Quality-optimization algorithm based on stochastic dynamic programming for MPEG DASH video streaming

In contrast to traditional push-based protocols, adaptive streaming techniques like Dynamic Adaptive Streaming over HTTP (DASH) fix attention on the client, who dynamically requests different-quality portions of the content to cope with a limited and variable bandwidth but aiming at maximizing the quality perceived by the user. Since DASH adaptation logic at the client is not covered by the standard, we propose a solution based on Stochastic Dynamic Programming (SDP) techniques to find the optimal request policies that guarantee the users' Quality of Experience (QoE). Our algorithm is evaluated in a simulated streaming session and is compared with other adaptation approaches. The results show that our proposal outperforms them in terms of QoE, requesting higher qualities on average.

The Balanced Cross-Layer Design Routing Algorithm in Wireless Sensor Networks Using Fuzzy Logic

Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.

Image Segmentation Using Ant System-based Clustering Algorithm

Industrial applications of computer vision sometimes require detection of atypical objects that occur as small groups of pixels in digital images. These objects are difficult to single out because they are small and randomly distributed. In this work we propose an image segmentation method using the novel Ant System-based Clustering Algorithm (ASCA). ASCA models the foraging behaviour of ants, which move through the data space searching for high data-density regions, and leave pheromone trails on their path. The pheromone map is used to identify the exact number of clusters, and assign the pixels to these clusters using the pheromone gradient. We applied ASCA to detection of microcalcifications in digital mammograms and compared its performance with state-of-the-art clustering algorithms such as 1D Self-Organizing Map, k-Means, Fuzzy c-Means and Possibilistic Fuzzy c-Means. The main advantage of ASCA is that the number of clusters needs not to be known a priori. The experimental results show that ASCA is more efficient than the other algorithms in detecting small clusters of atypical data.

SMS-based optimization strategy for ultra-compact SWIR telephoto lens design: erratum

We report and correct an error in [Opt. Express 20, 9726–9735 (2012)]. The author list has been modified. All other contents are unchanged.

SMS-based optimization strategy for ultra-compact SWIR telephoto lens design

A new optical design strategy for rotational aspheres using very few parameters is presented. It consists of using the SMS method to design the aspheres embedded in a system with additional simpler surfaces (such as spheres, parabolas or other conics) and optimizing the free-parameters. Although the SMS surfaces are designed using only meridian rays, skew rays have proven to be well controlled within the optimization. In the end, the SMS surfaces are expanded using Forbes series and then a second optimization process is carried out with these SMS surfaces as a starting point. The method has been applied to a telephoto lens design in the SWIR band, achieving ultra-compact designs with an excellent performance.

Photonic Logic Based on Molecular Reorientation of Nematic Liquid Crystals

A new type of photonic logic, based on the use of nematic liquid crystals is proposed. The system takes advantage of the refractive-index changes induced by laser beams. Examples of AND, OR and NOR functions are presented.

Neuroanatomic-based detection algorithm for automatic labeling of brain structures in brain injury

The number and grade of injured neuroanatomic structures and the type of injury determine the degree of impairment after a brain injury event and the recovery options of the patient. However, the body of knowledge and clinical intervention guides are basically focused on functional disorder and they still do not take into account the location of injuries. The prognostic value of location information is not known in detail either. This paper proposes a feature-based detection algorithm, named Neuroanatomic-Based Detection Algorithm (NBDA), based on SURF (Speeded Up Robust Feature) to label anatomical brain structures on cortical and sub-cortical areas. Themain goal is to register injured neuroanatomic structures to generate a database containing patient?s structural impairment profile. This kind of information permits to establish a relation with functional disorders and the prognostic evolution during neurorehabilitation procedures.

Mission profile based optimization of a wearable power system

A Wearable Power System (WPS) is a portable power source utilized primarily to power the modern soldier’s electronic equipment. Such a system has to satisfy output power demands in the range of 20 W...200 W, specified as a 4-day mission profile and has a weight limit of 4 kg. To meet these demands, an optimization of a WPS, comprising an internal combustion (IC) engine, permanent magnetic three-phase electrical motor/generator, inverter, Li-batteries, DC-DC converters, and controller, is performed in this paper. The mechanical energy extracted from the fuel by IC engine is transferred to the generator that is used to recharge the battery and provide the power to the electrical output load. The main objectives are to select the engine, fuel and battery type, to match the weight of fuel and the number of battery cells, to find the optimal working point of engine and to minimize the system weight. To provide the second output voltage level of 14 VDC, a separate DC-DC converter is connected between the battery and the load, and optimized for the specified mission profile. A prototype of the WPS based on the optimization presented in the paper results in a total system weight of 3.9 kg and fulfils the mission profile.

A Multi Ant Colony Optimization algorithm for a Mixed Car Assembly Line

This paper presents an ant colony optimization algorithm to sequence the mixed assembly lines considering the inventory and the replenishment of components. This is a NP-problem that cannot be solved to optimality by exact methods when the size of the problem growth. Groups of specialized ants are implemented to solve the different parts of the problem. This is intended to differentiate each part of the problem. Different types of pheromone structures are created to identify good car sequences, and good routes for the replenishment of components vehicle. The contribution of this paper is the collaborative approach of the ACO for the mixed assembly line and the replenishment of components and the jointly solution of the problem.

