High-gain pseudomorphic InGaAs base ballistic hot-electron device

A high-gain ballistic hot-electron device is described. The GaAs-AlGaAs heterostructure device, with a 21-mm-thick pseudomorphic In _0.12Ga_0.88As base, had a current gain of 27 at 77 K and 41 at 4.2 K. As characteristically seen in ballistic devices, transfer into the L valley limited the maximum gain. The Γ-L valley separation in the strained In_0.12Ga_0.88As was estimated to be about 380 meV     

Financial Analysis and Marketing Strategy

A combination of concept (the product portfolio and the product life cycle) and empirical research (the PIMS study) can aid in clarifying the key issues involved in the selection of a firm's core strategies. Strategy control is multistage: periodic re-evaluation of strategy alternatives by use of the marketing audit; an analytical framework for control of chosen strategies by breaking down components and reporting their performance variances; and 'marketing segment' analysis for control of the detailed marketing plan.?     

Sensory analysis of polystyrene packaging material taint in cocoa powder for drinks and chocolate flakes

Polystyrene packaging material taint was sensorily evaluated in cocoa powder for drinks and chocolate flakes using short-cut signal detection measures on differences between control and test samples and on recognition of styrene. No differences were observed in cocoa powder for drinks and plain chocolate flakes treated with 0.5 dm2 polystyrene of 1 mm thickness. However, differences were detected in milk chocolate flakes and plain chocolate flakes, which were in contact with a larger area or thicker polystyrene packaging material. The latter results were confirmed by the styrene recognition test, so polystyrene is a potential source of off-flavour for chocolate products. The amount of residual styrene in the polystyrene used was about 320 ppm, while the amounts of styrene ranged from 7 to 132 ppb in cocoa drinks and from 414 to 1447 ppb in chocolate flakes.     

Solution of Helmholtz equation by Trefftz method

The application of the Trefftz method for calculating wave forces on offshore structures is presented. Indirect and direct formulations using complete and non-singular systems of Trefftz functions for the Helmholtz equation are posed in this paper. An effective technique using different interpolation functions for the velocity potential and wave force are suggested to improve the computational accuracy of the wave force. The numerical examples show that the present method is highly efficient and accurate.     

Axial-Field Electrical Machines - Design and Applications

Axial-field electrical machines offer an alternative to the conventional machines. In the axial-field machine, the airgap flux is axial in direction and the active current carrying conductors are radially positioned. This paper presents the design characteristics, special features, manufacturing aspects and potential applications for axial-field electrical machines. The experimental results from several prototypes, including d.c. machines, synchronous machines and single-phase machines are given. The special features of the axial-field machine, such as its planar and adjustable airgap, flat shape, ease of diversification, etc., enable axial-field machines to have distinct advantages over conventional machines in certain applications, especially in special-purpose applications.     

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.     

A Recursive Frequency Estimator Using Linear Prediction and a Kalman-Filter-Based Iterative Algorithm

This paper proposes a new Kalman-filter-based recursive frequency estimator for discrete-time multicomponent sinusoidal signals whose frequencies may be time-varying. The frequency estimator is based on the linear prediction approach and it employs the Kalman filter to track the linear prediction coefficients (LPCs) recursively. Frequencies of the sinusoids can then be computed using the estimated LPCs. Due to the coloredness of the linear prediction error, an iterative algorithm is employed to estimate the covariance matrix of the prediction error and the LPCs alternately in the Kalman filter in order to improve the tracking performance. Simulation results show that the proposed Kalman-filter-based iterative frequency estimator can achieve better tracking results than the conventional recursive least-squares-based estimators.     

Modeling tool wear in end-milling using enhanced GMDH learning networks

This paper presents an enhanced approach to predictive modeling for determining tool-wear in end-milling operations based on enhanced-group method of data handling (e-GMDH). Using milling input parameters (speed, feed, and depth-of-cut) and response (tool wear), the data for the model is partitioned into training and testing datasets, and the training dataset is used to realize a predictive model that is a function of the input parameters and the coefficients determined. In our approach, we first present a methodology for modeling, and then develop predictive model(s) of the problem being solved in the form of second-order equations based on the input data and coefficients realized. This approach leads to some generalization because it becomes possible to predict not only the test data obtained during experimentation, but other test data outside the experimental results can also be used. Moreover, this approach makes it easy to present the realized solution in a form that can be further optimized for the input parameters using some optimization techniques. The results realized using our e-GMDH method are promising, and the comparative study presented shows that the e-GMDH outperforms polynomial neural network (PNN); moreover, it is more flexible than the conventional GMDH, which tends to produce nonlinear solutions even for simple problems. In the investigation, the extended particle swarm optimization (PSO) technique was applied to obtain the optimal parameters. Consequently, the modeling approach is extremely useful in realizing a computer-aided process-planning system in an advanced manufacturing environment.     

Evaluation of Digitally Encoded Layer‐by‐layer Coated Microparticles as Cell Carriers

To obtain more biologically relevant data there is a growing interest in the use of living cells for assaying the biological activity of unknown chemical compounds. Density ‘multiplex’ cell‐based assays, where different cell types are mixed in one well and simultaneously investigated upon exposure to a certain compound are beginning to emerge. To be able to identify the cells they should be attached to microscopic carriers that are encoded. This paper investigates how digitally encoded microparticles can be loaded with cells while keeping the digital code in the microcarriers readable. It turns out that coating the surface of the encoded microcarriers with polyelectrolytes using the layer‐by‐layer (LbL) approach provides the microcarriers with a ‘highly functional’ surface. The polyelectrolyte layer allows the growth of the cells, allows the orientation of the cell loaded microcarriers in a magnetic field, and does not hamper the reading of the code. It has further been shown that the cells growing on the polyelectrolyte layer can become transduced by adenoviral particles hosted by the polyelectrolyte layer. It is concluded that the digitally encoded microparticles are promising materials for use in biomedical and pharmaceutical in‐vitro research where cells are used as tools.     

Noise–Power Optimization of Incremental Data Converters

Incremental data converters (IDCs) are useful in instrumentation and measurement applications, where low-frequency analog signals need to be converted into digital form with high accuracy and low power dissipation. They are particularly well suited for applications where a single analog-digital converter is multiplexed between many channels. This paper proposes an exact design methodology for IDCs, which optimizes the signal-to-noise ratio of the converter under practical design constraints. The process also allows the designer to apportion the noise budget in an arbitrary manner between thermal and quantization noise. The design process is illustrated by an example which describes the optimization of a third-order multiplexed IDC.