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"Ling, S. H"
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Electrocardiographic Signals and Swarm-Based Support Vector Machine for Hypoglycemia Detection
Cardiac arrhythmia relating to hypoglycemia is suggested as a cause of death in diabetic patients. This article introduces electrocardiographic (ECG) parameters for artificially induced hypoglycemia detection. In addition, a hybrid technique of swarm-based support vector machine (SVM) is introduced for hypoglycemia detection using the ECG parameters as inputs. In this technique, a particle swarm optimization (PSO) is proposed to optimize the SVM to detect hypoglycemia. In an experiment using medical data of patients with Type 1 diabetes, the introduced ECG parameters show significant contributions to the performance of the hypoglycemia detection and the proposed detection technique performs well in terms of sensitivity and specificity.
Journal Article
Computational intelligence and its applications
This book focuses on computational intelligence techniques and their applications — fast-growing and promising research topics that have drawn a great deal of attention from researchers over the years. It brings together many different aspects of the current research on intelligence technologies such as neural networks, support vector machines, fuzzy logic and evolutionary computation, and covers a wide range of applications from pattern recognition and system modeling, to intelligent control problems and biomedical applications.
eBook
An Improved Genetic Algorithm with Average-bound Crossover and Wavelet Mutation Operations
This paper presents a real-coded genetic algorithm (RCGA) with new genetic operations (crossover and mutation). They are called the average-bound crossover and wavelet mutation. By introducing the proposed genetic operations, both the solution quality and stability are better than the RCGA with conventional genetic operations. A suite of benchmark test functions are used to evaluate the performance of the proposed algorithm. Application examples on economic load dispatch and tuning an associative-memory neural network are used to show the performance of the proposed RCGA.
Journal Article
Study on micro hot embossing of low temperature co-firable ceramic green substrates
Multi-layered ceramic substrates with embedded micro patterns are becoming increasingly important, for example, in harsh environment electronics, enabling microsystems and microfluidic devices. Fabrication of these embedded micro patterns, such as micro channels, cavities and vias, is a challenge. This study focuses on the process aspects of patterning micro features on low temperature co-firable ceramic (LTCC) green substrates using micro hot embossing. Green ceramic tapes that possessed near-zero shrinkage in the
x
–
y
plane were used, six layers of which were stacked and laminated as a substrate. The process parameters that impact on the embossing fidelity were investigated and optimized in this study. Micro features with channel-width as small as several micrometers were formed on green ceramic substrates. The dynamic thermo-mechanical analysis indicated that extending the holding time at a certain temperature range would harden the substrates with little effect on improving the embossing fidelity. Ceramic substrates with embossed micro patterns were obtained after co-firing; the shrinkage ratios of the embossed depth and channel-width were 8–15 and 12–17%, respectively. The changes of pitches between two embossed channels were within ±1.0% due to the interlocking effect of the ceramic tapes.
Journal Article
Input-dependent neural network trained by real-coded genetic algorithm and its industrial applications
This paper presents an input-dependent neural network (IDNN) with variable parameters. The parameters of the neurons in the hidden nodes adapt to changes of the input environment, so that different test input sets separately distributed in a large domain can be tackled after training. Effectively, there are different individual neural networks for different sets of inputs. The proposed network exhibits a better learning and generalization ability than the traditional one. An improved real-coded genetic algorithm (RCGA) Ling and Leung (Soft Comput 11(1):7–31, 2007) is proposed to train the network parameters. Industrial applications on short-term load forecasting and hand-written graffiti recognition will be presented to verify and illustrate the improvement.
Journal Article
Application of a modified neural fuzzy network and an improved genetic algorithm to speech recognition
This paper presents the recognition of speech commands using a modified neural fuzzy network (NFN). By introducing associative memory (the tuner NFN) into the classification process (the classifier NFN), the network parameters could be made adaptive to changing input data. Then, the search space of the classification network could be enlarged by a single network. To train the parameters of the modified NFN, an improved genetic algorithm is proposed. As an application example, the proposed speech recognition approach is implemented in an eBook experimentally to illustrate the design and its merits.
Journal Article
End-of-life practices in Hong Kong intensive care units: results from the Ethicus-2 study
The need for end-of-life care is common in intensive care units (ICUs). Although guidelines exist, little is known about actual end-of-life care practices in Hong Kong ICUs. The study aim was to provide a detailed description of these practices.
This prospective, multicentre observational sub-analysis of the Ethicus-2 study explored end-of-life practices in eight participating Hong Kong ICUs. Consecutive adult ICU patients admitted during a 6-month period with life-sustaining treatment (LST) limitation or death were included. Follow-up continued until death or 2 months from the initial decision to limit LST.
Of 4922 screened patients, 548 (11.1%) had LST limitation (withholding or withdrawal) or died (failed cardiopulmonary resuscitation/brain death). Life-sustaining treatment limitation occurred in 455 (83.0%) patients: 353 (77.6%) had decisions to withhold LST and 102 (22.4%) had decisions to withdraw LST. Of those who died without LST limitation, 80 (86.0%) had failed cardiopulmonary resuscitation and 13 (14.0%) were declared brain dead. Discussions of LST limitation were initiated by ICU physicians in most (86.2%) cases. Shared decision-making between ICU physicians and families was the predominant model; only 6.0% of patients retained decision-making capacity. Primary medical reasons for LST limitation were unresponsiveness to maximal therapy (49.2%) and multiorgan failure (17.1%). The most important consideration for decision-making was the patient's best interest (81.5%).
Life-sustaining treatment limitations are common in Hong Kong ICUs; shared decision-making between physicians and families in the patient's best interest is the predominant model. Loss of decision-making capacity is common at the end of life. Patients should be encouraged to communicate end-of-life treatment preferences to family members/surrogates, or through advance directives.
Journal Article
Green fluorescent protein-tagged Edwardsiella tarda reveals portal of entry in fish
The application of green fluorescent protein (GFP) to identify the portal(s) of entry of bacterial pathogens in animal hosts was studied using the fish pathogen Edwardsiella tarda and blue gourami, Trichogaster trichopterus. An immersion challenge model was utilized to mimic natural infection conditions in fish. Gastrointestinal tract, gills and the body surface of fish were found to be the sites of entry of virulent E. tarda (PPD130/91) by histological and infection kinetics studies. On the other hand, avirulent E. tarda (PPD125/87) was mainly found in the gastrointestinal tract, and the bacterial population in tissue declined over a period of 7 days.
Journal Article