Wah Ching Lee

A High Fuel Consumption Efficiency Management Scheme for PHEVs Using an Adaptive Genetic Algorithm

A high fuel efficiency management scheme for plug-in hybrid electric vehicles (PHEVs) has been developed. In order to achieve fuel consumption reduction, an adaptive genetic algorithm scheme has been designed to adaptively manage the energy resource usage. The objective function of the genetic algorithm is implemented by designing a fuzzy logic controller which closely monitors and resembles the driving conditions and environment of PHEVs, thus trading off between petrol versus electricity for optimal driving efficiency. Comparison between calculated results and publicized data shows that the achieved efficiency of the fuzzified genetic algorithm is better by 10% than existing schemes. The developed scheme, if fully adopted, would help reduce over 600 tons of CO2 emissions worldwide every day.

A speedy cardiovascular diseases classifier using multiple criteria decision analysis.

Each year, some 30 percent of global deaths are caused by cardiovascular diseases. This figure is worsening due to both the increasing elderly population and severe shortages of medical personnel. The development of a cardiovascular diseases classifier (CDC) for auto-diagnosis will help address solve the problem. Former CDCs did not achieve quick evaluation of cardiovascular diseases. In this letter, a new CDC to achieve speedy detection is investigated. This investigation incorporates the analytic hierarchy process (AHP)-based multiple criteria decision analysis (MCDA) to develop feature vectors using a Support Vector Machine. The MCDA facilitates the efficient assignment of appropriate weightings to potential patients, thus scaling down the number of features. Since the new CDC will only adopt the most meaningful features for discrimination between healthy persons versus cardiovascular disease patients, a speedy detection of cardiovascular diseases has been successfully implemented.

Traffic condition monitoring using weighted kernel density for intelligent transportation

Smart transportation is an application of intelligent system on transportation domain, expected to bring the society environmental and economic advantages. By combining with IoT techniques, the concept is being enhanced and raised to a system level. Numerous data are able to collect and effective analysis technique is needed. Here in this paper, we proposed a framework of employing IoT technique to construct a free time navigation system. The system aims at providing a real-time quantification of traffic conditions and suggests optimal route based on the information retrieved. The system can be basically separated into two major components: (i) the traffic condition estimation module and the (ii) real-time routing algorithm. In the first component, traffic conditions of roads will be estimated based the information collected from sensors installed on vehicles. Based on these location and speed information, the traffic condition can be quantified using a weighted kernel density estimation (WKDE) function. This function is a function of time and provides a real time insight of the overall traffic condition. By combining this information and the topological structure of the road network, a more accurate time consumption on each road can be estimated and hence enable a better routing.

A Study on the Reliability Optimization of LED-Lit Backlight Units in Mobile Devices

This paper studies the prevention of premature failures of LED backlights used in mobile devices that are subject to different use conditions. This is a vitally important topic for consumer mobile device manufacturers as the life expectancy of two identical devices from the same production line may vary substantially under different operating environments and use conditions. These differences are not addressed by traditional reliability assessment methods documented in many electronics handbooks. The paper outlines the use of a prognostics approach and condition-based monitoring for optimizing the reliability in the LED backlight display unit of mobile devices.

Sensitivity improved ZigBee RF receiver for a medical sensor

In this paper, a ZigBee based telemedicine monitoring system is presented with a 2.4 GHz ISM band sensitivity improved low-IF receiver for ZigBee sensor nodes. The receiver implemented is in 0.18 μm 1P6M RF CMOS process. The circuit is formed by a single-end dual band Low Noise Amplifier (LNA) that enhances the sensitivity of the ZigBee receiver by several dB - a key factor that extends the receiver range, a quadrature high gain and low noise current bleeding mixer and a quadrature parallel-coupled voltage-controlled oscillator (VCO). The receiver operates in the 2.4 GHz ISM band and complies with IEEE 802.15.4 (ZigBee) specifications. The circuit exhibits a low noise figure of 2.27 dB and dissipates only 14.6 mW with a 1.2 V supply voltage. This high sensitivity RF receiver is highly suitable for Telemedicine Monitoring System.

