Earticle

Archwire bending is conducted by orthodontist in orthodontic treatment. However, this procedure is boring and time-consuming. In order to reduce the dependence on human technology in archwire bending forming, decrease the labor intensity of dentists and technicians, and improve the degree of automation of the orthodontic process. This paper proposes to use robots to replace dentists for completing orthodontic wires bending. Quantitative model of orthodontic wires with canine eminace is established based on Power function model. On the basis of bending process analysis of orthodontic wires, the overall structure, bend die and archwire supporting part of archwire bending robot for orthodontic treatment is designed.

Based on analysis of the configuration and powertrain parameters of the series hybrid electric bus typically operating in certain Chinese city, this paper establishes simulation model of the series hybrid powertrain. The energy efficiency and fuel economy of the series hybrid electric bus are analyzed by energy flow method in the driving cycles of Chinese typical city, Zhuzhou city in Hunan province of China, and Hefei city in Anhui province of China. Simulation results show that, APU parts selection, braking system configuration and control of the series hybrid electric bus can be optimized. The fuel-saving ratios reach nearly 20% in all driving cycles.

The test platform plays an important role for the development of intelligent vehicles. In this work, we propose to design and build a miniature test model before building a real scene. The whole test system consists of the simulated traffic environment, the micro-intelligent vehicle and the visual information processing. Firstly, a micro- intelligent vehicle test platform applied to visual information perception is proposed. Secondly, some algorithms about traffic environmental element detection such as lane detection, traffic light and traffic signal recognition and obstacle detection are presented. The experiment validated the proposed approach. On the one hand, the main visual technologies of intelligent vehicles such as line detection, obstacle detection, and traffic signal recognition can be tested in this system; on the other hand, the test result can be used to evaluate and improve the design of the real test platform.

In this dissertation, we designed a kind of CMOS integrated precision acceleration detection system which is use high performance operation amplifier as the core. It was analysis directly as a low noise accelerometer and the principle of charge amplification. Detection circuit is based on the principle of time detection, which can be detected variation of the acceleration continuously in a successive time, and improving the detection accuracy. The input terminal of the circuit using sensitive charge amplifier to realize C-V conversion, which is effectively avoid the switch noise of detection principle. The whole circuit is designed and simulated based on 0.5μm CMOS process. The research result of Operational Amplifier module has shown that, the circuit’s the DC open-loop gain is 85.96dB, and its phase margin is 62.8°, and the effect input noise is 3.632HznV/. The research result of overall current has shown that, full scale range of the closed-loop system between ±2.5 V the voltage is ±30V. The detection sensitivity is 16.2mV/g, which is enough to conform the requirements of the low noise accelerometer.

The things to realize using the network system of ubiquitous sensors are situation perception and personalization services. To enhance performance of the situation perception, construct wireless networks with multi-sensors. In other to enhance the performance of the context awareness, temporary storage and utilization for the sensing data were proposed. The criteria to judge whether to use or not the sensing data reported from the sensor in the next time zones was presented by saving it temporarily, the data proved to be used in the next time zones should be recycled. On using by calling the Basic Probability Assignment saved, weights corresponding to the increment of the previous and present time zones should be added. Since then, the belief and uncertainty were calculated by using each focal element's BPA and through this, advanced information can be deduced rather than obtaining context information.

Shoulder joint rehabilitation exercises are considered one of the most effective treatments for reducing shoulder pain and improving the range of motion. In addition to regular supervision from professional rehabilitation staff, participation in home- based self-practice can enhance the effectiveness of treatment. Therefore, this study proposes an intelligent monitoring system for home-based self-rehabilitation. In this system, smart phones serve as the platform for integrating an accelerometer -based sensor network for monitoring the performance of rehabilitation exercises by patients with shoulder injuries. The developed sensor network comprises 2 accelerometer sensors and the built-in smart phone accelerometer that communicate using Bluetooth protocols. The following 5 monitoring exercises were included in this study: touch ear, use fingers to climb wall both facing and sideways to the wall, clockwise and counterclockwise pendulum circles, active-assisted front and side stretches, and raises hand from back. Shoulder rehabilitation activities are recognized by the Support Vector Machine algorithms and recorded on the smart phone. These records can be used by patients as a reference of their activity. The records can also be uploaded to the hospital server to assist physicians in monitoring the effectiveness of exercises. The proposed approach is low cost and can be extended to various monitoring targets by simply installing a new Android app.

In this paper, we propose the analytical approach for amplify-and-forward (AF) relay cooperative transmission in the presence of channel estimation error (CEE) generated by pilot symbol assisted-channel estimation (PSA-CE) schemes over quasi-static Rayleigh fading channels. Average symbol error rate (SER) is expressed as the well-known closed-form by using moment generating function (MGF) of the received signal-to-noise ratio (SNR), which quantifies the SNR penalty arising from CEE. Moreover, the effect of CEE on SER performance is verified based on the number of pilot symbols and the accuracy of the derived average SER expression of M-ary phase shift keying (MPSK) is confirmed by comparison with simulation results.