An image-guided planning system for endosseous oral implants

A preoperative planning system for oral implant surgery was developed which takes as input computed tomographies (CT's) of the jaws. Two-dimensional (2-D) reslices of these axial CT slices orthogonal to a curve following the jaw arch are computed and shown together with three-dimensional (3-D) surface rendered models of the bone and computer-aided design (CAD)-like implant models. A technique is developed for scanning and visualizing an eventual existing removable prosthesis together with the bone structures. Evaluation of the planning done with the system shows a difference between 2-D and 3-D planning methods. Validation studies measure the benefits of the 3-D approach by comparing plans made in 2-D mode only with those further adjusted using the full 3-D visualization capabilities of the system. The benefits of a 3-D approach are then evident where a prosthesis is involved in the planning. For the majority of the patients, clinically important adjustments and optimizations to the 2-D plans are made once the 3-D visualization is enabled, effectively resulting in a better plan. The alterations are related to bone quality and quantity (p<0.05), biomechanics (p<0.005), and esthetics (p<0.005), and are so obvious that the 3-D plan stands out clearly (p<0.005). The improvements often avoid complications such as mandibular nerve damage, sinus perforations, fenestrations, or dehiscences     

Mechanistic framework for dry etching, beam assisted etching and tribochemical etching

A mechanistic framework is presented for impact assisted etch reactions. The consecutive reaction steps are assumed to be activated thermally and in parallel mechanically by fast particle impacts. The model explains the complicated temperature dependencies observed in dry etching and beam assisted etching, and it correlates the side wall profiles to the rate determining steps in the etch mechanisms. The framework is used to describe Reactive Ion Beam Etching (RIBE) experiments on InP with Ar⁺ ions and chlorine, in comparison with our recent Reactive Ion Etching (RIE) experiments of magnetic alloys in HCl plasmas. The framework is also applicable to other non-thermally activated etch reactions, as encountered in tribo-chemical etching and laser chemical etching.     

Concurrent software engineering: prospects and pitfalls

Software development remains largely a sequential, time-consuming process. Concurrent engineering (CE) principles have been more widely adopted and with greater success in hardware development. In this paper, a methodology for marrying CE principles to software engineering, or concurrent software engineering (CSE), is proposed. CSE is defined as a management technique to reduce the time-to-market in product development through simultaneous performance of activities and processing of information. A hierarchy of concurrent software development activity is defined, ranging from the simplest (within stage) to the most complex (across products and platforms). The information support activities to support this activity hierarchy are also defined, along with two key linking concepts-synchronicity and architectural modularity. Principles of CSE are developed for each level in the activity hierarchy. Research findings that establish limitations to implementing CE are also discussed     

Optical feedback on self-pulsating semiconductor lasers

Weak optical-feedback effects on the statistical properties of self-pulsations in narrow-stripe semiconductor lasers are analyzed using Lang-Kobayashi-type equations. The self-pulsation features are compared with the characteristics of excited relaxation oscillations. We determine the operating regime in which the randomizing effect of spontaneous-emission noise destroys pulse coherence. In this regime, only phase-insensitive effects of optical feedback are possible, and optimum jitter reduction is achieved with delay times of the order of an integer-odd multiple of the free-running pulsation period. In the high-pump operating regime, interpulse coherence is retained and the optical-feedback phase is shown to be instrumental for pulse-jitter control. Our results show that for cavity lengths up to 10 cm, variations on the order of half an optical wavelength induce jitter variations of one order of magnitude     

Colloid attachment by ILGAR-layers: Creating fluorescing layers to increase quantum efficiency of solar cells

A method for the fixation of colloids by an ion-layer-gas-reaction-“ILGAR”-oxide layer is presented. The embedding of CdS nano-particles in an ILGAR-ZnO/Zn(OH)₂-matrix is confirmed by transmission electron micrographs (TEM); the composition of the layer surface is analyzed by X-ray photoelectron microscopy (XPS). When these particles are fixed by an ILGAR-oxide layer on top of a solar cell the observed absorption and fluorescing properties of CdS nano-particles offer the possibility to reduce the absorption loss in the window layer. This is shown for a Cu(In,Ga)(S,Se)₂-“CIGSSe”-based solar cell with an additional top CdS_particle/ILGAR-ZrO₂-layer as a first example. The improvement of the device performance is proven by J(V)-characteristics and the external quantum efficiency.     

