Design of BOM configuration for reducing spare parts logistic costs

This paper proposes an approach to reduce the total operational cost of a spare part logistic system by appropriately designing the BOM (bill of material) configuration. A spare part may have several vendors. Parts supplied by different vendors may vary in failure rates and prices – the higher the failure rate, the lower the price. Selecting vendors for spare parts is therefore a trade-off decision. Consider a machine where the BOM is composed of s critical parts and each part has k vendors. The number of possible BOM configurations for the machine is then k^s. For each BOM configuration, we can use OPUS10 (proprietary software) to calculate an optimum inventory policy and its associated total logistic cost. Exhaustively searching the solution space by OPUS10 can yield an optimal BOM configuration; however, it may be formidably time-consuming. To remedy the time-consuming problem, this research proposes a GA-neural network approach to solve the BOM configuration design problem. A neural network is developed to efficiently emulate the function of OPUS10 and a GA (genetic algorithm) is developed to quickly find a near-optimal BOM configuration. Experiment results indicate that the approach can obtain an effective BOM configuration efficiently.     

A Fuzzy Ontological Knowledge Document Clustering Methodology

This correspondence presents a novel hierarchical clustering approach for knowledge document self-organization, particularly for patent analysis. Current keyword-based methodologies for document content management tend to be inconsistent and ineffective when partial meanings of the technical content are used for cluster analysis. Thus, a new methodology to automatically interpret and cluster knowledge documents using an ontology schema is presented. Moreover, a fuzzy logic control approach is used to match suitable document cluster(s) for given patents based on their derived ontological semantic webs. Finally, three case studies are used to test the approach. The first test case analyzed and clustered 100 patents for chemical and mechanical polishing retrieved from the World Intellectual Property Organization (WIPO). The second test case analyzed and clustered 100 patent news articles retrieved from online Web sites. The third case analyzed and clustered 100 patents for radio-frequency identification retrieved from WIPO. The results show that the fuzzy ontology-based document clustering approach outperforms the K-means approach in precision, recall, F-measure, and Shannon's entropy.     

NMR microscopy of single neurons at 500 MHZ

Previous NMR microimaging studies at 360 MHz have demonstrated a clear differentiation between the nucleus and cytoplasm in isolated single neurons. In particular, theT ₂ of the cell nucleus is 2.5 times larger than that of the cytoplasm. In order to determine the magnitude of possibleT ₂ ^* influences on these observations, images of single cells have been obtained at 500 MHz using spin-echo and line-narrowing sequences. Comparison of the images acquired by the two sequences, and of the spin-echo images at 360 and 500 MHz, imply that anyT ₂ ^* contributions are relatively small. Consequently, the measuredT ₂ differences in spin-echo imaging represent a true difference in theT ₂ relaxation in the two cellular compartments.     

Pulmonary infiltrates in neutropenic patients with acute leukemia during chemotherapy: outcome and prognostic factors

STUDY OBJECTIVE: To determine predictors of mortality from pulmonary infiltrates in neutropenic patients with acute leukemia during chemotherapy, and the significance of those factors related to the underlying malignancy and its therapy as well as of those related to the severity of the illness associated with pulmonary infiltrates. DESIGN: A historical cohort study. SETTING: A university teaching hospital and tertiary referral center. PATIENTS AND METHODS: Overall, 53 patients with neutropenia during chemotherapy and with first episodes of pulmonary infiltrates during a 4-year period were studied. Prognostic analysis included 38 variables. Multivariate analyses were performed by logistic regression. RESULTS: The survival rate from pneumonia was 57% (30/53). The following eight parameters were significantly associated with death in univariate analysis: comorbidity present; development of "late" pulmonary infiltrates (> or = 14 days after hospital admission); heart rate > or = 100 beats/min; a ratio heart rate/systolic blood pressure (HR/SBP) > or = 1.2; urea nitrogen > 7 mmol/L; radiographic score > or = 3; neutropenia < 1.0x10(9)/L at the treatment end point; and failed complete remission. In a multivariate model including only parameters available at diagnosis of pulmonary infiltrates, the presence of a ratio HR/SBP > or = 1.2 and of a radiographic score > or = 3 remained independently associated with death. In a second model also including the evolutionary parameter neutropenia < or = 1.0x10(9)/L at the treatment end point, both parameters remained significant together with neutropenia <1.0x 10(9)/L at the treatment end point. The presence of a ratio HR/SBP > or = 1.2 was a strong marker of early death. CONCLUSION: Both therapy- and malignancy-associated neutropenia as well as the severity of illness associated with pulmonary infiltrates are independent prognostic factors. Patients with a ratio HR/SBP > or = 1.2 at diagnosis of pulmonary infiltrates suffer from potentially reversible acute illness, are at risk for early death and, therefore, may be appropriate candidates for treatment in an ICU.     

