A comprehensive survey of industry practice in real-time systems

Real-Time Systems - This paper presents results and observations from a survey of 120 industry practitioners in the field of real-time embedded systems. The survey provides insights into the...     

Bamboo reinforced concrete: a critical review

The use of small diameter whole-culm (bars) and/or split bamboo (a.k.a. splints or round strips) has often been proposed as an alternative to relatively expensive reinforcing steel in reinforced concrete. The motivation for such replacement is typically cost—bamboo is readily available in many tropical and sub-tropical locations, whereas steel reinforcement is relatively more expensive—and more recently, the drive to find more sustainable alternatives in the construction industry. This review addresses such ‘bamboo-reinforced concrete’ and assesses its structural and environmental performance as an alternative to steel reinforced concrete. A prototype three bay portal frame, that would not be uncommon in regions of the world where bamboo-reinforced concrete may be considered, is used to illustrate bamboo reinforced concrete design and as a basis for a life cycle assessment of the same. The authors conclude that, although bamboo is a material with extraordinary mechanical properties, its use in bamboo-reinforced concrete is an ill-considered concept, having significant durability, strength and stiffness issues, and does not meet the environmentally friendly credentials often attributed to it.     

On the Structure of Amorphous Mesoporous Silica Nanoparticles by Aberration‐Corrected STEM

Mesoporous silica materials have demonstrated a vast spectrum of applications, stimulating an intensive field of study due to their potential use as nanocarriers. Nonetheless, when produced at the nanoscale, their structural characterization is hindered due to the re‐arrangement of the pores. To address this issue, this work combines molecular dynamics simulations with electron microscopy computer simulations and experimental results to provide an insight into the structure of amorphous mesoporous silica nanoparticles. The amorphous silica model is prepared using a simple melt‐quench molecular dynamics method, while the reconstruction of the mesoporous nanoparticles is carried out using a methodology to avoid false symmetry in the final model. Simulated scanning transmission electron microscopy images are compared with experimental images, revealing the existence of structural domains, created by the misalignment of the pores to compensate the surface tension of these spherical nanoparticles.     

Enterprise networks: The re-engineering of complex software systems

Today technology design can no longer be understood as a design process on a green site. Design and implementation of new technology are always dependent on existing technology and the way it is used by people. In this respect Software-Engineering has also changed to the characteristics of normal technology design taking into account existing computer systems. Experiences show that the conditions and needs of such Software-Reengineering projects are highly complex and differ in their special characteristics ranging from aspects of quality of existing system documentation to organizational structures of the computer departments concerned. The Task-Artifact Cycle presented here gives a suitable reengineering approach emphasizing both analysis and design in Software-Reengineering.     

The Donauspital-Stolzalpe concept (Danube Hospital, Vienna, Austria). Corrective osteotomy with selective labrum surgery following preoperative MRI arthrography

Concomitant pathologies (labral lesions, intra-/extra-osseous ganglia and stress bone marrow edema) in adult residual hip dysplasia (RHD) might influence the outcome of conservative hip surgery. The aim of our prospective clinical study was to assess the value of preoperative MR arthrography in diagnosing concomitant lesions and in making surgical decisions in RHD. The first 37 consecutive patients with a minimum follow-up of 18 months have been analysed. All 37 patients presented RHD with the clinical symptomatology of labral lesions and underwent routine preoperative MRA. According to clinical, radiological and MR arthrographical criteria, these 37 patients were subdivided into four therapeutic subgroups: (1) reorientation of the acetabulum using the T?nnis triple pelvic osteotomy (TPO); (2) intertrochanteric varisation osteotomy (IVO); (3) palliative decompression with only symptomatic partial resection of the torn labrum (PALL); (4) primary total hip replacement (TEP). Based on the preliminary clinical and radiological outcomes of these four subgroups, the following conclusions can be drawn: labral lesions are considered to be a sign of chronic joint instability. Therefore, acetabular malorientation should be corrected by redirectional osteotomy of the acetabulum (TPO-subgroup) even in low grades of RHD if labral lesions are present. "Palliative" labral resections without corrective osteotomy (PALL subgroup) in secondary osteoarthritis due to RHD are definitively obsolete, because they rapidly progress to severe osteoarthritis due to surgically accelerated joint instability. In RHD with highly osteoarthritic hip joints and concomitant lesions, one should not hesitate to perform primary THR even in young patients.     