RSS-based localization algorithm for indoor patient tracking

The application of localization in healthcare system is a crucial topic which helps to locate the position of patent or the elderly in case urgency happens. From this aspect, a wireless technology is adopted to provide an efficient localization monitoring system for patients or the elderly in indoor area. The location of patients can be obtained through the developed algorithm. Fuzzy C-Means clustering (FCM) is one of the applicable techniques to locate the position of patients. However, low accuracy of FCM is the main problem. For this reason, the revised FCM localization algorithm, Calibrated Fuzzy C-Means Clustering Algorithm (C-FCM) is proposed in this investigation based on received signal strength (RSS) in wearable device. The proposed algorithm is evaluated through experiment and it has a percentage improvement of 14% compared with FCM.

ZigBee LNA design for wearable healthcare application

A fully integrated single-band 2.4 GHz low noise amplifier (LNA) is designed by using 0.18μm CMOS technology for ZigBee applications. For healthcare applications, high power consumption is not preferred. Increasing the sensitivity of receiver, therefore, could be a solution resulting in the use of LNA. The impedance expression is mathematically reconstructed into a quadratic equation and leads to the solutions by adding the LC tank in the matching networks. Besides, by using voltage controlled MOS varactor, the LC tanks at the input and output can be tuned. Such topology is convenient for calibrating the frequency drift due to the process variation and unexpected parasitics. The amplifier works at the supply voltage 1.2 V with current dissipation 10 mA. The gains achieved are over 15 dB at 2.4 GHz and the corresponding noise figure is about 2.1 dB.

High accuracy localization of long term evolution based on a new multiple carrier noise model.

A high accuracy localization technique using Long Term Evolution (LTE) based on a new and accurate multiple carrier noise model has been developed. In the noise consideration, the LTE multiple carriers phase noise has been incorporated so that a new and accurate noise model is achieved. An experiment was performed to characterize the phase noise of carriers at 2 GHz. The developed noise model was incorporated into LTE localization analysis in a high traffic area in Hong Kong to evaluate the accuracy of localization. The evaluation and analysis reveals that the new localization method achieves an improvement of about 10% accuracy comparing to existing widely adopted schemes.

A current bleeding mixer based on Gilbert-cell featuring LO amplification

A high gain and low noise mixer based on current bleeding topology is implemented. The high performance is attributed to the effect of current injection and local oscillator (LO) amplification. The conversion gain of the mixer is 17.5 dB at −14 dBm LO power and the noise figure is 10.5 dB. The proposed topology dramatically relieves the typically high power requirement of LO. The mixer is implemented by a 0.18-μm CMOS process. The operating frequency is 2.4 GHz with 10 MHz intermediate frequency. The circuit drains 12 mA current from a 1.5 V supply voltage.

Adaptive Hybrid Automatic Repeat Request (ARQ) with a Novel Packet Reuse Scheme for Wireless Communications

In wireless communication systems, selective repeat automatic repeat request (SR-ARQ) with code combining is a good solution for fading channels. However, performance of such scheme varies with different packet lengths. In this paper, we propose an adaptive hybrid automatic repeat request protocol (AH-ARQ) which continuously estimates throughput efficiency of different packet lengths with average number of packet transmission in different decoding conditions while combining received packets. By estimating channel condition and adapting packet length, throughput efficiency can be maximized. Other than former studies, throughput efficiencies of different packet lengths can be predicted without knowledge of channel condition such as Doppler frequency or vehicle speed which needs extra modification or device to the system because average bit error probability can be seen as constant for different packet lengths in the same channel condition. We also consider the influence of observation interval (OI) and difference between throughput efficiencies of different packet lengths (DTE). With optimized OI and DTE, simulation result shows that AH-ARQ can adaptively sense change of channel condition and maximize the throughput efficiency continuously in spite of its simplicity.