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This work develops a novel automatic irrigation system to implement the customized and accurate watering for an individual seedling. The system integrates the modules of visual recognition of the stem-leaf junction, identification of the stem-root junction as the watering point, and control of the spraying nozzle. The model of YOLOv3 is employed to screen the stem-leave junction of an orchid seedling, whose depth map then acquired by the method of Semi-Global Block Matching (SGBM) extracts the three-dimensional (3D) coordinates of the junction center. Next, the concept of leaf vector is introduced to identify the stem-root junction of the orchid seedling as the accurate watering point, which the spraying nozzle is controlled to reach for supplement of the specific amount of water. A number of experiments were conducted to verify the proposed irrigation system for orchid seedlings at different locations with various heights. The experimental results show that the rates of successful watering are 82% and 83.3% for the uni-pot and multi-pot orchid seedlings, respectively.

Recently, saving the cooling power in servers by controlling the fan speed has attracted considerable attention because of the increasing demand for high-density servers. This paper presents an optimal self-tuning proportional-integral-derivative (PID) controller, combining a PID neural network (PIDNN) with fan-power-based optimization in the transient-state temperature response in the time domain, for a server fan cooling system. Because the thermal model of the cooling system is nonlinear and complex, a server mockup system simulating a 1U rack server was constructed and a fan power model was created using a third-order nonlinear curve fit to determine the cooling power consumption by the fan speed control. PIDNN with a time domain criterion is used to tune all online and optimized PID gains. The proposed controller was validated through experiments of step response when the server operated from the low to high power state. The results show that up to 14% of a server’s fan cooling power can be saved if the fan control permits a slight temperature response overshoot in the electronic components, which may provide a time-saving strategy for tuning the PID controller to control the server fan speed during low fan power consumption.

This paper presents a new actuation mechanism to drive comb-drive actuators. An asymmetric configuration of the finger overlap was used to generate capacitive coupling for the actuation mechanism. When the driving voltages were applied on the stators, a voltage would be induced at the rotor due to the capacitive coupling. Then, an electrostatic force would be exerted onto the rotor due to the voltage differences between the stators and the rotor. The actuator’s static displacement and resonant frequency were theoretically analyzed. To verify the design, a comb-drive actuator with different initial finger overlaps, i.e., 159.3 μm and 48.9 μm on each side, was fabricated and tested. The results show that the actuator worked well using the proposed actuation mechanism. A static displacement of 41.7 μm and a resonant frequency of 577 Hz were achieved. Using the actuation mechanism, no electrical connection is required between the rotor and the outside power supply. This makes some comb-drive actuators containing heterogeneous structures easy to design and actuate.

Plasma process tools, which usually cost several millions of US dollars, are often used in the semiconductor fabrication etching process. If the plasma process is halted due to some process fault, the productivity will be reduced and the cost will increase. In order to maximize the product/wafer yield and tool productivity, a timely and effective fault process detection is required in a plasma reactor. The classification of fault events can help the users to quickly identify fault processes, and thus can save downtime of the plasma tool. In this work, optical emission spectroscopy (OES) is employed as the metrology sensor for in-situ process monitoring. Splitting into twelve different match rates by spectrum bands, the matching rate indicator in our previous work (Yang, R.; Chen, R.S. Sensors 2010, 10, 5703-5723) is used to detect the fault process. Based on the match data, a real-time classification of plasma faults is achieved by a novel method, developed in this study. Experiments were conducted to validate the novel fault classification. From the experimental results, we may conclude that the proposed method is feasible inasmuch that the overall accuracy rate of the classification for fault event shifts is 27 out of 28 or about 96.4% in success.

In this paper, a novel capacitive tactile sensing device has proposed and demonstrated to solve coupling problem within the normal force and shear force by the unique design of electrode shape. In addition, the tactile sensor was added in the measuring capability of torsion sensing compared with traditional capacitive sensor. The perceptive unit of tactile sensor, which was consist of five sensing electrodes to detect three-axial force. The complete tactile sensor composed of a top electrode, a bottom electrode, and a spacer layer. Each capacitive sensing unit comprised a pair of the concentric-shape but different size electrodes (top electrode and bottom electrode). In the future, the proposed tactile sensor can be utilized in the wearable devices, flexible interface, and bionic robotic skins.

The plasma process is often used in the fabrication of semiconductor wafers. However, due to the lack of real-time etching control, this may result in some unacceptable process performances and thus leads to significant waste and lower wafer yield. In order to maximize the product wafer yield, a timely and accurately process fault or abnormal detection in a plasma reactor is needed. Optical emission spectroscopy (OES) is one of the most frequently used metrologies in in-situ process monitoring. Even though OES has the advantage of non-invasiveness, it is required to provide a huge amount of information. As a result, the data analysis of OES becomes a big challenge. To accomplish real-time detection, this work employed the sigma matching method technique, which is the time series of OES full spectrum intensity. First, the response model of a healthy plasma spectrum was developed. Then, we defined a matching rate as an indictor for comparing the difference between the tested wafers response and the health sigma model. The experimental results showed that this proposal method can detect process faults in real-time, even in plasma etching tools.