System Operational Evaluation of Mine Monitoring Systems

In the testing of mine monitoring systems, a software package was developed for the mine monitoring test facility designed at West Virginia University. The software establishes delay times of sensor input to annunciation for single alarms and multiple simultaneous alarms. The alarm measurement techniques for the test fixture are described, as is the software developed to analyze and graph monitoring system response data. Also included is the analysis capability of the facility, the criteria for evaluating mine monitoring systems, and typical test data from a sample system.     

固态继电器为电动汽车电池监测提供便利

电动汽车常被喻作“归来的孩子”，因为这项技术在多年前进入市场后便一直沉寂，直至最近才再次活跃起来。其实，电动汽车早于1835年首次于美国出现，到1899年，纽约市接近90％的出租车都是由电力驱动。然而，当电力启动器和内燃机变得完善时，电动汽车的使用就迅速衰退。随着如今对环境保护的关注，由燃烧碳氢化合物造成的污染，加之汽油成本高升的影响，再次     

Microcomputer Control of a Residential Photovoltaic Power Conditioning System

Microcomputer-based control of a residential photovoltaic power conditioning system is described. The microcomputer is responsible for array current feedback control, maximum power tracking control, array safe zone steering control, phase-locked reference wave synthesis, sequencing control, and some diagnostics. The control functions are implemented using Intel 8751 single-chip microcomputer-based hardware and software. The controller has been tested in the laboratory with the prototype power conditioner and shows excellent performance.     

An Analysis of Scheduling Policies In Multiechelon Production Systems

Results of a simulation study of the economics of frequency of rescheduling Material Requirements Planning (MRP) systems are presented for a single-product, two-stage system in which demand is uncertain. The results indicate that for systems with moderate demand uncertainty, frequent rescheduling to maintain customer service may be uneconomical when compared with the alternative of more stable schedules in conjunction with safety stock. This result arises primarily because the cost of “emergency” production setups which occur when rescheduling is frequent exceeds the cost of safety stock required to “protect” stable schedules.     

Integration of prior knowledge of measurement noise in kernel density classification

Samples can be measured with different precisions and reliabilities in different experiments, or even within the same experiment. These varying levels of measurement noise may deteriorate the performance of a pattern recognition system, if not treated with care. Here we seek to investigate the benefit of incorporating prior knowledge about measurement noise into system construction. We propose a kernel density classifier which integrates such prior knowledge. Instead of using an identical kernel for each sample, we transform the prior knowledge into a distinct kernel for each sample. The integration procedure is straightforward and easy to interpret. In addition, we show how to estimate the diverse measurement noise levels in a real world dataset. Compared to the basic methods, the new kernel density classifier can give a significantly better classification performance. As expected, this improvement is more obvious for small sample size datasets and large number of features.     

The Effects of H2O, CO and CO2 on the H2 Permeance and Surface Characteristics of 1 mm Thick Pd80wt%Cu Membranes

The hydrogen permeance of 1 mm-thick Pd_80wt%Cu foils was measured in the presence of equimolar mixtures of H₂ with CO, CO₂ or H₂O over the temperature and total pressure ranges of 623–1,173 K and 0.62–2.86 MPa, respectively. In all cases, permeance losses at 623 and 738 K were very modest. At higher temperatures, more significant decreases in membrane permeance were observed with the highest reduction of about 50% occurring when macroscopic carbon deposition occurred on the membrane surface during H₂–CO exposure at 908 K. The more worrisome effects of exposure to these gases, however, were the micron-scale surface defects observed at 908 and 1,038 K. Although the 1 mm thick disk membranes retained their mechanical integrity, such defects could cause catastrophic failure of ultra-thin, Pd–Cu membranes (1–5 μm thick) deposited on porous substrates.     

Microstructure and fatigue properties of hydroformed aluminum alloys 6063 and 5754

This study investigated the microstructure and fatigue properties of hydroformed sections of the 5754 and 6063 aluminum alloys. The second-phase particles in 6063-T7 are identified as a mixture of Al₁₂Fe₃Si and Al₉Fe₂Si₂, with a slightly higher fraction of the former. The constituent particles in the 5754 alloy are Al₄Mn-type hexagonal compounds, where Mn is partially substituted by various other elements, resulting in Al₄(Fe,Mn,Si,Cr). The results show that despite its lower yield strength, the hydroformed 5754 alloy has higher ultimate tensile strength, ductility, and, more importantly, higher fatigue resistance than the 6063 material. Both crystallographic stage I and noncrystallographic stage II cracking are found in the 6063-T7 samples, but only stage II cracking is observed in the 5754 alloy. This implies that the low fatigue strength of 6063-T7 is related to its relatively large grain size, resulting in rapid stage I crack propagation. The higher fatigue lives of the 5754 alloy compared to the 6063 alloy in both the low- and high-cycle life regimes are due to the increased fatigue-crack-initiation and propagation resistance of the 5754 alloy and its probable cyclic strain-hardening behavior.     

ELECTRICALLY CONDUCTING GLASSES*

Glasses containing lead, bismuth, or antimony oxides or combinations of these become conducting after several hours’ reduction in hydrogen. The electronic surface conductivity is both stable and reproducible. The magnitude of the conductivity depends on the nature and amounts of the reducible oxides, the temperatures at which reduction is carried out, and the electrical influence of the nonreduced portions of the glasses.     

Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case

The Quantitative Structure-Property Relationships (QSPRs) based on Graph or Network Theory are important for predicting the properties of polymeric systems. In the three previous papers of this series (Polymer 45 (2004) 3845-3853; Polymer 46 (2005) 2791-2798; and Polymer 46 (2005) 6461-6473) we focused on the uses of molecular graph parameters called topological indices (TIs) to link the structure of polymers with their biological properties. However, there has been little effort to extend these TIs to the study of complex mixtures of artificial polymers or biopolymers such as nucleic acids and proteins. In this sense, Blood Proteome (BP) is one of the most important and complex mixtures containing protein polymers. For instance, outcomes obtained by Mass Spectrometry (MS) analysis of BP are very useful for the early detection of diseases and drug-induced toxicities. Here, we use two Spiral and Star Network representations of the MS outcomes and defined a new type of TIs. The new TIs introduced here are the spectral moments (π_k) of the stochastic matrix associated to the Spiral graph and describe non-linear relationships between the different regions of the MS characteristic of BP. We used the MARCH-INSIDE approach to calculate the π_k(SN) of different BP samples and S2SNet to determine several Star graph TIs. In the second step, we develop the corresponding Quantitative Proteome-Property Relationship (QPPR) models using the Linear Discriminant Analysis (LDA). QPPRs are the analogues of QSPRs in the case of complex biopolymer mixtures. Specifically, the new QPPRs derived here may be used to detect drug-induced cardiac toxicities from BP samples. Different Machine Learning classification algorithms were used to fit the QPPRs based on π_k(SN), showing J48 decision tree classifier to have the best performance. These results suggest that the present approach captures important features of the complex biopolymers mixtures and opens new opportunities to the application of the idea supporting classic QSPRs in polymer sciences.