Quantifying requirements volatility effects

In an organization operating in the bancassurance sector we identified a low-risk IT subportfolio of 84 IT projects comprising together 16,500 function points, each project varying in size and duration, for which we were able to quantify its requirements volatility. This representative portfolio stems from a much larger portfolio of IT projects. We calculated the volatility from the function point countings that were available to us. These figures were aggregated into a requirements volatility benchmark. We found that maximum requirements volatility rates depend on size and duration, which refutes currently known industrial averages. For instance, a monthly growth rate of 5% is considered a critical failure factor, but in our low-risk portfolio we found more than 21% of successful projects with a volatility larger than 5%. We proposed a mathematical model taking size and duration into account that provides a maximum healthy volatility rate that is more in line with the reality of low-risk IT portfolios. Based on the model, we proposed a tolerance factor expressing the maximal volatility tolerance for a project or portfolio. For a low-risk portfolio its empirically found tolerance is apparently acceptable, and values exceeding this tolerance are used to trigger IT decision makers. We derived two volatility ratios from this model, the π-ratio and the ρ-ratio. These ratios express how close the volatility of a project has approached the danger zone when requirements volatility reaches a critical failure rate. The volatility data of a governmental IT portfolio were juxtaposed to our bancassurance benchmark, immediately exposing a problematic project, which was corroborated by its actual failure. When function points are less common, e.g. in the embedded industry, we used daily source code size measures and illustrated how to govern the volatility of a software product line of a hardware manufacturer. With the three real-world portfolios we illustrated that our results serve the purpose of an early warning system for projects that are bound to fail due to excessive volatility. Moreover, we developed essential requirements volatility metrics that belong on an IT governance dashboard and presented such a volatility dashboard.     

Modeling the impact of spectral sensor configurations on the FLD retrieval accuracy of sun-induced chlorophyll fluorescence

Chlorophyll fluorescence is related to photosynthesis and can serve as a remote sensing proxy for estimating photosynthetic energy conversion and carbon uptake. Recent advances in sensor technology allow remote measurements of the sun-induced chlorophyll fluorescence signal (Fs) at leaf and canopy scale. The commonly used Fraunhofer Line Depth (FLD) principle exploits spectrally narrow atmospheric oxygen absorption bands and relates Fs to the difference of the absorption feature depth of a fluorescensing and a non-fluorescensing surface. However, due to the nature of these narrow bands, Fs retrieval results depend not only on vegetation species type or environmental conditions, but also on instrument technology and processing algorithms. Thus, an evaluation of all influencing factors and their separate quantification is required to further improve Fs retrieval and to allow a reproducible interpretation of Fs signals.Here we present a modeling study that isolates and quantifies the impacts of sensor characteristics, such as spectral sampling interval (SSI), spectral resolution (SR), signal to noise ratio (SNR), and spectral shift (SS) on the accuracy of Fs measurements in the oxygen A band centered at 760 nm (O₂-A). Modeled high resolution radiance spectra associated with known Fs were spectrally resampled, taking into consideration the various sensor properties. Fs was retrieved using the three most common FLD retrieval methods, namely the original FLD method (sFLD), the modified FLD (3FLD) and the improved FLD (iFLD). The analysis investigates parameter ranges, which are representative for field and airborne instruments currently used in Fs research (e.g., ASD FieldSpec, OceanOptics HR, AirFLEX, AISA, APEX, CASI, and MERIS).Our results show that the most important parameter affecting the retrieval accuracy is SNR, SR accounts for ≤ 40% of the error, the SSI for ≤ 12%, and SS for ≤ 7% of the error. A trade-off study revealed that high SR can partly compensate for low SNR. There is a strong interrelation between all parameters and the impact of specific parameters can compensate or amplify the influence of others. Hence, the combination of all parameters must be considered by the evaluation of sensors and their potential for Fs retrieval. In general, the standard FLD method strongly overestimates Fs, while 3FLD and iFLD provide a more accurate estimation of Fs. We conclude that technical sensor specifications and the retrieval methods cause a significant variability in retrieved Fs signals. Results are intended to be one relevant component of the total uncertainty budget of Fs retrieval and have to be considered in the interpretation of retrieved Fs signals.     

Simulation of hyperspectral and directional radiance images using coupled biophysical and atmospheric radiative transfer models

Future remote sensing satellite missions exploring the earth will feature advanced hyperspectral and directional optical imaging instruments. Given the complex nature of the data to be expected from these missions, a thorough preparation for them is essential and this can be accomplished by realistic simulation of the imagery data, years before the actual launch. Based on given spectral and directional capabilities of the instrument, and in combination with biophysical land surface properties obtained from existing imagery, the spectral and directional responses of several types of vegetation and bare soil have been simulated pixel by pixel using the radiative transfer models PROSPECT (for hyperspectral leaf reflectance and transmittance), GeoSAIL (for two-layer canopy bidirectional spectral reflectance), and MODTRAN4 (for atmospheric hyperspectral and directional effects). In this way, one obtains realistically simulated hyperspectral and directional top-of-atmosphere spectral radiance images, with all major effects included, such as heterogeneity of the landscape, non-Lambertian reflectance of the land surface, the atmospheric adjacency effect, and the limited spatial resolution of the instrument. The output of the image simulations can be used to demonstrate the capabilities of future earth observation missions. In addition, instrument specifications and image acquisition strategies might be optimized on the basis of simulated image analysis results, and new advanced data assimilation procedures could be validated with realistic inputs under controlled circumstances. This paper describes the applied methodology, the study area with the input images, the set-up of the actual image simulations, and discusses the final results obtained.     

