Optimization and comparison of photonic crystal resonators for silicon microcantilever sensors

Microcantilever sensors have been known as a fundamental design used in force sensors, strain sensors and biochemical sensors. The fast-growing applications in nanoelectromechanical systems (NEMS) lead to strong demands in new sensing mechanism in order to downsize the sensing elements to nanometer scale. Photonic crystal (PC) based resonators have been investigated as promising solutions because the bandgap structure and resonator characteristics are extremely sensitive to the deformation and position shift of holes in PC resonators. In addition to the well-known nano-cavity resonator (NCR), we proposed hexagonal nano-ring resonators (NRR) of two different layout configurations. When a microcantilever under different force loads, both of the resonant wavelength and the resonant wavelength shift can be measured as a linear function of force load. The linear relationship between wavelength shifts and strain is observed as well. The minimum detectable force and detectable strain for NRR configuration 1 is derived as small as 0.0757 μN and 0.0023%. The outstanding sensing capability renders PC resonators as a promising nanomechanical sensing element to be integrated in various transducers for NEMS applications.     

Size effect on mechanical properties of TiO2 capped nanotubes investigated using in situ transmission electron microscopy

In situ transmission electron microscopy nanoindentation tests are used to measure the compressive fracture and mechanical properties of individual titanium oxide (TiO₂) capped nanotubes. The average critical loads ranged from 3.6 to 9.6 μN. Individual TiO₂ capped nanotubes with lengths of 8–10 μm were found to have Young’s modulus values of ~2.2–9.4 GPa and work energy values of ~3.1–6.6 × 10^?13 J. The results indicate that the Young’s modulus and tensile strength depend on capped nanotube length.     

Design of interval type-2 fuzzy sliding-mode controller

In this paper, an interval type-2 fuzzy sliding-mode controller (IT2FSMC) is proposed for linear and nonlinear systems. The proposed IT2FSMC is a combination of the interval type-2 fuzzy logic control (IT2FLC) and the sliding-mode control (SMC) which inherits the benefits of these two methods. The objective of the controller is to allow the system to move to the sliding surface and remain in on it so as to ensure the asymptotic stability of the closed-loop system. The Lyapunov stability method is adopted to verify the stability of the interval type-2 fuzzy sliding-mode controller system. The design procedure of the IT2FSMC is explored in detail. A typical second order linear interval system with 50% parameter variations, an inverted pendulum with variation of pole characteristics, and a Duffing forced oscillation with uncertainty and disturbance are adopted to illustrate the validity of the proposed method. The simulation results show that the IT2FSMC achieves the best tracking performance in comparison with the type-1 Fuzzy logic controller (T1FLC), the IT2FLC, and the type-1 fuzzy sliding-mode controller (T1FSMC).     

A Sensor Network Web Platform Based on WoT Technology

This study proposes a Web platform, the Web of Things (WoT), whose Internet of Things (IoT) architecture is used to develop the technology behind a new standard Web platform. When a remote sensor passes data to a microcontroller for processing, the protocol is often not known. This study proposes a WoT platform that enables the use of a browser in a mobile device to control a remote hardware device. An optimized code is written using an artificial intelligence-based algorithm in a microcontroller. Digital data convergence technology is adopted to process the packets of different protocols and place them on the Web platform for access by other mobile devices. The platform has high efficiency and cross-platform advantages, with no limitation on the operating system. Message queueing telemetry transport (MQTT) technology is used to simplify the original HTTP protocol. Assume that the mobile device is a subscriber, i.e., the controller, and a microcontroller that connects the sensing device is the publisher. The publishers and subscribers of MQTT need not know each other if they share a message broker. The intermediate agent role is much like a router. Publishers and subscribers do not need to interact, and publishers do not have to wait for subscriber confirmation to cause interactive permission be locked. Nor must publishers and subscribers be online at the same time, and they are free to choose when to get messages. The proposed WoT method is compared with the traditional IoT method regarding data transfer. The results show that the proposed method can save time in processing large amounts of data, as the traditional IoT method wastes time, especially in data format transfer.     

Static and dynamic minimum energy broadcast problem in wireless ad-hoc networks: A PSO-based approach and analysis

In this paper, we address the minimum energy broadcast (MEB) problem in wireless ad-hoc networks (WANETs). The researches in WANETs have attracted significant attentions, and one of the most critical issues in WSNs is minimization of energy consumption. In WANETs the packets have to be transported from a given source node to all other nodes in the network, and the objective of the MEB problem is to minimize the total transmission power consumption. A hybrid algorithm based on particle swarm optimization (PSO) and local search is presented to solve the MEB problem. A power degree encoding is proposed to reflect the extent of transmission power level and is used to define the particle position in PSO. We also analyze a well-known local search mechanism, r-shrink, and propose an improved version, the intensified r-shrink. In order to solve the dynamic MEB problem with node removal/insertion, this paper provides an effective simple heuristic, Conditional Incremental Power (CIP), to reconstruct the broadcast network efficiently. The promising results indicate the potential of the proposed methods for practical use.     

