Robust stability of systems with delayed feedback

Some issues in the stability of differential delay systems in the linear and the nonlinear case are investigated. In particular, sufficient robustness conditions are derived under which a system remains stable, independent of the length of the delay(s). Applications in the design of delayed feedback systems are given. Two approaches are presented, one based on Lyapunov theory, the other on a transformation to Jordan form. In the former, sufficient conditions are obtained in the form of certain Riccati-type equations.     

A classification of predictive-reactive project scheduling procedures

The vast majority of the project scheduling research efforts over the past several years have concentrated on the development of workable predictive baseline schedules, assuming complete information and a static and deterministic environment. During execution, however, a project may be subject to numerous schedule disruptions. Proactive-reactive project scheduling procedures try to cope with these disruptions through the combination of a proactive scheduling procedure for generating predictive baseline schedules that are hopefully robust in that they incorporate safety time to absorb anticipated disruptions with a reactive procedure that is invoked when a schedule breakage occurs during project execution. In this paper we discuss the results obtained by a large experimental design set up to evaluate several predictive-reactive resource-constrained project scheduling procedures under the composite objective of maximizing both the schedule stability and the timely project completion probability.     

Equilibrium Studies of the System'(Fe,Co)O'–(Fe,Co)3O4 by Solid-State emf Measurements in the Temperature Range 970 to 1370 K

The equilibrium reaction 3'(Fe, Co)O'( ss ) +1/2O₂ ( g ) ⇄ (Fe, Co)₃O₄( ss ) was studied in the temperature range 970 to 1370 K for seven different total compositions of molar ratios 0.5 < Fe/(Fe + Co) ≤ 1.0. The equilibrium pressures of oxygen were determined by using galvanic cells incorporating calcia stabilized zirconia as solid electrolyte and the Fe/Co ratios in the solid-solution phases by wavelength dispersive spectrometry microprobe analyses. The activities of 'FeO' in the cobaltowüstite phase were then derived from the experimental results obtained.     

External-Memory Algorithms for Processing Line Segments in Geographic Information Systems

In the design of algorithms for large-scale applications it is essential to consider the problem of minimizing I/O communication. Geographical information systems (GIS) are good examples of such large-scale applications as they frequently handle huge amounts of spatial data. In this paper we develop efficient external-memory algorithms for a number of important problems involving line segments in the plane, including trapezoid decomposition, batched planar point location, triangulation, red--blue line segment intersection reporting, and general line segment intersection reporting. In GIS systems the first three problems are useful for rendering and modeling, and the latter two are frequently used for overlaying maps and extracting information from them.     

Using airborne laser scanning to monitor tree migration in the boreal-alpine transition zone

The boreal tree line is expected to advance upwards into the mountains and northwards into the tundra due to global warming. The major objective of this study was to find out if it is possible to use high-resolution airborne laser scanner data to detect very small trees — the pioneers that are pushing the tree line up into the mountains and out onto the tundra. The study was conducted in a sub-alpine/alpine environment in southeast Norway. A total of 342 small trees of Norway spruce, Scots pine, and downy birch with tree heights ranging from 0.11 to 5.20 m were precisely georeferenced and measured in field. Laser data were collected with a pulse density of 7.7 m^− 2. Three different terrain models were used to process the airborne laser point cloud in order to assess the effects of different pre-processing parameters on small tree detection. Greater than 91% of all trees > 1 m tall registered positive laser height values regardless of terrain model. For smaller trees (< 1 m), positive height values were found in 5-73% of the cases, depending on the terrain model considered. For this group of trees, the highest rate of trees with positive height values was found for spruce. The more smoothed the terrain model was, the larger the portion of the trees that had positive laser height values. The accuracy of tree height derived from the laser data indicated a systematic underestimation of true tree height by 0.40 to 1.01 m. The standard deviation for the differences between laser-derived and field-measured tree heights was 0.11-0.73 m. Commission errors, i.e., the detection of terrain objects — rocks, hummocks — as trees, increased significantly as terrain smoothing increased. Thus, if no classification of objects into classes like small trees and terrain objects is possible, many non-tree objects with a positive height value cannot be separated from those actually being trees. In a monitoring context, i.e., repeated measurements over time, we argue that most other objects like terrain structures, rocks, and hummocks will remain stable over time while the trees will change as they grow and new trees are established. Thus, this study indicates that, given a high laser pulse density and a certain density of newly established trees, it would be possible to detect a sufficient portion of newly established trees over a 10 years period to claim that tree migration is taking place.     

A Comparison of Presentation Methods for Reading on Mobile Phones

A study compares two methods of reading text-based content on mobile phones: traditional scroll-based reading and Rapid Serial Visual Presentation, which displays words rapidly in a sequence. University students used a prototype called Feedo to test both methods, and their reading comprehension, efficiency, and preference ratings were measured. The results show that efficiency increases with fast RSVP, comprehension is equal, and preference rating is lower than with self-paced scroll.     

The controversy over recovered memories.

Comments on the article by J. L. Alpert et al (see record 2000-13581-002), which presented the report of the American Psychological Association Working Group on Investigation of Memories of Childhood Abuse. The authors discuss 4 issues in this commentary: (a) the assumptions and evidence used to support the case for dissociated and recovered memories (noting that the evidence is weak and the assumptions internally inconsistent as well as contradictory to a mass of experimental evidence about human memory); (b) the process by which dissociated memories are said to be recovered (events that were originally very poorly encoded as fragmentary, kinesthetic memories cannot be recovered with accuracy later); (c) 4 bodies of relevant, but neglected, research on human memory (reminiscence and hypermnesia, effectiveness of retrieval cues, priming in implicit memory tests, and intentional forgetting); and (d) the issue of appropriate research strategies to gain evidence on the thorny issues of long-delayed retrieval of information. Current evidence does not support the conclusion that memories of repeated abuse are dissociated and recovered with accuracy years later. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Sentic Computing for social media marketing

In a world in which millions of people express their opinions about commercial products in blogs, wikis, fora, chats and social networks, the distillation of knowledge from this huge amount of unstructured information can be a key factor for marketers who want to create an image or identity in the minds of their customers for their product, brand or organization. Opinion mining for product positioning, in fact, is getting a more and more popular research field but the extraction of useful information from social media is not a simple task. In this work we merge AI and Semantic Web techniques to extract, encode and represent this unstructured information. In particular, we use Sentic Computing, a multi-disciplinary approach to opinion mining and sentiment analysis, to semantically and affectively analyze text and encode results in a semantic aware format according to different web ontologies. Eventually we represent this information as an interconnected knowledge base which is browsable through a multi-faceted classification website.