On the versatility of radial basis function neural networks: A case study in the field of intrusion detection

Classifiers based on radial basis function neural networks have a number of useful properties that can be exploited in many practical applications. Using sample data, it is possible to adjust their parameters (weights), to optimize their structure, and to select appropriate input features (attributes). Moreover, interpretable rules can be extracted from a trained classifier and input samples can be identified that cannot be classified with a sufficient degree of “certainty”. These properties support an analysis of radial basis function classifiers and allow for an adaption to “novel” kinds of input samples in a real-world application. In this article, we outline these properties and show how they can be exploited in the field of intrusion detection (detection of network-based misuse). Intrusion detection plays an increasingly important role in securing computer networks. In this case study, we first compare the classification abilities of radial basis function classifiers, multilayer perceptrons, the neuro-fuzzy system NEFCLASS, decision trees, classifying fuzzy-k-means, support vector machines, Bayesian networks, and nearest neighbor classifiers. Then, we investigate the interpretability and understandability of the best paradigms found in the previous step. We show how structure optimization and feature selection for radial basis function classifiers can be done by means of evolutionary algorithms and compare this approach to decision trees optimized using certain pruning techniques. Finally, we demonstrate that radial basis function classifiers are basically able to detect novel attack types. The many advantageous properties of radial basis function classifiers could certainly be exploited in other application fields in a similar way.     

3D Human model adaptation by frame selection and shape–texture optimization

We present a novel approach for 3D human body shape model adaptation to a sequence of multi-view images, given an initial shape model and initial pose sequence. In a first step, the most informative frames are determined by optimization of an objective function that maximizes a shape–texture likelihood function and a pose diversity criterion (i.e. the model surface area that lies close to the occluding contours), in the selected frames. Thereafter, a batch-mode optimization is performed of the underlying shape- and pose-parameters, by means of an objective function that includes both contour and texture cues over the selected multi-view frames.Using above approach, we implement automatic pose and shape estimation using a three-step procedure: first, we recover initial poses over a sequence using an initial (generic) body model. Both model and poses then serve as input to the above mentioned adaptation process. Finally, a more accurate pose recovery is obtained by means of the adapted model.We demonstrate the effectiveness of our frame selection, model adaptation and integrated pose and shape recovery procedure in experiments using both challenging outdoor data and the HumanEva data set.     

Color invariant chroma keying and color spill neutralization for dynamic scenes and cameras

In this article we show how temporal backdrops that alternately change their color rapidly at recording rate can aid chroma keying by transforming color spill into a neutral background illumination. Since the chosen colors sum up to white, the chromatic (color) spill component is neutralized when integrating over both backdrop states. The ability to separate both states additionally allows to compute high-quality alpha mattes. Besides the neutralization of color spill, our method is invariant to foreground colors and supports applications with real-time demands. In this article, we explain different realizations of temporal backdrops and describe how keying and color spill neutralization are carried out, how artifacts resulting from rapid motion can be reduced, and how our approach can be implemented to be compatible with common real-time post-production pipelines.     

Computing delay resistant railway timetables

In the past, much research has been dedicated to compute optimum railway timetables. A typical objective has been the minimization of passenger waiting times. But only the planned nominal waiting times have been addressed, whereas delays as they occur in daily operations have been neglected. Delays have been rather treated mainly in an online context and solved as a separate optimization problem, called delay management.We provide the first computational study which aims at computing delay resistant periodic timetables. In particular we assess the delay resistance of a timetable by evaluating it subject to several delay scenarios to which optimum delay management will be applied.We arrive at computing delay resistant timetables by selecting a new objective function which we design to be somehow in the middle of the traditional simple timetabling objective and the sophisticated delay management objective. This is a slight extension of the concept of “light robustness” (LR) as it has been proposed by Fischetti and Monaci [2006. Robust optimization through branch-and-price. In: Proceedings of AIRO]. Moreover, in our application we are able to provide accurate interpretations for the ingredients of LR. We apply this new technique to real-world data of a part of the German railway network of Deutsche Bahn AG. Our computational results suggest that a significant decrease of passenger delays can be obtained at a relatively small price of robustness, i.e. by increasing the nominal travel times of the passengers.