Preoperative localization procedures for initial surgery in primary hyperparathyroidism

BACKGROUND: Left ventricular hypertrophy (LVH) has been identified as a main target organ change resulting from hypertension, also being a long-term predictor of myocardial infarction, stroke and cardiovascular death. However, very few longitudinal studies exist following the development of LVH in the hypertensive process. METHODS: The present longitudinal study investigated a population based group of borderline hypertensive men (BHT, n = 66, diastolic blood pressure (BP) 85-94 mm Hg). M-mode echocardiography was performed at baseline and after 3 years, and anthropometrical data recorded. RESULTS: There was no increase in LVH indices over the 3-year period, while there was a statistically significant increase in aortic root dimension (P < 0.001), left atrial diameter in diastole (LADD, P < 0.001), left ventricular diameter in diastole (LVDD, P < 0.001) and peak systolic wall stress (PSWS, P < 0.01) and a significant decrease in left ventricular ejection time (LVET, P < 0.01). Baseline BP levels correlated to PSWS (P < 0.05) but not to LVH indices, whereas body mass index (BMI) correlated significantly to wall thickness (P < 0.05) and LV mass (P < 0.05). CONCLUSIONS: LVH indices did not increase over a 3-year period. However, there was a significant increase in aortic root dimension, LADD, LVDD and PSWS, and a significantly shortened LVET, suggesting that these changes precede any increase in LVH. Finally, BMI showed stronger correlation to LVH indices than did BP levels.     

An Open-Loop Computer-Based Drug Infusion System

This study reports the development of a computer-based infusion system and methodology to produce and maintain selected plasma concentrations. The method identifies pharmacokinetic infusion parameters for subjects from bolus injection response data, employs these values in control equations implemented by a portable microcomputer and computer-controlled infusion pump, and achieves and maintains selected stepwise drug levels by intravenous drug infusion. Infusion studies with four dogs and five humans resulted in correlation coefficients of 0.98 for the dogs and 0.94 for the humans, with rms errors in maintaining the drug concentration at the desired level of 13.4 and 19.3 percent, respectively. An analysis of error demonstrated that: 1) the control error was less than the value of the pharmacokinetic parameter estimation error in determining a single parameter value, 2) errors in several parameters can have cancelling or additive effects depending on their sign, and 3) an error in the sum of two of the model parameters (A and B) directly translates to equivalent time-independent error in the controlled level.     

Real-time triple product relighting using spherical local-frame parameterization

This paper addresses the problem of real-time rendering for objects with complex materials under varying all-frequency illumination and changing view. Our approach extends the triple product algorithm by using local-frame parameterization, spherical wavelets, per-pixel shading and visibility textures. Storing BRDFs with local-frame parameterization allows us to handle complex BRDFs and incorporate bump mapping more easily. In addition, it greatly reduces the data size compared to storing BRDFs with respect to the global frame. The use of spherical wavelets avoids uneven sampling and energy normalization of cubical parameterization. Finally, we use per-pixel shading and visibility textures to remove the need for fine tessellations of meshes and shift most computation from vertex shaders to more powerful pixel shaders. The resulting system can render scenes with realistic shadow effects, complex BRDFs, bump mapping and spatially-varying BRDFs under varying complex illumination and changing view at real-time frame rates on modern graphics hardware.     

Using commercial video games in flipped classrooms to support physical concept construction

Based on the flipped‐classroom model and the potential motivational and instructional benefits of digital games, we describe a flipped game‐based learning (FGBL) strategy focused on preclass and overall learning outcomes. A secondary goal is to determine the effects, if any, of the classroom aspects of the FGBL strategy on learning efficiency. Our experiments involved 2 commercial games featuring physical motion concepts: Ballance (Newton's law of motion) and Angry Birds (mechanical energy conservation). We randomly assigned 87 8th‐grade students to game instruction (digital game before class and lecture‐based instruction in class), FGBL strategy (digital game before class and cooperative learning in the form of group discussion and practice in class), or lecture‐based instruction groups (no gameplay). Results indicate that the digital games exerted a positive effect on preclass learning outcomes and that FGBL‐strategy students achieved better overall learning outcomes than their lecture‐based peers. Our observation of similar overall outcomes between the cooperative learning and lecture‐based groups suggests a need to provide additional teaching materials or technical support when introducing video games to cooperative classroom learning activities.     

An Efficient Value Predictor Dynamically Using Loop and Locality Properties

Value prediction, a technique to break data dependency, is important in enhancing instruction-level parallelism and processor performance. A new value predictor utilizing both the loop and locality properties of data values has been proposed in this paper to pursue desirable prediction accuracy at reasonable cost. The proposed value predictor, called the Dynamic Loop and Locality-based (DLL) predictor, makes predictions by dynamically practicing the loop or locality-based prediction policy according to the state. With certain simple designs, the DLL predictor gains prediction accuracy in an efficient way. To secure more comprehensive experimental evaluation of value predictors, a new performance measure, accuracy improvement per cost, briefed as the A/C ratio, is introduced in the paper. Simulation results show that, compared with other existing value predictors, the proposed DLL predictor produces better A/C ratios in almost all situations due to flexible application of different prediction policies and reduced cost.