Strategic Interactions of Bilateral Monopoly on a Private Highway

This paper investigates strategic interactions between a private highway operator and a private transit operator who uses the same highway for its services. Heterogeneity of travellers is taken into account by considering a continuous distribution of values of time. Demand elasticity arises from the inclusion of an outside virtual mode. Game theory is applied to model the possible moves taken by the operators in their interactions. Four games are formulated, representing different decision making processes, including Nash and Stackelberg (leader-follower) games. The different timings of long-run and short-run decisions are also modeled in a two-stage game. Our results indicate that the market equilibria in the four games formulated are quite different as a result of the different sequences of moves. The highway operator is considered to be in a better position in terms of profit making in most cases, while for the transit operator it will generally be more advantageous to be the follower rather than in the leader position.     

Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999

We used land surface temperature (LST) algorithms and NDVI values to estimate changes in vegetation in the European continent between 1982 and 1999 from the Pathfinder AVHRR Land (PAL) dataset. These two parameters are monitored through HANTS (Harmonic ANalysis of Time Series) software, which allows the simultaneous observation of mean value, first harmonic amplitude and phase behaviors in the same image. These results for each complete year of data show the effect of volcanic aerosols and orbital drift on PAL data. Comparison of time series of HANTS cloud-free time series with the original time series for various land cover proves that this software is useful for LST analysis, although primarily designed for NDVI applications. Comparison of yearly averages of HANTS LST over the whole Europe with air temperature confirms the validity of the results. Maps of the evolution for both parameters between periods 1982/1986 and 1995/1999 have been elaborated: NDVI data show the well confirmed trend of increase over Europe (up to 0.1 in NDVI), Southern Europe seeing a decrease in NDVI (− 0.02). LST averages stay stable or slightly decrease (up to − 1.5 K) over the whole continent, except for southern areas for which the increase is up to 2.5 K. These results evidence that arid and semi-arid areas of Southern Europe have become more arid, the rest of Europe seeing an increase in its wood land proportion, while seasonal amplitude in Northern Europe has decreased.     

Reconstructing cloudfree NDVI composites using Fourier analysis of time series

This letter describes the Harmonic ANalysis of Time Series (HANTS) algorithm. It performs two tasks: (i) screening and removal of cloud affected observations; and (ii) temporal interpolation of the remaining observations to reconstruct gapless images at a prescribed time. HANTS was applied to 36 AVHRR 10-days-maximum-NDVI composites covering most of Europe. The results show that cloud affected data are recognized successfully and replaced. Up to half the data points were rejected with no consequence for the successful reconstruction of seasonal NDVI profiles.     

A single course of remission reinduction chemotherapy for acute myelogenous leukemia relapsing after allogeneic bone marrow transplantation is complicated by graft-versus-host disease and followed by sustained complete remission

Graft-versus-host disease (GVHD) remains a major immunological complication after allogeneic bone marrow transplantation (allo-BMT), but also favors development of the beneficial graft-versus-leukemia (GVL) effect. A patient with AML-M4 (inv (16)) is described, who was given non-myeloablative remission reinduction therapy for leukemic relapse (inv (16), trisomy 8) diagnosed on day 184 after HLA-compatible sibling BMT. On day 236, ie about 6 weeks after completion of this course, a clinical syndrome suggestive of acute GVHD grade 3 had developed. Skin biopsy confirmed the clinical diagnosis of GVHD, with a compatible liver biopsy. Transfusion-associated GVHD was ruled out by analysis of short tandem repeat (STR) alleles in the skin biopsy, revealing alleles from donor and recipient but not from third party origin. Cyclosporin A (CsA) therapy, which had been tapered between days 150 and 175, was resumed, resulting in a favorable response and gradual transition to limited chronic GVHD. The patient has since remained in complete remission with an excellent performance status for more than 40 months, without further chemotherapy. Thus this biopsy proven case of GVHD was induced by marrow donor lymphocytes more than 200 days after transplantation and apparently triggered by remission reinduction chemotherapy. The case indicates that intensive non-myeloablative chemotherapy can cure AML relapsing after allo-BMT. The therapeutic effect in this case probably involved a direct pharmacological suppression of the leukemic clone followed by a GVL effect initiated by donor-derived alloreactive T lymphocytes.     

Cracking the 500-language problem

Constructing analysis and modification tools for software assets is laborious because you first need to implement the underlying parser for the software's specific programming language. These implementations are generally not in the public domain. So, parser development for any of the 500+ languages in use today implies a major up-front investment. The authors propose a solution that will work for virtually all languages: the rapid development of renovation parsers by stealing the grammars. They also share lessons learned