-Hsu Tan

Development and Evaluation of an RFID-Based Ubiquitous Learning Environment for Outdoor Learning.

Many issues have been identified in outdoor teaching, especially in places that lack the capacity to effectively present information about such subjects as historical relics, rare animals, and geological landscapes. This study proposes an Environment of Ubiquitous Learning with Educational Resources (EULER) based on radio frequency identification (RFID), the Internet, ubiquitous computing, embedded systems and database technologies to resolve such issues. A case study of natural science learning was conducted in classrooms and at the Guandu Nature Park in Taiwan. Participants included elementary school teachers and students. The results of the evaluation in this study show that the proposed EULER significantly improves student motivation and learning. Furthermore, the results of a post-study survey reveal that most student feedback is positive, further indicating the effectiveness of the EULER.

QR code and augmented reality-supported mobile english learning system

Mobile learning highly prioritizes the successful acquisition of context-aware contents from a learning server. A variant of 2D barcodes, the quick response (QR) code, which can be rapidly read using a PDA equipped with a camera and QR code reading software, is considered promising for context-aware applications. This work presents a novel QR code and handheld augmented reality (AR) supported mobile learning (m-learning) system: the handheld English language learning organization (HELLO). In the proposed English learning system, the linked information between context-aware materials and learning zones is defined in the QR codes. Each student follows the guide map displayed on the phone screen to visit learning zones and decrypt QR codes. The detected information is then sent to the learning server to request and receive context-aware learning material wirelessly. Additionally, a 3D animated virtual learning partner is embedded in the learning device based on AR technology, enabling students to complete their context-aware immersive learning. A case study and a survey conducted in a university demonstrate the effectiveness of the proposed m-learning system.

Performance of space-time block coded MB-OFDM UWB systems

This paper presents two MIMO-MB-OFDM UWB systems which include the space-time block coded MB-OFDM (STBC-MB-OFDM) UWB and convolutional space-time block coded MB-OFDM (CCSTBC-MB-OFDM) UWB. A series of experiments is conducted over the UWB channels with 2ISO and 2I2O configurations. Experimental results indicate that the 2I2O STBC-MB-OFDM is applicable to the real-time multimedia service in the general wireless digital home environment, and CCSTBC-MB-OFDM can be considered for the extremely adverse channel environment

Development of a Portable Linux-Based ECG Measurement and Monitoring System

This work presents a portable Linux-based electrocardiogram (ECG) signals measurement and monitoring system. The proposed system consists of an ECG front end and an embedded Linux platform (ELP). The ECG front end digitizes 12-lead ECG signals acquired from electrodes and then delivers them to the ELP via a universal serial bus (USB) interface for storage, signal processing, and graphic display. The proposed system can be installed anywhere (e.g., offices, homes, healthcare centers and ambulances) to allow people to self-monitor their health conditions at any time. The proposed system also enables remote diagnosis via Internet. Additionally, the system has a 7-in. interactive TFT-LCD touch screen that enables users to execute various functions, such as scaling a single-lead or multiple-lead ECG waveforms. The effectiveness of the proposed system was verified by using a commercial 12-lead ECG signal simulator and in vivo experiments. In addition to its portability, the proposed system is license-free as Linux, an open-source code, is utilized during software development. The cost-effectiveness of the system significantly enhances its practical application for personal healthcare.

Development and evaluation of an RFID-based e-restaurant system for customer-centric service

Traditional restaurant service is passive: waiters must interact with customers directly before processing their orders. However, a high quality customer-centered service system would actively identity customers, their favorite meals and their expenditure records. To achieve this goal, this study integrates radio frequency identification (RFID), wireless local area network (WLAN) and database technologies to develop an e-restaurant system for customer-centric service, which enables waiters to immediately identify customers via RFID-based membership cards and then actively provide customized services. The user interface of the proposed system is built with Visual C# 2005 and eMbedded Visual C++, and the database is built on Microsoft SQL Server 2005 for Server management and statistic reporting. The WLAN and RFID technologies are used to transmit real-time information of each dining table. To verify the effectiveness of the proposed system, a series of experiments was conducted in two restaurants. A questionnaire survey administrated to waiters and customers confirmed the effectiveness of the proposed e-restaurant system in providing customer-centric service. Furthermore, extensive interviews with restaurant owners revealed very positive feedback.

