Unsupervised Segmentation of Stereoscopic Video Objects: Constrained Segmentation Fusion Versus Greedy Active Contours

In this paper, we present a novel memory access reduction scheme (MARS) for two-dimension fast cosine transform (2-D FCT). It targets programmable DSPs with high memory-access latency. It reduces the number of memory accesses by: 1) reducing the number of weighting factors and 2) combining butterflies in vector-radix 2-D FCT pruning diagram from two stages to one stage with an efficient structure. Hardware platform based on general purpose processor is used to verify the effectiveness of the proposed method for vector-radix 2-D FCT pruning implementation. Experimental results validate the benefits of the proposed method with reduced memory access, less clock cycle and fewer memory space compared with the conventional implementation.     

Suitability,efficiency and microbiological safety of novel physical technologies for the processing of ready‐to‐eat meals,meats and pumpable products

Consumer studies and market reports show an increase in consumption of ready‐to‐eat (RTE) foods. Although conventional processing technologies can in most cases produce safe products, they can also lead to the degradation of nutritional compounds and negatively affect quality characteristics. Consumers strongly prefer food that is minimally processed with the maximum amount of health‐promoting substances. Novel processing technologies as pre‐ or post‐treatment decontamination methods or as substitutes of conventional technologies have the potential to produce foods that are safe, rich in nutrient content and with superior organoleptic properties. Combining novel with conventional processes can eliminate potential drawbacks of novel technologies. This review examines available scientific information and critically evaluates the suitability and efficiency of various novel thermal and nonthermal technologies in terms of microbial safety, quality as well as nutrient content on the production of RTE meals, meats and pumpable products.     

Three-dimensional rotated digital filters: Design,stability, and applications

Three-dimensional (3-D) signal processing offers many advantages over two-dimensional (2-D) processing, because it preserves 3-D correlations. In this paper the design and the stability of 3-D rotated filters are considered. These filters are designed by rotating a one-dimensional (1-D) digital filter in 3-D space. The rotated filters are valuable in the design of various 3-D filters which possess prescribed spectral specifications. An efficient algorithm for the design of 3-D lowpass (LP) digital filters, with approximately spherically symmetric magnitude responses, is introduced. To achieve the desirable spectral characteristics, a number of 3-D rotated filters is cascaded. The stability of the spherically symmetric filters designed is considered, and stable realizations are proposed. The relation between the cut-off isopotential sphere of the 3-D filter and the cut-off frequency of the 1-D filter employed in the design, is derived. Finally, configurations that result in highpass (HP) and bandpass (BP) filters are proposed. Examples of LP, HP, and BP filters, designed on the basis of the method proposed, are presented.This research was supported by the Public Benefit Foundation, Alexander S. Onassis.     

PBURC: a patterns-based,unsupervised requirements clustering framework for distributed agile software development

Agile software development methodologies are increasingly adopted by organizations because they focus on the client’s needs, thus safeguarding business value for the final product. At the same time, as the economy and society move toward globalization, more organizations shift to distributed development of software projects. From this perspective, while adopting agile techniques seems beneficial, there are still a number of challenges that need to be addressed; among these notable is the effective cooperation between the stakeholders and the geographically distributed development team. In addition, data collection and validation for requirements engineering demands efficient processing techniques in order to handle the volume of data as well as to manage different inconsistencies, when the data are collected using online tools. In this paper, we present “PBURC,” a patterns-based, unsupervised requirements clustering framework, which makes use of machine-learning methods for requirements validation, being able to overcome data inconsistencies and effectively determine appropriate requirements clusters for optimal definition of software development sprints.     

Transition phenomena of polymers in mixed solvents in the vicinity of theta conditions: Effect of preferential adsorption

Viscosimetric measurements were obtained with the ternary systems polystyrene/dioxane/methanol, polystyrene/benzene/methanol and poly(methyl methacrylate)/dioxane/cyclohexane, changing the solvent mixture composition at constant temperature. The polystyrene and poly(methyl methacrylate) systems exhibit a transition phenomenon with solvent-mixture composition in which the polymer is just above the theta condition. In the case where two theta conditions occur ((θ-intra, θ-inter) the transition point is closely related to the intramolecular theta conditions. Moreover the intramolecular theta conditions vary with the molecular weight in the region of molecular weights where the preferential adsorption also varies. This variation induces a variation of the transition point with molecular weight which obeys a formula analogous to that giving the variation of the preferential adsorption with molecular weight.     

