively “worn” onto the flanged valve and performs measurements in real-time. The device is composed of piezoelectric lead zirconate titanate (PZT) transducers fortified by a layer of cushioning rubber and a metallic outer layer. This paper presents the design of the device, and verifies its performance using a 12-bolted flanged valve recovered from the field. The device is able to accurately track the tightness of the bolted connections. Unlike prior PZT-based monitoring methods, this device shows great promise for practical application.

The technology of harvesting energy from the natural environment can be used to overcome the energy limitation of wireless sensor networks. In this paper, we consider the problem of deploying energy-harvesting directional sensor networks for optimal target coverage. It involves the directional sensing coverage, communication route selection, and energy neutral operation. We formulate it as a mixed integer linear programming model, and propose three heuristics to solve it, i.e., a linear program-based heuristic (LPBH), a two-stage heuristic (TSH), and a sensing- and routing-integrated greedy heuristic (SRIGH). Their approximation upper bounds and time complexities are analyzed. Finally, we conduct extensive simulation experiments to evaluate and compare them. Simulation results show that TSH is the fastest one among them, but achieves the lowest success rate and solution quality. LPBH and SRIGH can achieve roughly equal success rate and solution quality, and LPBH is the most time-consuming.