Two-machine open shop scheduling with secondary criteria

This paper considers two-machine open shop problems with secondary criteria where the primary criterion is the minimization of makespan and the secondary criterion is the minimization of the total flow time, total weighted flow time, or total weighted tardiness time. In view of the strongly NP-hard nature of these problems, two polynomially solvable special cases are given and constructive heuristic algorithms based on insertion techniques are developed. A strongly connected neighborhood structure is derived and used to develop effective iterative heuristic algorithms by incorporating iterative improvement, simulated annealing and multi-start procedures. The proposed insertion and iterative heuristic algorithms are empirically evaluated by solving problem instances with up to 80 jobs.     

Self-Consistent Quantum Mechanical Monte Carlo MOSFET Device Simulation

We have developed a self-consistent quantum mechanical Monte Carlo device simulator that takes electron transport in quantized states into consideration. Two-dimensional quantized states in MOSFET channels are constructed from one-dimensional solutions of the Schrödinger equation at different positions along the channel, and the Schrödinger and Poisson equations are solved self-consistently in terms of electron concentration and electrostatic potential distribution. The channel electron concentration, velocity and drain currents are calculated with the one particle Monte Carlo approach incorporating the intra-valley acoustic phonon and inter-valley phonon scattering mechanisms. This simulator was applied to a 70 nm n-MOSFET transistor, and we found that current mostly flows through the lowest subband and transport is quasi-ballistic near the source junction. To quantitatively estimate the performance of advanced devices, we have developed an inversion carrier transport simulator based on a full-band model. Our simulation method enables us to evaluate device characteristics and analyze the transport properties of ultra-small MOSFETs.     

Simulation of thermally induced package effects with regard to piezoresistive pressure sensors

Microsystems are on their way out of laboratories into production. One of these microsystems, a piezoresistive pressure sensor developed by Robert Bosch GmbH, is examined within this paper. Obviously, one can detect undesirable temperature effects resulting from the sensor package, which influence the electrical characteristics of the sensor. By means of finite-element modelling (FEM), a simulation of the temperature effects can be managed. It is also possible to search for alternative designs of the sensor package.     

Spherical harmonic coefficients for the potential of a constant-density polyhedron

Recurrent relationships for the definitions of fully normalized spherical harmonic coefficients C?_n,m and S?_n,m are derived and integrated analytically to yield the gravitational potential of a constant-density polyhedron. The algorithm is expressed in a C language computer program.     

Software quality management in turbulent times – are there alternatives to process oriented software quality management?

Software Quality Journal - There is a widely accepted paradigm of successful software development, called process oriented software quality management (PSQM). The proponents of PSQM claim that it...     

User preference mining techniques for personalized applications

Advanced personalized e-applications require comprehensive knowledge about their users’ likes and dislikes in order to provide individual product recommendations, personal customer advice, and custom-tailored product offers. In our approach we model such preferences as strict partial orders with “A is better than B” semantics, which has been proven to be very suitable in various e-applications. In this paper we present preference mining techniques for detecting strict partial order preferences in user log data. Real-life e-applications like online shops or financial services usually have large log data sets containing the transactions of their customers. Since the preference miner uses sophisticated SQL operations to execute all data intensive operations on database layer, our algorithms scale well even for such large log data sets. With preference mining personalized e-applications can gain valuable knowledge about their customers’ preferences, which can be applied for personalized product recommendations, individual customer service, or one-to-one marketing.     

A new didactic approach to statistical analysis of measurement data for the evaluation of measurement uncertainty – “SAM–EMU”

This paper describes assumptions, aims, methodology, content and consortium make up of a European project (SAM–EMU) founded under the Erasmus Lifelong Learning Programme. The project has developed learning materials in the field of evaluation of measurement uncertainty. It is available in the form of a multimedia web based course, which has many advantages. This format is commonly accepted as a good way to prepare an EU wide vocational training vehicle. The course is available in English.