05031 Abstracts Collection -- Algorithms for Optimization with Incomplete Information

From 16.01.05 to 21.01.05, the Dagstuhl Seminar 05031 ``Algorithms for Optimization with Incomplete Information\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

New Old Algorithms for Stochastic Scheduling

We consider the stochastic identical parallel machine scheduling problem and its online extension, when the objective is to minimize the expected total weighted completion time of a set of jobs that are released over time. We give randomized as well as deterministic online and offline algorithms that have the best known performance guarantees in either setting, online or offline and deterministic or randomized. Our analysis is based on a novel linear programming relaxation for stochastic scheduling problems that can be solved online

Dagstuhl News January - December 2005

"Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic

Measurement Based Channel Characterization and Modeling for Vehicle-to-Vehicle Communications

Vehicle-to-Vehicle (V2V) communication is a challenging but fast growing technology that has potential to enhance traffic safety and efficiency. It can also provide environmental benefits in terms of reduced fuel consumption. The effectiveness and reliability of these applications highly depends on the quality of the V2V communication link, which rely upon the properties of the propagation channel. Therefore, understanding the properties of the propagation channel becomes extremely important. This thesis aims to fill some gaps of knowledge in V2V channel research by addressing four different topics. The first topic is channel characterization of some important safety critical scenarios (papers I and II). Second, is the accuracy or validation study of existing channel models for these safety critical scenarios (papers III and IV). Third, is about channel modeling (paper V) and, the fourth topic is the impact of antenna placement on vehicles and the possible diversity gains. This thesis consists of an introduction and six papers: Paper I presents a double directional analysis of vehicular channels based on channel measurement data. Using SAGE, a high-resolution algorithm for parameter estimation, we estimate channel parameters to identify underlying propagation mechanisms. It is found that, single-bounce reflections from static objects are dominating propagation mechanisms in the absence of line-of-sight (LOS). Directional spread is observed to be high, which encourages the use of diversity-based methods. Paper II presents results for V2V channel characterization based on channel measurements conducted for merging lanes on highway, and four-way street intersection scenarios. It is found that the merging lane scenario has the worst propagation condition due to lack of scatterers. Signal reception is possible only with the present LOS component given that the antenna has a good gain in the direction of LOS. Thus designing an antenna that has an omni-directional gain, or using multiple antennas that radiate towards different directions become more important for such safety critical scenarios. Paper III presents the results of an accuracy study of a deterministic ray tracing channel model for vehicle-to-vehicle (V2V) communication, that is compared against channel measurement data. It is found that the results from measurement and simulation show a good agreement especially in LOS situations where as in NLOS situations the simulations are accurate as far as existing physical phenomena of wave propagation are captured by the implemented algorithm. Paper IV presents the results of a validation study of a stochastic NLOS pathloss and fading model named VirtualSource11p for V2V communication in urban street intersections. The reference model is validated with the help of independent channel measurement data. It is found that the model is flexible and fits well to most of the measurements with a few exceptions, and we propose minor modifications to the model for increased accuracy. Paper V presents a shadow fading model targeting system simulations based on channel measurements. The model parameters are extracted from measurement data, which is separated into three categories; line-of-sight (LOS), LOS obstructed by vehicles (OLOS), and LOS blocked by buildings (NLOS), with the help of video information recorded during the measurements. It is found that vehicles obstructing the LOS induce an additional attenuation in the received signal power. The results from system level vehicular ad hoc network (VANET) simulations are also presented, showing that the LOS obstruction affects the packet reception probability and this can not be ignored. Paper VI investigates the impact of antenna placement based on channel measurements performed with four omni-directional antennas mounted on the roof, bumper, windscreen and left-side mirror of the transmitter and receiver cars. We use diversity combining methods to evaluate the performance differences for all possible single-input single-output (SIMO), multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) link combinations. This investigation suggests that a pair of antennas with complementary properties, e.g., a roof mounted antenna together with a bumper antenna is a good solution for obtaining the best reception performance, in most of the propagation environments. In summary, this thesis describes the channel behavior for safety-critical scenarios by statistical means and models it so that the system performance can be assessed in a realistic manner. In addition to that the influence of different antenna arrangements has also been studied to exploit the spatial diversity and to mitigate the shadowing effects. The presented work can thus enable more efficient design of future V2V communication systems

Integration of hyperspectral, genomic, and agronomic data for early prediction of biomass yield in hybrid rye (Secale cereale L.)