The artificial heart and neuromonitoring? Technical and clinical aspects

There is a steady progress in the development of artificial heart and circulatory assist devices. There is also no doubt that further advances in energy systems, materials, and electronics will provide for smaller and more reliable electrically driven blood pumps, but the present engineering design appears to be adequate to provide devices satisfactory for initial clinical use. Due to problems in the availability of suitable donor hearts, the concept of replacing the natural heart with an artificial heart as a "bridge to transplantation" has gained attention in recent years. The present paper shows technical and clinical aspects of multivariable electrophysiologic neuromonitoring in a patient with an artificial heart assist device in the intensive care unit. The data (EEG, 40 Hz brain oscillations, brainstem auditory- and somatosensory evoked potentials) are discussed with respect to the influence of the artificial heart on their quality and reliability. Reasons for artifacts and problems of interpretation are shown.     

Polarization-Dependent Periodic Pulse Oscillation in a Diode-Laser-Pumped and Intracavity Frequency-Doubled Nd:YVO 4 Laser

We demonstrate that two cross-polarized longitudinal modes can have 50% higher conversion efficiency than two parallel-polarized longitudinal modes in a diode-laser-pumped and intracavity frequency-doubled Nd:YVO(4) laser when operated under periodic pulse oscillation. Through simulations of the rate equations for primary frequency intensities and gains, we also verify that this effect can be attributed to gain competition and complementary conversion coefficient between second-harmonic and sum-frequency generations.     

Single- and dual-ion-beam sputter deposition of titanium oxide films

The optical properties and the surface morphologies of single-ion-beam sputtering (SIBS) and dual-ion-beam sputtering (DIBS) depositions of titanium oxide films are investigated and compared. In the DIBS process, the ion-assisted deposition by the voltage of a low ion beam ranged from 50 to 300 V at a 0% and 44% oxygen percentage. Cosputtering with materials of Si, SiO(2) (fused silica), and Al is also utilized in SIBS to improve amorphous-structure film. For the low-absorption and surface-roughness film, the optimum deposition condition of DIBS and postdeposition baking temperature for SIBS and DIBS are essential to the process.     

Independent spanning trees vs. edge-disjoint spanning trees in locally twisted cubes

Fault-tolerant broadcasting and secure message distribution are important issues for numerous applications in networks. It is a common idea to design multiple spanning trees with a specific property in the underlying graph of a network to serve as a broadcasting scheme or a distribution protocol for receiving high levels of fault-tolerance and of security. A set of spanning trees in a graph is said to be edge-disjoint if these trees are rooted at the same node without sharing any common edge. Hsieh and Tu [S.-Y. Hsieh, C.-J. Tu, Constructing edge-disjoint spanning trees in locally twisted cubes, Theoretical Computer Science 410 (2009) 926-932] recently presented an algorithm for constructing n edge-disjoint spanning trees in an n-dimensional locally twisted cube. In this paper, we prove that indeed all spanning trees constructed by their algorithm are independent, i.e., any two spanning trees are rooted at the same node, say r, and for any other node v≠r, the two different paths from v to r, one path in each tree, are internally node-disjoint.     

Local contrast enhancement and adaptive feature extraction for illumination-invariant face recognition

Recognizing human faces in various lighting conditions is quite a difficult problem. The problem becomes more difficult when face images are taken in extremely high dynamic range scenes. Most of the automatic face recognition systems assume that images are taken under well-controlled illumination. The face segmentation as well as recognition becomes much simpler under such a constrained condition. However, illumination control is not feasible when a surveillance system is installed in any location at will. Without compensating for uneven illumination, it is impossible to get a satisfactory recognition rate. In this paper, we propose an integrated system that first compensates uneven illumination through local contrast enhancement. Then the enhanced images are fed into a robust face recognition system which adaptively selects the most important features among all candidate features and performs classification by support vector machines (SVMs). The dimension of feature space as well as the selected types of features is customized for each hyperplane. Three face image databases, namely Yale, Yale Group B, and Extended Yale Group B, are used to evaluate performance. The experimental result shows that the proposed recognition system give superior results compared to recently published literatures.