From monolithic to component-based performance evaluation of software architectures

Model-based performance evaluation methods for software architectures can help architects to assess design alternatives and save costs for late life-cycle performance fixes. A recent trend is component-based performance modelling, which aims at creating reusable performance models; a number of such methods have been proposed during the last decade. Their accuracy and the needed effort for modelling are heavily influenced by human factors, which are so far hardly understood empirically. Do component-based methods allow to make performance predictions with a comparable accuracy while saving effort in a reuse scenario? We examined three monolithic methods (SPE, umlPSI, Capacity Planning (CP)) and one component-based performance evaluation method (PCM) with regard to their accuracy and effort from the viewpoint of method users. We conducted a series of three experiments (with different levels of control) involving 47 computer science students. In the first experiment, we compared the applicability of the monolithic methods in order to choose one of them for comparison. In the second experiment, we compared the accuracy and effort of this monolithic and the component-based method for the model creation case. In the third, we studied the effort reduction from reusing component-based models. Data were collected based on the resulting artefacts, questionnaires and screen recording. They were analysed using hypothesis testing, linear models, and analysis of variance. For the monolithic methods, we found that using SPE and CP resulted in accurate predictions, while umlPSI produced over-estimates. Comparing the component-based method PCM with SPE, we found that creating reusable models using PCM takes more (but not drastically more) time than using SPE and that participants can create accurate models with both techniques. Finally, we found that reusing PCM models can save time, because effort to reuse can be explained by a model that is independent of the inner complexity of a component. The tasks performed in our experiments reflect only a subset of the actual activities when applying model-based performance evaluation methods in a software development process. Our results indicate that sufficient prediction accuracy can be achieved with both monolithic and component-based methods, and that the higher effort for component-based performance modelling will indeed pay off when the component models incorporate and hide a sufficient amount of complexity.     

An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments

Digital 3D models of the environment are needed in rescue and inspection robotics, facility managements and architecture. This paper presents an automatic system for gaging and digitalization of 3D indoor environments. It consists of an autonomous mobile robot, a reliable 3D laser range finder and three elaborated software modules. The first module, a fast variant of the Iterative Closest Points algorithm, registers the 3D scans in a common coordinate system and relocalizes the robot. The second module, a next best view planner, computes the next nominal pose based on the acquired 3D data while avoiding complicated obstacles. The third module, a closed-loop and globally stable motor controller, navigates the mobile robot to a nominal pose on the base of odometry and avoids collisions with dynamical obstacles. The 3D laser range finder acquires a 3D scan at this pose. The proposed method allows one to digitalize large indoor environments fast and reliably without any intervention and solves the SLAM problem. The results of two 3D digitalization experiments are presented using a fast octree-based visualization method.     

Parsing human skeletons in an operating room

Multiple human pose estimation is an important yet challenging problem. In an operating room (OR) environment, the 3D body poses of surgeons and medical staff can provide important clues for surgical workflow analysis. For that purpose, we propose an algorithm for localizing and recovering body poses of multiple human in an OR environment under a multi-camera setup. Our model builds on 3D Pictorial Structures and 2D body part localization across all camera views, using convolutional neural networks (ConvNets). To evaluate our algorithm, we introduce a dataset captured in a real OR environment. Our dataset is unique, challenging and publicly available with annotated ground truths. Our proposed algorithm yields to promising pose estimation results on this dataset.     

SAP NetWeaver: Slicing the fridge

Zusammenfassung Das Schlagwort NetWeaver ist seit einiger Zeit in unserer Branche en vogue. Wie so oft, ist es nicht leicht, Marketingaspekte vom informatischen Wesensgehalt zu unterscheiden. Dieser Beitrag m?chte hier helfen.     

An enzymic method for differentiating thawed and fresh fish fillets

The specific activities of the lysosomal enzymes α-glucosidase and β-N-acetylglucosaminidase were determined in press juices and extracts from fresh and frozen/thawed fillets of cod, saithe, red fish and haddock. For each of the two enzymes it was found that the press juice/extract activity ratio increased following the freezing/thawing process (six to nine times for αglucosidase and three to five times for β-N-acetylglucosaminidase).     

Computing surfaces invariant under subdivision

In this paper, we propose a general subdivision algorithm for generating surfaces. The algorithm has as motivation our earlier work on the design of free form curves where similar ideas were investigated. Here we describe some properties of uniform refinement algorithms for surface generation. A detail analysis of their properties will be given later by one of us.     

An interval arithmetic method for the solution of nonlinear systems of equations on a vector computer

We describe a vectorized algorithm for an interval arithmetic Newton-like method for a class of systems of nonlinear equations arising from discretizations of nonlinear elliptic PDE. This method converges to a solution under relatively weak conditions. It is founded on a combination of a Newton-like interval method and interval arithmetic ‘fast’ direct solver. In the present paper we focus our attention on aspects of the vectorization, in particular that of a simulation of an interval arithmetic and that of the direct solver.     

A multi-sensor climatological view of double ITCZs over the Indian Ocean

We characterize the climatological features of the double inter-tropical convergence zones (DITCZs) over the western Indian Ocean during November–December by a synergistic analysis of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS III) data (1988–2005) and the National Aeronautics and Space Administration's (NASA's) A-Train data (2002–2009). We investigate rainfall, freshwater flux and cloud liquid water, cloud fraction and relative humidity over the DITCZs. In addition, the daily rainfall data from the Global Precipitation Climatology Project (GPCP) are used to document the DITCZs during the El Niño southern oscillation (ENSO) events. An analysis of the GPCP data shows that the DITCZs are clearly discernible during strong ENSO events (1997, 2002 and 2006), in sharp contrast to the DITCZs in the eastern Pacific Ocean, where they are absent during ENSOs. Further, these convergence zones on either side of the equator are of short duration, approximately 3–6 pentads during November and December. All satellite sensor data sets consistently capture the major features of DITCZs. As an accurate simulation of DITCZs in coupled global climate models remains a challenge, the results from the present study would provide a platform for evaluating these models.     

Solving a linear multiperiod portfolio problem by interior-point methodology

In this report we formulate a linear multiperiod programming problem and show how it can be solved by a new interior point algorithm. The conditions of convergence and applicability of the algorithm of centers are explicitly connected to the multiperiod programming problem. For the former, effective application is supported by a set of simplifying conditions stated and proved in the text. For the latter, boundedness and nontriviality under real world conditions is demonstrated, allowing for its solution by the interior point algorithm. The use of a fast interior point algorithm is motivated by some empirical evidence from a Revised Simplex optimizer.     

A strong winner-take-all model based on integration of potential differences

A dynamic, strong winner-take-all model is presented. It is based on a limited integrator that is fed by potential differences between feedback from a single interneuron and the input value. The model does not require a special nonlinear function in the forward path. In equilibrium state, a single winner neuron transmits its input value to the output without change. For a two-neuron system the behaviour is shown graphically. Equilibrium states are determined for different types of input vectors.