Optimal periodic inspection of a deterioration process with sequential condition states

The condition of components subject to visual inspections is often evaluated on a discrete scale. If at each inspection a decision is made to do nothing or to perform preventive or corrective maintenance, the proposed decision model allows us to determine the optimal time between periodic inspections, such that the expected average costs per unit of time are minimized. The model which describes the uncertain condition over time is based on a Markov process with sequential phases. The key quantities involved in the model are the probabilities of having to perform either preventive or corrective maintenance before or after an inspection. The costs functions for two scenarios are presented: a scenario in which failure is immediately detected without the need to perform an inspection and a scenario in which failure is only detected by inspection of the object. Analytical results for a special case and algorithmic results for a broad class of Markov processes are derived. The model is illustrated using an application to the periodic inspection of road bridges.     

Comparison of direct-drive and geared generator concepts for wind turbines

The objective of this paper is to compare five different generator systems for wind turbines, namely the doubly-fed induction generator with three-stage gearbox (DFIG3G), the direct-drive synchronous generator with electrical excitation (DDSG), the direct-drive permanent-megnet generator (DDPMG), the permanent-magnet generator with single stage gearbox (PMG1G), and the doubly-fed induction generator with single-stage gearbox (DFIG1G). The comparison is based on cost and annual energy yield for a given wind climate. The DFIG3G is a cheap solution using standard components. The DFIG1G seems the most attractive in terms of energy yield divided by cost. The DDPMG has the highest energy yield, but although it is cheaper than the DDSG, it is more expensive than the generator systems with gearbox.     

Technological learning in bioenergy systems

The main goal of this article is to determine whether cost reductions in different bioenergy systems can be quantified using the experience curve approach, and how specific issues (arising from the complexity of biomass energy systems) can be addressed. This is pursued by case studies on biofuelled combined heat and power (CHP) plants in Sweden, global development of fluidized bed boilers and Danish biogas plants. As secondary goal, the aim is to identify learning mechanisms behind technology development and cost reduction for the biomass energy systems investigated. The case studies reveal large difficulties to devise empirical experience curves for investment costs of biomass-fuelled power plants. To some extent, this is due to lack of (detailed) data. The main reason, however, are varying plant costs due to differences in scale, fuel type, plant layout, region etc. For fluidized bed boiler plants built on a global level, progress ratios (PRs) for the price of entire plants lies approximately between 90–93% (which is typical for large plant-like technologies). The costs for the boiler section alone was found to decline much faster. The experience curve approach delivers better results, when the production costs of the final energy carrier are analyzed. Electricity from biofuelled CHP-plants yields PRs of 91–92%, i.e. an 8–9% reduction of electricity production costs with each cumulative doubling of electricity production. The experience curve for biogas production displays a PR of 85% from 1984 to the beginning of 1990, and then levels to approximately 100% until 2002. For technologies developed on a local level (e.g. biogas plants), learning-by-using and learning-by-interacting are important learning mechanism, while for CHP plants utilizing fluidized bed boilers, upscaling is probably one of the main mechanisms behind cost reductions.     

Incorporating Uncertainty via Hierarchical Classification Using Fuzzy Decision Trees

Object hierarchy is often ignored when collecting and classifying geographical objects. Object attributes are defined on the basis of uncertain parameters that may change in space and time. In this paper, we consider fuzzy decision trees for classification and a Bayesian hierarchical model for modeling and handling uncertainty. The study is illustrated with dynamic geographical objects from a coastal management application in the northern part of The Netherlands. Hierarchical modeling is applied to obtain posterior distributions for several boundary regions. The posterior distributions yield lower and upper limits of membership functions describing boundaries between object classes. In this way, a proper fuzzy decision tree for the coastal management application is built, which includes the inherent dynamic uncertainty     

Root Cause of Charge Loss in a Nitride-Based Localized Trapping Memory Cell

Data retention loss mechanisms in nitride-based localized trapping memory devices are investigated with various electrical measurements and Medici simulations. First, the effect of program and erase cycles on device behavior is determined in terms of bottom oxide degradation and nitride charge profile evolution. Even if a strong degradation of the interface is observed, there is no important impact of this degradation on the cell behavior. However, the nitride charge profile evolves with cycling and leads to a three-pole electron-hole-electron profile over the channel region. Second, the interface trap annealing, the tunneling through the bottom oxide, and the lateral redistribution are studied in order to determine which mechanism plays the main role in the threshold voltage shift after cycling. The retention performance is dominated by a lateral redistribution of charges in the nitride layer.