Offline GA-Based optimization for heterogeneous modular multi-configurable chained microrobots

This paper presents a GA-based optimization procedure for bioinspired heterogeneous modular multiconfigurable chained microrobots. When constructing heterogeneous chained modular robots that are composed of several different drive modules, one must select the type and position of the modules that form the chain. One must also develop new locomotion gaits that combine the different drive modules. These are two new features of heterogeneous modular robots that they do not share with homogeneous modular robots. This paper presents an offline control system that allows the development of new configuration schemes and locomotion gaits for these heterogeneous modular multiconfigurable chained microrobots. The offline control system is based on a simulator that is specifically designed for chained modular robots and allows them to develop and learn new locomotion patterns.

Automated end user-centred adaptation of web components through automated description logic-based reasoning

Context: This paper addresses one of the major end-user development (EUD) challenges, namely, how to pack today?s EUD support tools with composable elements. This would give end users better access to more components which they can use to build a solution tailored to their own needs. The success of later end-user software engineering (EUSE) activities largely depends on how many components each tool has and how adaptable components are to multiple problem domains. Objective: A system for automatically adapting heterogeneous components to a common development environment would offer a sizeable saving of time and resources within the EUD support tool construction process. This paper presents an automated adaptation system for transforming EUD components to a standard format. Method: This system is based on the use of description logic. Based on a generic UML2 data model, this description logic is able to check whether an end-user component can be transformed to this modeling language through subsumption or as an instance of the UML2 model. Besides it automatically finds a consistent, non-ambiguous and finite set of XSLT mappings to automatically prepare data in order to leverage the component as part of a tool that conforms to the target UML2 component model. Results: The proposed system has been successfully applied to components from four prominent EUD tools. These components were automatically converted to a standard format. In order to validate the proposed system, rich internet applications (RIA) used as an operational support system for operators at a large services company were developed using automatically adapted standard format components. These RIAs would be impossible to develop using each EUD tool separately. Conclusion: The positive results of applying our system for automatically adapting components from current tool catalogues are indicative of the system?s effectiveness. Use of this system could foster the growth of web EUD component catalogues, leveraging a vast ecosystem of user-centred SaaS to further current EUSE trends.

Surrogate-based optimization of the nose shape of a train subjected to crosswind

Optimización multi-objetivo frente a varias direcciones del viento incidente del testero de un tren de alta velocidad

Towards description and optimization of abstract machines in an extension of prolog

Competitive abstract machines for Prolog are usually large, intricate, and incorpórate sophisticated optimizations. This makes them difñcult to code, optimize, and, especially, maintain and extend. This is partly due to the fact that efñciency considerations make it necessary to use low-level languages in their implementation. Writing the abstract machine (and ancillary code) in a higher-level language can help harness this inherent complexity. In this paper we show how the semantics of basic components of an efficient virtual machine for Prolog can be described using (a variant of) Prolog which retains much of its semantics. These descriptions are then compiled to C and assembled to build a complete bytecode emulator. Thanks to the high level of the language used and its closeness to Prolog the abstract machine descriptions can be manipulated using standard Prolog compilation and optimization techniques with relative ease. We also show how, by applying program transformations selectively, we obtain abstract machine implementations whose performance can match and even exceed that of highly-tuned, hand-crafted emulators.

Combined static and dynamic assertion-based debugging of constraint logic programs

We propose a general framework for assertion-based debugging of constraint logic programs. Assertions are linguistic constructions for expressing properties of programs. We define several assertion schemas for writing (partial) specifications for constraint logic programs using quite general properties, including user-defined programs. The framework is aimed at detecting deviations of the program behavior (symptoms) with respect to the given assertions, either at compile-time (i.e., statically) or run-time (i.e., dynamically). We provide techniques for using information from global analysis both to detect at compile-time assertions which do not hold in at least one of the possible executions (i.e., static symptoms) and assertions which hold for all possible executions (i.e., statically proved assertions). We also provide program transformations which introduce tests in the program for checking at run-time those assertions whose status cannot be determined at compile-time. Both the static and the dynamic checking are provably safe in the sense that all errors flagged are definite violations of the pecifications. Finally, we report briefly on the currently implemented instances of the generic framework.

A generic framework for the analysis and specialization of logic programs

The relationship between abstract interpretation and partial deduction has received considerable attention and (partial) integrations have been proposed starting from both the partial deduction and abstract interpretation perspectives. In this work we present what we argüe is the first fully described generic algorithm for efñcient and precise integration of abstract interpretation and partial deduction. Taking as starting point state-of-the-art algorithms for context-sensitive, polyvariant abstract interpretation and (abstract) partial deduction, we present an algorithm which combines the best of both worlds. Key ingredients include the accurate success propagation inherent to abstract interpretation and the powerful program transformations achievable by partial deduction. In our algorithm, the calis which appear in the analysis graph are not analyzed w.r.t. the original definition of the procedure but w.r.t. specialized definitions of these procedures. Such specialized definitions are obtained by applying both unfolding and abstract executability. Our framework is parametric w.r.t. different control strategies and abstract domains. Different combinations of such parameters correspond to existing algorithms for program analysis and specialization. Simultaneously, our approach opens the door to the efñcient computation of strictly more precise results than those achievable by each of the individual techniques. The algorithm is now one of the key components of the CiaoPP analysis and specialization system.