3D measures exploitation for a monocular semi-supervised fall detection system

Falls have been reported as the leading cause of injury-related visits to emergency departments and the primary etiology of accidental deaths in elderly. Thus, the development of robust home surveillance systems is of great importance. In this article, such a system is presented, which tries to address the fall detection problem through visual cues. The proposed methodology utilizes a fast, real-time background subtraction algorithm, based on motion information in the scene and pixels intensity, capable to operate properly in dynamically changing visual conditions, in order to detect the foreground object. At the same time, it exploits 3D space’s measures, through automatic camera calibration, to increase the robustness of fall detection algorithm which is based on semi-supervised learning approach. The above system uses a single monocular camera and is characterized by minimal computational cost and memory requirements that make it suitable for real-time large scale implementations.     

Das datenschutzrechtliche Vollzugsdefizit im Bereich der Telemedien — ein Schreckensbericht

Zusammenfassung  Die Autoren untersuchen das datenschutzrechtliche Vollzugsdefizit im Anwendungsbereich des Telemediengesetzes. Ihr Ergebnis ist, dass das Ausma? des datenschutzrechtlichen Vollzugsdefizits der von au?en zu überprüfenden datenschutzrechtlichen Pflichten der Anbieter „erschreckend“ ist. Nur einem ganz geringen Teil der Anbieter gelingt es, sich rechtskonform zu verhalten. Prof. Dr. Jürgen Kühling Inhaber eines Lehrstuhls für ?ffentliches Recht an der Universit?t Regensburg. Anastasios Sivridis wissenschaftlicher Mitarbeiter und Doktorand am Lehrstuhl Prof. Kühling. Mathis Schwuchow studentische Hilfskraft am Lehrstuhl Prof. Kühling. Thorben Burghardt wissenschaftlicher Mitarbeiter und Doktorand am Lehrstuhl für Systeme der Informationsverwaltung (TH Karlsruhe).     

Fracture mechanics‐based progressive damage modelling of adhesively bonded fibre‐reinforced polymer joints

A quasi‐static progressive damage model for prediction of the fracture behaviour and strength of adhesively bonded fibre‐reinforced polymer joints is introduced in this paper. The model is based on the development of a mixed‐mode failure criterion as a function of a master R‐curve derived from the experimental results obtained from standard fracture mechanics joints. Consequently, the developed failure criterion is crack‐length and mode‐mixity dependent, and it takes into account the contribution of the fibre‐bridging effect. Energy release rate values for adhesively bonded double‐lap joints are obtained by using the virtual crack closure technique method in a finite element model, and the numerically obtained strain energy release rate is compared to the critical strain energy release rate given by the mixed‐mode failure criterion. The entire procedure is implemented in a numerical algorithm, which was successfully used for predicting the strength and R‐curve response of adhesively bonded double‐lap structural joints made of pultruded glass fibre‐reinforced polymers and epoxy adhesives.     

Salient feature and reliable classifier selection for facial expression classification

A novel facial expression classification (FEC) method is presented and evaluated. The classification process is decomposed into multiple two-class classification problems, a choice that is analytically justified, and unique sets of features are extracted for each classification problem. Specifically, for each two-class problem, an iterative feature selection process that utilizes a class separability measure is employed to create salient feature vectors (SFVs), where each SFV is composed of a selected feature subset. Subsequently, two-class discriminant analysis is applied on the SFVs to produce salient discriminant hyper-planes (SDHs), which are used to train the corresponding two-class classifiers. To properly integrate the two-class classification results and produce the FEC decision, a computationally efficient and fast classification scheme is developed. During each step of this scheme, the most reliable classifier is identified and utilized, thus, a more accurate final classification decision is produced. The JAFFE and the MMI databases are used to evaluate the performance of the proposed salient-feature-and-reliable-classifier selection (SFRCS) methodology. Classification rates of 96.71% and 93.61% are achieved under the leave-one-sample-out evaluation strategy, and 85.92% under the leave-one-subject-out evaluation strategy.