Clinical Verification of A Clinical Decision Support System for Ventilator Weaning

BackgroundWeaning is typically regarded as a process of discontinuing mechanical ventilation in the daily practice of an intensive care unit (ICU). Among the ICU patients, 39%-40% need mechanical ventilator for sustaining their lives. The predictive rate of successful weaning achieved only 35-60% for decisions made by physicians. Clinical decision support systems (CDSSs) are promising in enhancing diagnostic performance and improve healthcare quality in clinical setting. To our knowledge, a prospective study has never been conducted to verify the effectiveness of the CDSS in ventilator weaning before. In this study, the CDSS capable of predicting weaning outcome and reducing duration of ventilator support for patients has been verified.MethodsA total of 380 patients admitted to the respiratory care center of the hospital were randomly assigned to either control or study group. In the control group, patients were weaned with traditional weaning method, while in the study group, patients were weaned with CDSS monitored by physicians. After excluding the patients who transferred to other hospitals, refused further treatments, or expired the admission period, data of 168 and 144 patients in the study and control groups, respectively, were used for analysis.ResultsThe results show that a sensitivity of 87.7% has been achieved, which is significantly higher (p<0.01) than the weaning determined by physicians (sensitivity: 61.4%). Furthermore, the days using mechanical ventilator for the study group (38.41 ± 3.35) is significantly (p<0.001) shorter than the control group (43.69 ± 14.89), with a decrease of 5.2 days in average, resulting in a saving of healthcare cost of NT

Performance of particle swarm optimization techniques on papr reduction for OFDM systems

45,000 (US

Robust vector quantization for wireless channels

1,500) per patient in the current Taiwanese National Health Insurance setting.ConclusionsThe CDSS is demonstrated to be effective in identifying the earliest time of ventilator weaning for patients to resume and sustain spontaneous breathing, thereby avoiding unnecessary prolonged ventilator use and decreasing healthcare cost.

Using K-Nearest Neighbor Classification to Diagnose Abnormal Lung Sounds.

Partial transmit sequence (PTS) technique requires an exhaustive search over all combinations of allowed phase weighting factors, the search complexity increases exponentially with the number of sub-blocks. In this paper, a novel combing strategy that employs sub-block partition scheme and phase factors for PTS in orthogonal frequency division multiplexing (OFDM) system is proposed. We present an OFDM system, which through the use of sub-optimal PTS based on particle swarm optimization (PSO) algorithm, achieves low computation complexity to find optimum phase weighting factors and reduce the peak-to-average power ratio (PAPR). Furthermore, to work around potentially computational intractability, the proposed scheme exploits heuristics in consideration of both global and local exploration partial transmit sequence. Simulation results show that the proposed PSO-based PTS can efficiently find the optimum phase weighting factor, and can achieve the lower PAPR with moderate complexity.

Developing an Intelligent e-Restaurant With a Menu Recommender for Customer-Centric Service

This study focuses on two issues: parametric modeling of the channel and index assignment of codevectors, to design a vector quantizer that achieves high robustness against channel errors. We first formulate the design of a robust zero-redundancy vector quantizer as a combinatorial optimization problem leading to a genetic search for a minimum-distortion index assignment. The performance is further enhanced by the use of the Fritchman (1967) channel model that more closely characterizes the statistical dependencies between error sequences. This study also presents an index assignment algorithm based on the Fritchman model with parameter values estimated using a real-coded genetic algorithm. Simulation results indicate that the global explorative properties of genetic algorithms make them very effective in estimating Fritchman model parameters, and use of this model can match index assignment to expected channel conditions.