Cumulative index to NASA Tech Briefs, 1986-1990, volumes 10-14

Tech Briefs are short announcements of new technology derived from the R&D activities of the National Aeronautics and Space Administration. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This cumulative index of Tech Briefs contains abstracts and four indexes (subject, personal author, originating center, and Tech Brief number) and covers the period 1986 to 1990. The abstract section is organized by the following subject categories: electronic components and circuits, electronic systems, physical sciences, materials, computer programs, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Portable High Throughput Digital Microfluidics and On-Chip Bacteria Cultures

An intelligent, portable, and high throughput digital microfluidic (DMF) system is developed. Chapter 1 introduces microfluidics and DMF systems. In Chapter 2, a low-cost and high resolution capacitive-to-digital converter integrated circuit is used for droplet position detection. A field-programmable gate array FPGA is used as the integrated logic hub of the system for highly reliable and efficient control of the circuit. In this chapter a fast-fabricating PCB (printed circuit board) substrate microfluidic system is proposed. Smaller actuation threshold voltages than those previously reported are obtained. Droplets (3 µL) are actuated using 200 V, 500 Hz DC pulses. Droplet positions can be detected and displayed on a PC-based 3D animation in real time. The actuators and the capacitance sensing circuits are implemented on one PCB to reduce the size of the system. In Chapter 3, an intelligent EWOD (electrowetting on dielectric) top plate control system is proposed. The dynamic top plate is controlled by a piezoelectric (PZT) cantilever structure. A high resolution laser displacement sensor is used to monitor the deflection of the top plate. The gap height optimization and the harmonic vibration significantly improve the droplet velocity and decrease the droplet minimum threshold actuation voltage. The top plate vibration induced actuation improvement is magnitude and frequency dependent. 100 µm and 200 µm vibrations are tested at 25 Hz. Vibration frequencies at 5 Hz, 10 Hz, and 20 Hz are tested while the magnitude is 200 µm. Results show greater improvements are achieved at larger vibration magnitudes and higher vibration frequencies. With a vibrated top plate, the largest reduction of the actuation voltage is 76 VRMS for a 2.0 µl DI water droplet. The maximum droplet instantaneous velocity is around 9.3 mm/s, which is almost 3 times faster than the droplet velocity without top plate vibration. Liquid that has different hysteresis such as acetonitrile with various concentrations are used as a control to show its compatibility with the proposed DMF chip. Contact line depinning under top plate vibration is observed, which indicates the underlying mechanism for the improvements in actuation velocity and threshold voltage. The top plate control technique reported in this study makes EWOD DMF chips more reliable for point of care diagnostics. In Chapter 4, the mechanisms of the improvements were investigated by observing the detailed changes in the contact angle hysteresis using both parallel and nonparallel top plates. In Chapter 5, on-chip cell cultures are used for anti-biotic resistant bacteria detection. The passively dispensed on-chip cell cultures realize the isolated micro environment electrochemistry measurement, shorten the culturing time, and reduce the required sample volume. The design of the next generation ultra-portable DMF system is covered in the Appendix. Detailed technical notes and hardware design is covered in the Appendix. The proposed portable and high throughput DMF system with on-chip cell cultures have a great potential to change the standards for micro-environment culturing technologies, which will significantly improve the efficiency of actuation, sensing, and detecting performance of the DMF systems

Machine Learning in Sensors and Imaging

Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens

Antennas and Propagation

This Special Issue gathers topics of utmost interest in the field of antennas and propagation, such as: new directions and challenges in antenna design and propagation; innovative antenna technologies for space applications; metamaterial, metasurface and other periodic structures; antennas for 5G; electromagnetic field measurements and remote sensing applications

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

MATHEMATICAL MODELING OF THE PROGRAMING FIELD IN A NEURAL SWITCH USING THE SEMI-INFINITE COPLANAR ELECTRODE APPROXIMATION

The design and mathematical modeling of the programing electric field in a neural switch is carried out. The specified function for the switch is to operate as a synaptic processor behaving in an adaptive manner and suitable to be used as a compact programable device with other artificial neural network hardware. Modeling of the switch is carried out by means of complex mathematical analysis employing the Schwarz–Christoffel transform. The effect of inter-electrode separation on the field strength is analyzed in two dimensions. The realized power law function of the programing field is discussed and explained.Neural, mathematical modeling, synapse, memory, information processing