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This publication presents papers and reprints of articles aimed at family members of persons with mental illnesses. After an introductory chapter, the second chapter reviews definitions of mental illness, and discusses what is known about medicating such conditions as well as the relationship of substance abuse to mental illness. The next chapter covers mental illness in a family context, including grieving, sibling reactions, communication skills, and crisis management. A chapter on advocacy groups is more specifically focused on resources available in Oregon. Chapter 5 covers the mental health service system, including a history of public mental health treatment in Oregon and descriptions of residential programs and community programs. Chapter 6 discusses the rights of families and clients, confidentiality, and estate planning. The last chapter covers voluntary and involuntary hospitalization. Appendices include a list of 35 recommended readings and a glossary of terms and acronyms. (PB)

Digital Virtual Manufacturing (DVM) is technology to facilitate effective product development and agile production by using a digital model to represent the physical and logical schema and the behavior of real manufacturing systems, including products, resources, processes and plant. For successful application of this technology, a digital virtual factory (DVF) functioning in a well-designed and integrated environment is essential. In this research, we constructed a sophisticated, DVF based on kinematic simulations and visualizations of a Korean automotive company's press shop by analyzing the entire business process and detailed activities of press engineering. We evaluated the geometries, structures, characteristics and motions of all plant and machinery in the press shop. The geometric model and related data of the virtual press shop were built and managed by a modeling standard defined in this paper. The manufacturing press machinery underwent virtual simulation to evaluate the kinematic motions, cycle time and component locations using geometric models and related data in order to perform interference checks and achieve productivity improvements. We expect this virtual press shop to achieve great savings in time and cost in many manufacturing preparation activities in the new car development process of automotive companies. [ABSTRACT FROM AUTHOR]

A Kernel PCA based fault diagnosis system for biological reaction in full-scale wastewater treatment plant was proposed using only common bio-chemical sensors such as ORP (Oxidation-Reduction Potential) and DO (Dissolved Oxygen). SBR (Sequencing Batch Reactor) is one of the most general sewage/wastewater treatment processes and, particularly, has an advantage in high concentration wastewater treatment like sewage wastewater. During the SBR operation, the operation status could be divided into normal status and abnormal status such as controller malfunction, influent disturbance and instrumental trouble. For the classification and diagnosis of these statuses, a series of preprocessing, dimension reduction using PCA, LDA, K-PCA and feature reduction was performed. Also, raw data obtained from SBR were transformed to synthetic data or fusion data and the performance were compared with each other. As the results, the fault recognition rate using fusion data showed the better result than that of raw data of [ORP] or [DO] and the combination method of K-PCA with LDA was superior to other methods such as PCA and LDA. [ABSTRACT FROM AUTHOR]

In this paper, the neural net pattern recognition equations were attempted to apply to speech recognition. The proposed method features a dynamic process of self-organization that has been proved to be successful in recognizing a depth perception in stereoscopic vision. This study showed that the dynamic process was also useful in recognizing human speech. In the processing, input vocal signals are first compared with standard models to measure similarities that are then given to the dynamic process of self-organization. The competitive and cooperative processes are conducted among neighboring input similarities, so that only one winner neuron is finally detected. In a comparative study, it showed that the proposed method outperformed the conventional Hidden Markov Models(HMM) speech recognizer under the same conditions. [ABSTRACT FROM AUTHOR]

This paper deals with applying Euclidian data distance based GA-PSO (Genetic-Particle Swarm Optimization) algorithm (EU-GA-PSO) to PID controller tuning of AVR (Automatic Voltage Regulator). Through this approach, global and local optimal solution can simultaneously achieved for tuning of controller parameter. [ABSTRACT FROM AUTHOR]

This paper deals with the GA-PSO (Genetic Algorithm-Particle Swarm Optimization) based vector control for loss minimization operation of induction motor. It is estimated that more than around 50% of the world electric energy generated is consumed by electric machines such as induction motor, DC motor. So, improving efficiency in electric drives is important and control strategy for minimum energy loss is needed as one of optimal operation strategy. In this paper, vector control approach is suggested for an optimal operation of induction motor using GA-PSO tuning method through simulation. [ABSTRACT FROM AUTHOR]

Chapter 39 of the book "Critical Decisions in Periodontology" is presented. It cites the need or desirability of referring a patient with complex dental problem to a periodontist. Ways on how practitioners go about deciding what should be done are offered through a decision tree presented. Several commonly available additional readings are also provided for further details.