Currently, the combination of a growing bioenergy demand and the need to diversify the dominant cultivation of energy maize opens a highly attractive scenario for alternative biomass crops. Rye (Secale cereale L.) stands out for its vigorous growth and increased tolerance to abiotic and biotic stressors. In Germany, less than a quarter of the total harvest is used for food production. Consequently, rye arises as a source of renewables with a reduced bioenergy-food tradeoff, emerging biomass as a new breeding objective. However, rye breeding is mainly driven by grain yield while biomass is destructively evaluated in later selection stages by expensive and time-consuming methods. The overall motivation of this research was to investigate the prospects of combining hyperspectral, genomic, and agronomic data for unlocking the potential of hybrid rye as a dual-purpose crop to meet the increasing demand for renewable sources of energy affordably. A specific aim was to predict the biomass yield as precisely as possible at an early selection stage. For this, a panel of 404 elite rye lines was genotyped and evaluated as testcrosses for grain yield and a subset of 274 genotypes additionally for biomass. Field trials were conducted at four locations in Germany in two years (eight environments). Hyperspectral fingerprints consisted of 400 discrete narrow bands (from 410 to 993 nm) and were collected in two points of time after heading for all hybrids in each site by an uncrewed aerial vehicle. In a first study, population parameters were estimated for different agronomic traits and a total of 23 vegetation indices. Dry matter yield showed significant genetic variation and was stronger correlated with plant height (r_g=0.86) than with grain yield (r_g=0.64) and individual vegetation indices (r_g: =<|0.35|). A multiple linear regression model based on plant height, grain yield, and a subset of vegetation indices surpassed the prediction ability for dry matter yield of models based only on agronomic traits by about 6 %. In a second study, whole-spectrum data was used to indirectly estimate dry matter yield. For this, single-kernel models based on hyperspectral reflectance-derived (HBLUP) and genomic (GBLUP) relationship matrices, a multi-kernel model combining both matrices, and a bivariate model fitted also with plant height as a secondary trait, were considered. HBLUP yielded superior predictive power than the models based on vegetation indices previously tested. The phenotypic correlations between individual wavelengths and dry matter yield were generally significant (p < 0.05) but low (r_p: =< |0.29|). Across environments and training set sizes, the bivariate model yielded the highest prediction abilities (0.56 0.75). All models profited from larger training populations. However, if larger training sets cannot be afforded, HBLUP emerged as a promising approach given its higher prediction power on reduced calibration populations compared to the well-established GBLUP. Before its incorporation into prediction models, filtering the hyperspectral data available by the least absolute shrinkage and selection operator (Lasso) was worthwhile to deal with data dimensionally. In a third study, the effects of trait heritability, as well as genetic and environmental relatedness on the prediction ability of GBLUP and HBLUP for biomass-related traits were compared. While the prediction ability of GBLUP (0.14 - 0.28) was largely affected by genetic relatedness and trait heritability, HBLUP was significantly more accurate (0.41 - 0.61) across weakly connected datasets. In this context, dry matter yield could be better predicted (up to 20 %) by a bivariate model. Nevertheless, due to environmental variances, genomic and reflectance-enabled predictions were strongly dependant on a sufficient environmental relationship between data used for model training and validation. In summary, to affordably breed rye as a double-purpose crop to meet the increasing bioenergy demands, the early prediction of biomass across selection cycles is crucial. Hyperspectral imaging has proven to be a suitable tool to select high-yielding biomass genotypes across weakly linked populations. Due to the synergetic effect of combining hyperspectral, genomic, and agronomic traits, higher prediction abilities can be obtained by integrating these data sources into bivariate models.Die Kombination eines wachsenden Bioenergiebedarfs und die Notwendigkeit, den vorherrschenden Anbau von Energiemais zu diversifizieren, eröffnen ein äußerst attraktives Szenario für alternative Biomassekulturen. Roggen (Secale cereale L.) zeichnet sich, durch ein kräftiges vegetatives Wachstum und eine erhöhte Toleranz gegenüber abiotischen und biotischen Stressfaktoren. In Deutschland wird weniger als ein Viertel der gesamten