Positive temperature dependence of the electron impact ionizationcoefficient in In0.53Ga0.47As/InP HBTs

Impact ionization is a major limiting factor to the maximum operating voltage of InGaAs-based, high-speed transistors. In this work, data on the positive temperature dependence of the electron impact ionization coefficient α_n in In_0.53Ga_0.47As at medium-low electric fields are reported for the first time. The increase of α_n with temperature is opposite to the behavior normally observed in most semiconductors. This anomalous behavior implies the onset of a positive feedback between power dissipation and avalanche generation which may adversely affect the power handling capability of In_0.53Ga _0.47As-based devices, and which should be taken into account in device thermal modeling. In the experimental procedure, based on the measurement of the multiplication factor M-1 in npn In_0.53Ga _0.47As/InP Heterojunction Bipolar Transistors (HBT), particular care has been taken in order to rule out possible spurious, temperature-dependent contributions to the measured multiplication current     

A fully soft-switched extended-period quasi-resonantpower-factor-correction circuit

This paper presents the design criteria, procedure, and implementation of a soft-switched power-factor-correction (PFC) circuit based on the extended-period quasi-resonant (EPQR) principles. All power electronic devices including switches and diodes in the circuit are fully soft switched. The design method is demonstrated in a prototype circuit. The operating principles are confirmed with computer simulation and experimental results. A comparison of the EP-QR operation and zero-voltage-transition (ZVT) pulse-width modulation (PWM) method     

Application of neural networks and machine learning in networkdesign

Communication network design is becoming increasingly complex, involving making networks more usable, affordable, and reliable. To help with this, we have proposed an expert network designer (END) for configuring, modeling, simulating, and evaluating large structured computer networks, employing artificial intelligence, knowledge representation, and network simulation tools. We present a neural network/knowledge acquisition machine-learning approach to improve the END's efficiency in solving the network design problem and to extend its scope to acquire new networking technologies, learn new network design techniques, and update the specifications of existing technologies     

Densification involved in the UV-based photosensitivity of silicaglasses and optical fibers

A comprehensive survey of photosensitivity in silica glasses and optical fiber is reviewed. Recent work on understanding the mechanisms contributing to germanium or aluminum doped fiber photosensitivity is discussed within the framework of photoelastic densification models     

Soft commutation in capacitive idling converters

The capacitive idling converters derived from the Cuk, SEPIC, Zeta, and flyback topologies allow soft commutation of power switches without the need for additional circuitry, making it possible to increase the switching frequency while maintaining high efficiency     

E-kernel: an embedding kernel on the IBM victor V256 multiprocessorfor program mapping and network reconfiguration

We present the design of E-kernel, an embedding kernel on the Victor V256 message-passing partitionable multiprocessor, developed for the support of program mapping and network reconfiguration. E-kernel supports the embedding of a new network topology onto Victor's 2D mesh and also the embedding of a task graph onto the 2D mesh network or the reconfigured network. In the current implementation, the reconfigured network can be a line or an even-size ring, and the task graphs meshes or tori of a variety of dimensions and shapes or graphs with similar topologies. For application programs having these task graph topologies and that are designed according to the communication model of E-kernel, they can be run without any change on partitions connected by the 2D mesh, line, or ring. Further, E-kernel attempts the communication optimization of these programs on the different networks automatically, thus making both the network topology and the communication optimization attempt completely transparent to the application programs. Many of the embeddings used in E-kernel are optimal or asymptotically optimal (with respect to minimum dilation cost). The implementation of E-kernel translated some of the many theoretical results in graph embeddings into practical tools for program mapping and network reconfiguration in a parallel system. E-kernel is functional on Victor V256. Measurements of E-kernel's performance on V256 are also included     

Algebra of algorithms and Kaluzhnin's graphschemas

This research was supported under project No. 6.02.02/128-93 as part of the state scientific-technical program on future information technologies and systems by the Ukrainian State Committee, of Science and Technology.     

Effect of Freezer Programs on Real-Time Storage Results of Dissolution Profiles

Carstensen and Rhodes¹ have suggested that when, in stability programs, assays cannot be performed immediately after the protocol-designated storage time, then freezing them until such a time when assays can be performed would be a reasonable manner to retain the protocol schedule. They caution, however, that such a procedure may not be valid for dissolution data. The article to follow deals with real-time data showing that such a process is feasible for Nalidixic Acid tablets (and presumably for other tablets as well), and that, furthermore, the dissolution pattern would seem to be “frozen” as well.