Optimization of machine flexibility in an ion plating cell

In 1970s, manufacturing system performance was heavily depended on productivity. Manufacturers only concentrated on increasing productivity by increasing the number of workforce. The concept of flexibility began to introduce into the industry since 1990s, manufacturers realized that flexibility was a better solution to improve productivity by responding the changing environment in manufacturing system. However, limited researches on machine flexibility in Ion Plating (IP) industry were studied, most of them have focused on product development and quality of coating. The aim of this paper is to determine the optimal level of machine flexibility in an Ion Plating Cell (IPC) to improve the entire system performance. A Machine Loading Sequencing (MLS) model based on multi-objectives Genetic Algorithms (GA) was developed. In the case study, industrial data of a precious metal finishing company has been input into the proposed Machine Loading Sequencing Genetic Algorithm (MLSGA) model. Different level of machine flexibility will be assigned into different machines to determine the optimum while the overall system performance (i.e. on-time delivery, quality of product and production cost) has been maximized. The results demonstrated that the machine flexibility level in IPC should be zero under the recent IP technology. However, when the quality of coating is improved, machine flexibility should be introduced. © 2004 IEEE.published_or_final_versio

In vivo manganese-enhanced MRI for visuotopic brain mapping

This study explored the feasibility of localized manganese-enhanced MRI (MEMRI) via 3 different routes of Mn(2+) administrations for visuotopic brain mapping of retinal, callosal, cortico-subcortical, transsynaptic and horizontal connections in normal adult rats. Upon fractionated intravitreal Mn(2+) injection, Mn enhancements were observed in the contralateral superior colliculus (SC) and lateral geniculate nucleus (LGN) by 45-60% at 1-3 days after initial Mn(2+) injection and in the contralateral primary visual cortex (V1) by about 10% at 2-3 days after initial Mn(2+) injection. Direct, single-dose Mn(2+) injection to the LGN resulted in Mn enhancement by 13-21% in V1 and 8-11% in SC of the ipsilateral hemisphere at 8 to 24 hours after Mn(2+) administration. Intracortical, single-dose Mn(2+) injection to the visual cortex resulted in Mn enhancement by 53-65% in ipsilateral LGN, 15-26% in ipsilateral SC, 32-34% in the splenium of corpus callosum and 17-25% in contralateral V1/V2 transition zone at 8 to 24 hours after Mn(2+) administration. Notably, some patchy patterns were apparent near the V1/V2 border of the contralateral hemisphere. Laminar-specific horizontal cortical connections were also observed in the ipsilateral hemisphere. The current results demonstrated the sensitivity of MEMRI for assessing the neuroarchitecture of the visual brains in vivo without depth-limitation, and may possess great potentials for studying the basic neural components and connections in the visual system longitudinally during development, plasticity, pharmacological interventions and genetic modifications.published_or_final_versio

Quality Of Life And Functioning Among Community-based Individuals Of Schizophrenia In Hong Kong

published_or_final_versio

An adaptive palette reordering method for compressing color-indexed image

Center for Multimedia Signal Processing, Department of Electronic and Information EngineeringRefereed conference paper2006-2007 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Characterization of piezoelectric ring used for wire bonding transducer application

Version of RecordPublishe

Reducing the complexity of multiscale error diffusion

2006-2007 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Psychometric Properties of the Traditional Chinese Version of the Child and Adolescent Needs and Strengths-Trauma Comprehensive

OBJECTIVE: To determine the internal consistency, construct validity, and scaling properties of the traditional Chinese version of the Child and Adolescent Needs and Strengths-Trauma Comprehensive (TC-CANS-Trauma). METHODS: 66 male and 62 female children, adolescents, and young adults aged 3 to 22 years who were referred to trauma treatment service were selected by convenience sampling. The original English version of the CANS-Trauma was translated to traditional Chinese by a medical professional, back-translated to English by a clinical psychologist, and then cross-checked by another psychologist to ensure consistency. Chinese wordings were adjusted to maintain the conceptual rather than literal meaning. Participants were assessed using the TC-CANS-Trauma as well as the traditional Chinese version of the Life Events Checklist (LEC), the Children's Impact of Event Scale-Revised (CHIES-R), the Strengths and Difficulties Questionnaire-Impact Component (SDQ-Impact), and the Parenting Sense of Competence (PSOC). Internal consistency of eight primary domains of the TC-CANS-Trauma was evaluated by Cronbach's alpha. Construct (convergent and divergent) validity of five of these domains with the LEC, the CHIES-R, the SDQ-Impact, and the PSOC was assessed. Rasch modelling was used to evaluate the scaling properties of the eight primary domains of the TC-CANS-Trauma. RESULTS: Internal consistency of the eight primary domains of the TC-CANS-Trauma was satisfactory, with Cronbach's alpha ranging from 0.63 to 0.90. Construct (convergent and divergent) validity of five of these domains with the LEC, the CHIES-R, the SDQ-Impact, and the PSOC was good. In Rasch modelling, most TC-CANS-Trauma domains showed good item separation values. Infit and outfit statistics of most domain items were <2 indicating good item fitness in their respective domains. For person separation, all domains of the TC-CANS-Trauma did not have a sufficient discriminability to identify high and low performers. CONCLUSIONS: The TC-CANS-Trauma is valid for comprehensive assessment of trauma-related domains among Hong Kong children and adolescents. Its ratings can be used to guide the levels of clinical intervention required. Clinicians are recommended to implement the TC-CANS-Trauma to facilitate trauma-informed practice in Hong Kong

Macro-approach of cell formation problem with consideration of machining sequence

Cellular Manufacturing System (CMS) which is based on the concept of Group Technology (GT) has been recognized as an efficient and effective way to improve the productivity in the factory. In recent years, there has been much effort done for continuing to improve CMS. Most researches concentrated on distinguishing the part families and machine cells either simultaneously or individually by considering of minimizing intercellular and intracellular part movements. However, fewer researches have studied the impact of the sequencing of machine cells. In light of this, the main aim of this present work is to study the impact of the sequencing of allocating the machine cells in minimizing intercellular part movement. The problem scope, which is also called as machine-part grouping problem (MPGP) together with the background of cell layout problem (CLP), has been identified. A mathematical model is formulated and part incidence matrix with operational sequence is often used. Since MPGP has been proved as an NP complete, genetic algorithm (GA) is employed as cell formation algorithms in solving this problem. © 2004 IEEE.published_or_final_versio

Modelling of nonlinear stochastic dynamical systems using neurofuzzy networks

Though nonlinear stochastic dynamical system can be approximated by feedforward neural networks, the dimension of the input space of the network may be too large, making it to be of little practical importance. The Nonlinear Autoregressive Moving Average model with eXogenous input (NARMAX) is shown to be able to represent nonlinear stochastic dynamical system under certain conditions. As the dimension of the input space is finite, it can be readily applied in practical application. It is well known that the training of recurrent networks using gradient method has a slow convergence rate. In this paper, a fast training algorithm based on the Newton-Raphson method for recurrent neurofuzzy network with NARMAX structure is presented. The convergence and the uniqueness of the proposed training algorithm are established. A simulation example involving a nonlinear dynamical system corrupted with the correlated noise and a sinusoidal disturbance is used to illustrate the performance of the proposed training algorithm.published_or_final_versio