Roggenernte für die Lebensmittelproduktion verwendet. Daher gewinnt Roggen durch einen geringeren Zielkonflikt zwischen Bioenergie- und Lebensmittelnutzung an Bedeutung als Quelle für erneuerbare Energien, wobei Biomasse als neues Züchtungsziel auftaucht. Die Roggenzüchtung konzentriert sich derzeit jedoch hauptsächlich auf den Kornertrag, während die Biomasse in späteren Selektionsstadien durch teure und zeitaufwändige Methoden destruktiv erfasst wird. Die übergeordnete Motivation dieser Arbeit war es, die Aussichten der Kombination von hyperspektralen, genomischen und agronomischen Daten für die Erschließung des Potenzials von Hybridroggen als Zweinutzungspflanze zu untersuchen, um den steigenden Bedarf an erneuerbaren Energiequellen kostengünstig zu decken. Das spezifische Ziel war es, den Biomasseertrag in einem frühen Selektionsstadium so genau wie möglich vorherzusagen. Dazu wurde ein Panel von 404 Elitelinien genotypisiert und als Testkreuzungen für Kornertrag - eine Teilmenge von 274 Genotypen auch für Biomasse-Ertrag ausgewertet. Feldversuche wurden an vier Standorten in zwei Jahren in Deutschland (entspricht acht Umwelten) durchgeführt. Die hyperspektralen Daten (400 diskreten Banden; 410-993 nm) wurden zu zwei Zeitpunkten nach dem Ährenschieben für alle Testkreuzungen an jedem Ort von einer Drohne gesammelt. In einer ersten Studie wurden Populationsparameter für verschiedene agronomische Merkmale und insgesamt 23 Vegetationsindizes geschätzt. Der Trockenmasseertrag zeigte eine signifikante genetische Variation und korrelierte stärker mit der Wuchshöhe (r_g=0.86) als mit dem Kornertrag (r_g=0.64) und den einzelnen Vegetationsindizes (r_g: =<|0.35|). Ein multiples lineares Regressionsmodell, welches auf Wuchshöhe, Kornertrag und den besten Vegetationsindizes basierte, übertraf die Vorhersagefähigkeit für den Trockenmasseertrag von Modellen, die nur auf agronomischen Merkmalen basierten, um etwa 6%. In einer zweiten Studie wurde das ganze Wellenlängenspektrum verwendet, um den Trockenmasseertrag indirekt abzuschätzen. Hierzu wurden Einzelkernmodelle (single-kernel models) basierend auf genomischen (GBLUP) oder hyperspektralen (HBLUP) Beziehungsmatrizen, ein Mehrkernmodell (multi-kernel model), das beide Matrizen kombiniert, sowie ein bivariates Modell, welches auch Wuchshöhe als ein sekundäres Merkmal enthielt, analysiert. HBLUP lieferte eine bessere Vorhersagekraft als die Modelle, die auf Vegetationsindizes basierten. Die phänotypische Korrelationen zwischen einzelnen Wellenlängen und dem Trockenmasseertrag waren im Allgemeinen signifikant (p<0,05), jedoch geringfügig (r_p: =<|0.29|). Über alle Umwelten und Trainingssatzgrößen hinweg ergab das bivariate Modell die höchsten Vorhersagefähigkeiten (0,56-0,75). Alle Modelle profitierten von größeren Trainingspopulationen. Wenn jedoch keine größeren Trainingssätze bereitgestellt werden können, zeigte HBLUP eine höhere Vorhersagefähigkeit als das etablierte GBLUP. Vor der Einbeziehung in Vorhersagemodelle hat sich das Filtern der verfügbaren Hyperspektraldaten durch den least absolute shrinkage and selection operator (Lasso) als notwendig erwiesen, um die Dimensionalität der Daten zu verringern. In einer dritten Studie wurden die Auswirkungen der Heritabilität sowie der Ähnlichkeit innerhalb von Genotypen und Umwelten auf die Vorhersagefähigkeit von GBLUP und HBLUP für biomassebezogene Merkmale verglichen. Während die Vorhersagefähigkeit von GBLUP (0,14-0,28) weitgehend durch genetische Verwandtschaft und die Merkmalsheritabilitäten beeinflusst wurde, war HBLUP in wenig verwandten Datensätzen signifikant genauer (0,41-0,61). In diesem Zusammenhang konnte der Trockenmasseertrag durch ein bivariates Modell bis zu 20% besser vorhergesagt werden. Aufgrund hoher Genotyp-Umwelt-Interaktionen waren genomische und reflexionsbasierte Vorhersagen nur schlecht geeignet, um die Leistung fehlender Umwelten vorherzusagen. Zusammenfassend ist es für eine kostengünstige Züchtung von Roggen als Zweinutzungspflanze zur Deckung des steigenden Bioenergiebedarfs entscheidend, die Biomasse über Selektionszyklen hinweg frühzeitig vorherzusagen. Die hyperspektrale Bildgebung hat sich als geeignetes Instrument zur Auswahl ertragreicher Biomasse-Genotypen auch in wenig verwandten Populationen erwiesen. Dank des synergetischen Effekts der Kombination von hyperspektralen, genomischen und agronomischen Merkmalen können durch die Integration dieser Datenquellen in bivariaten Modelle höhere Vorhersagefähigkeiten erzielt werden

Aeronautical engineering: A continuing bibliography with indexes (supplement 249)

This bibliography lists 637 reports, articles, and other documents introduced into the NASA scientific and technical information system in November, 1988. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics