Valuation: Developer support for by-references to by-value type conversion.

Modern object oriented languages like C# and JAVA enable developers to build complex application in less time. These languages are based on selecting heap allocated pass-by-reference objects for user defined data structures. This simplifies programming by automatically managing memory allocation and deallocation in conjunction with automated garbage collection. This simplification of programming comes at the cost of performance. Using pass-by-reference objects instead of lighter weight pass-by value structs can have memory impact in some cases. These costs can be critical when these application runs on limited resource environments such as mobile devices and cloud computing systems. We explore the problem by using the simple and uniform memory model to improve the performance. In this work we address this problem by providing an automated and sounds static conversion analysis which identifies if a by reference type can be safely converted to a by value type where the conversion may result in performance improvements. This works focus on C# programs. Our approach is based on a combination of syntactic and semantic checks to identify classes that are safe to convert. We evaluate the effectiveness of our work in identifying convertible types and impact of this transformation. The result shows that the transformation of reference type to value type can have substantial performance impact in practice. In our case studies we optimize the performance in Barnes-Hut program which shows total memory allocation decreased by 93% and execution time also reduced by 15%.

Modelo de Gestión del Conocimiento para la Competitividad del Sector de las Construcciones Petroleras, Petroquímicas y Energéticas Venezolanas

La construcción es una de las actividades más valiosas para la sociedad debido a la naturaleza de los servicios que ofrece y por el volumen de empleos y movimiento económico que genera. Por ello es un elemento fundamental para el desarrollo sustentable. Es una industria compleja, cada vez más dependiente del conocimiento. Debido a su naturaleza fragmentaria y temporal y la alta rotación de personal presenta grandes retos y complicaciones particulares. Estas dificultades en oportunidades pueden transformarse en problemas por la complejidad, localización geográfica o los requisitos técnicos, financieros e innovaciones de los proyectos. Debido a sus características, las construcciones sufren cambios en las condiciones planificadas. Con frecuencia estos cambios conducen a retrasos en la ejecución de los proyectos, costes superiores a los presupuestados y conflictos entre los clientes y los ejecutores. Esto genera problemas de competitividad que afectan tanto a países desarrollados como países en vías de desarrollo. Los problemas de la construcción tienen perniciosos efectos para la sociedad, que pierde recursos que deberían permitir mejores resultados en términos de calidad de vida y beneficios sociales y económicos. Debido a la importancia del sector y los ingentes recursos que se invierten en cada proyecto se justifican los máximos esfuerzos para lograr los mejores desempeños de esta industria. Éste interés ha orientado el desarrollo de investigaciones, para apoyar el logro de los objetivos de mejoramiento continuo y construcción sustentable. Los estudios desarrollados han permitido demostrar el valor añadido del conocimiento en todos los sectores productivos. Para la construcción, los conocimientos ofrecen indicadores de desempeño, datos y lecciones aprendidas provenientes de aciertos y errores. Estos deben conducir a aprendizajes fundamentales para sustentar su competitividad. Sin embargo, a pesar de los conocimientos disponibles y los avances en las técnicas de control gerencial y de proyectos, es alarmante la recurrencia de los problemas de construcción. Esta problemática se manifiesta con severidad en los proyectos de construcción industrial que se desarrollan para el sector petrolero, petroquímico y energético venezolano. El sector presenta evidentes necesidades para un mejor desempeño competitivo por la alta incidencia de retrasos de los proyectos, que implican pérdidas de gran parte de los recursos humanos, financieros, técnicos y conocimientos invertidos. Esta investigación plantea como objetivos analizar la importancia de la construcción y su sustentabilidad, los principales problemas que afectan el sector, la gestión del conocimiento y algunos modelos disponibles para gestionarlos. Igualmente examina las lecciones aprendidas y la productividad y competitividad, con particular atención a los problemas de competitividad venezolanos. Adicionalmente se evalúan las implicaciones del conocimiento como activo estratégico y se caracterizan las empresas de construcción industrial venezolanas. Para ello se identifican las dimensiones que sustentan la gestión del conocimiento en estas empresas, para finalmente determinar las que resultan más idóneas para el nuevo modelo a ser propuesto. Con estos objetivos se desarrolló el estudio empírico. Para ello fueron invitados a participar representantes de 105 empresas y expertos de construcción distintos, todos con experiencias de construcción al sector industrial venezolano. Se obtuvieron 112 respuestas en representación de 41 organizaciones y expertos diferentes. El trabajo de campo inició en Junio de 2012 y culminó en Noviembre de 2012. Los datos obtenidos fueron analizados con apoyo de técnicas estadísticas descriptivas y multivariables. Los objetivos de la investigación se alcanzaron ya que se logró caracterizar el sector de las construcciones industriales y se propuso un nuevo modelo de gestión del conocimiento adecuado a sus características. El nuevo modelo fue formulado atendiendo a criterios de sencillez, bajos costes y facilidad de adaptación para motivar su utilización en organizaciones de construcción industrial variadas. Con ello se busca que resulte de utilidad aún para las organizaciones más pequeñas, con menores recursos o aquellas que enfrentan entornos constructivos complicados. Por último se presentan algunas sugerencias para motivar la comprensión de los fenómenos estudiados en los grupos de interés de la construcción. Se propone analizar estos problemas desde las etapas iniciales de los estudios de ingeniería, de arquitectura, de construcción, de economía y administración. Igualmente se propone desarrollar acciones conjuntas de parte de los sectores académicos, gubernamentales, industriales y asociaciones para el mejoramiento competitivo y desarrollo sustentable global. La propuesta aporta datos sobre el sector constructivo venezolano en un área que presenta grandes carencias y propone un modelo innovador por su sencillez y orientación hacia el uso diario e intuitivo de los conocimientos como recursos fundamentales para la competitividad. Esta orientación puede tener trascendencia más allá del sector descrito, para apoyar la solución de problemas de otras industrias en entornos globales. ABSTRACT Construction is one of the most valuable activities for society due to the nature of the services offered and the number of jobs and revenues generated. Therefore it is a key element for sustainable development. Construction is a complex industry increasingly dependent on knowledge. Its temporary and fragmentary nature and the high staff turnover present great challenges and particular complications to construction. In some cases these conditions may evolve to serious problems because of the complexity, geographic location or even technical, financial and innovative requirements of each project. Due to their characteristics, constructions frequently undergo changes in planned conditions. Often these changes lead to delays in project completion, costs higher than budgeted and conflicts between clients and performers. This creates problems of competitiveness affecting both developed and developing countries. The construction problems have harmful effects on society, since it loses resources that would otherwise allow better results in terms of quality of life and social and economic benefits. The importance and the enormous resources invested in each project justify the efforts to achieve the best performance of this industry. This interest has guided the development of multiple research efforts to support the achievement of construction performance improvements and sustainable construction. The studies carried out have demonstrated the added value of knowledge in all productive sectors. For construction, knowledge offers performance indicators, data and lessons learned from successes and failures. These should lead to fundamental learning to sustain sector competitiveness. However, despite the available knowledge and advances in techniques and project management control, the recurrence of construction problems is alarming. This problem shows itself severely in industrial construction projects that are developed for the Venezuelan oil, petrochemical and energy sectors. These sectors have evident needs for better competitive performance because of the high incidence of project delays, involving loss of much of the human, financial, technical and knowledge resources invested. This research analyzes the importance of construction and sustainability, the main problems affecting the sector, knowledge and some models available to manage them. It also examines the lessons learned and the productivity and competitiveness, with particular attention to the problems of Venezuelan competitiveness. Additionally, the Venezuelan industrial construction companies are characterized evaluating the implications of knowledge as an strategic asset for construction. Moreover, the research evaluates the dimensions that support knowledge management in these companies, to finally identify those that are the most suitable for the new model to be proposed. With these objectives in mind the empirical study was developed. 105 different companies and experts with Venezuelan industrial construction experiences were invited to participate on the survey. 112 responses were obtained representing 41 different organizations and experts. Fieldwork started in June 2012 and ended in November 2012. The data obtained was analyzed with descriptive and multivariate statistical techniques. The research objectives were achieved since the industrial construction sector was characterized and a new management model was proposed based on the particular characteristics of these companies. The new model was formulated according to the criteria of simplicity, low cost and ease of adaptation. This was performed to motivate the use of the new model in various industrial construction organizations, even in smaller companies, with limited resources or those facing complex construction environments. Finally some suggestions to encourage understanding of the phenomena studied among construction stakeholders were proposed. The importance of studying these problems at an early stage of the engineering, architectural, construction, economic and administration studies is highlighted. Additionally, academic, government, industrial organizations and associations are invited to join efforts to improve the competitive and sustainable global development. The proposal provides data on the Venezuelan construction sector in an area that has large gaps and proposes a model which is innovative for its simplicity and suggests the daily and intuitive use of knowledge resources as a key issue to competitiveness. This orientation may have implications beyond the described sector to support the solution of problems of other industries in a global environment.

Enriquecimiento de fuentes de datos con descripciones lingüísticas mediante bases de datos geográficas externas

El presente trabajo se ha centrado en la investigación de soluciones para automatizar la tarea del enriquecimiento de fuentes de datos sobre redes de sensores con descripciones lingüísticas, con el fin de facilitar la posterior generación de textos en lenguaje natural. El uso de descripciones en lenguaje natural facilita el acceso a los datos a una mayor diversidad de usuarios y, como consecuencia, permite aprovechar mejor las inversiones en redes de sensores. En el trabajo se ha considerado el uso de bases de datos abiertas para abordar la necesidad de disponer de un gran volumen y diversidad de conocimiento geográfico. Se ha analizado también el enriquecimiento de datos dentro de enfoques metodológicos de curación de datos y métodos de generación de lenguaje natural. Como resultado del trabajo, se ha planteado un método general basado en una estrategia de generación y prueba que incluye una forma de representación y uso del conocimiento heurístico con varias etapas de razonamiento para la construcción de descripciones lingüísticas de enriquecimiento de datos. En la evaluación de la propuesta general se han manejado tres escenarios, dos de ellos para generación de referencias geográficas sobre redes de sensores complejas de dimensión real y otro para la generación de referencias temporales. Los resultados de la evaluación han mostrado la validez práctica de la propuesta general exhibiendo mejoras de rendimiento respecto a otros enfoques. Además, el análisis de los resultados ha permitido identificar y cuantificar el impacto previsible de diversas líneas de mejora en bases de datos abiertas. ABSTRACT This work has focused on the search for solutions to automate the task of enrichment sensor-network-based data sources with textual descriptions, so as to facilitate the generation of natural language texts. Using natural language descriptions facilitates data access to a wider range of users and, therefore, allows better leveraging investments in sensor networks. In this work we have considered the use of open databases to address the need for a large volume and diversity of geographical knowledge. We have also analyzed data enrichment in methodological approaches and data curation methods of natural language generation. As a result, it has raised a general method based on a strategy of generating and testing that includes a representation using heuristic knowledge with several stages of reasoning for the construction of linguistic descriptions of data enrichment. In assessing the overall proposal three scenarios have been addressed, two of them in the environmental domain with complex sensor networks and another real dimension in the time domain. The evaluation results have shown the validity and practicality of our proposal, showing performance improvements over other approaches. Furthermore, the analysis of the results has allowed identifying and quantifying the expected impact of various lines of improvement in open databases.

Introduction to Special issue on Reconfigurable computing and FPGAs

During the last three decades, FPGA technology has quickly evolved to become a major subject of research in computer and electrical engineering as it has been identified as a powerful alternative for creating highly efficient computing systems. FPGA devices offer substantial performance improvements when compared against traditional processing architectures via custom design and reconfiguration capabilities.

Image Noise Removal on Heterogeneous CPU-GPU Configurations

A parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU computing is proposed. The parallel denoising algorithm is based on the peer group concept and uses an Euclidean metric. In order to identify the amount of pixels to be allocated in multi-core and GPUs, a performance analysis using large images is presented. A comparison of the parallel implementation in multi-core, GPUs and a combination of both is performed. Performance has been evaluated in terms of execution time and Megapixels/second. We present several optimization strategies especially effective for the multi-core environment, and demonstrate significant performance improvements. The main advantage of the proposed noise removal methodology is its computational speed, which enables efficient filtering of color images in real-time applications.

Neuromuscular adaptation during skill acquisition on a two degree-of-freedom target-acquisition task: Isometric torque production

In this study we attempted to identify the principles that govern the changes in neural control that occur during repeated performance of a multiarticular coordination task. Eight participants produced isometric flexion/extension and pronation/supination torques at the radiohumeral joint, either in isolation (e.g., flexion) or in combination (e.g., flexion - supination), to acquire targets presented by a visual display. A cursor superimposed on the display provided feedback of the applied torques. During pre- and postpractice tests, the participants acquired targets in eight directions located either 3.6 cm (20% maximal voluntary contraction [MVC]) or 7.2 cm (40% MVC) from a neutral cursor position. On each of five consecutive days of practice the participants acquired targets located 5.4 cm (30% MVC) from the neutral position. EMG was recorded from eight muscles contributing to torque production about the radiohumeral joint during the pre- and posttests. Target-acquisition time decreased significantly with practice in most target directions and at both target torque levels. These performance improvements were primarily associated with increases in the peak rate of torque development after practice. At a muscular level, these changes were brought about by increases in the rates of recruitment of all agonist muscles. The spatiotemporal organization of muscle synergies was not significantly altered after practice. The observed adaptations appear to lead to performances that are generalizable to actions that require both greater and smaller joint torques than that practiced, and may be successfully recalled after a substantial period without practice. These results suggest that tasks in which performance is improved by increasing the rate of muscle activation, and thus the rate of joint torque development, may benefit in terms of the extent to which acquired levels of performance are maintained over time.

Neuromuscular adaptation during skill acquisition on a two degree-of-freedom target-acquisition task: Dynamic movement

In this experiment, we examined the extent to which the spatiotemporal reorganization of muscle synergies mediates skill acquisition on a two degree-of-freedom (df) target-acquisition task. Eight participants completed five practice sessions on consecutive days. During each session they practiced movements to eight target positions presented by a visual display. The movements required combinations of flexion/extension and pronation/supination of the elbow joint complex. During practice sessions, eight targets displaced 5.4 cm from the start position ( representing joint excursions of 54) were presented 16 times. During pre- and posttests, participants acquired the targets at two distances (3.6 cm [36 degrees] and 7.2 cm [72 degrees]). EMG data were recorded from eight muscles contributing to the movements during the pre- and posttests. Most targets were acquired more rapidly after the practice period. Performance improvements were, in most target directions, accompanied by increases in the smoothness of the movement trajectories. When target acquisition required movement in both dfs, there were also practice-related decreases in the extent to which the trajectories deviated from a direct path to the target. The contribution of monofunctional muscles ( those producing torque in a single df) increased with practice during movements in which they acted as agonists. The activity in bifunctional muscles ( those contributing torque in both dfs) remained at pretest levels in most movements. The results suggest that performance gains were mediated primarily by changes in the spatial organization of muscles synergies. These changes were expressed most prominently in terms of the magnitude of activation of the monofunctional muscles.

ADSL transceivers applying DSM and their nonstationary noise robustness

Dynamic spectrum management (DSM) comprises a new set of techniques for multiuser power allocation and/or detection in digital subscriber line (DSL) networks. At the Alcatel Research and Innovation Labs, we have recently developed a DSM test bed, which allows the performance of DSM algorithms to be evaluated in practice. With this test bed, we have evaluated the performance of a DSM level-1 algorithm known as iterative water-filling in an ADSL scenario. This paper describes the results of, on the one hand, the performance gains achieved with iterative water-filling, and, on the other hand, the nonstationary noise robustness of DSM-enabled ADSL modems. It will be shown that DSM trades off nonstationary noise robustness for performance improvements. A new bit swap procedure is then introduced to increase the noise robustness when applying DSM.

Improving support vector solutions by selecting a sequence of training subsets

In this paper we demonstrate that it is possible to gradually improve the performance of support vector machine (SVM) classifiers by using a genetic algorithm to select a sequence of training subsets from the available data. Performance improvement is possible because the SVM solution generally lies some distance away from the Bayes optimal in the space of learning parameters. We illustrate performance improvements on a number of benchmark data sets.

Clustering strategies for object databases

When object databases arrived on the scene some ten years ago, they provided database capabilities for previously neglected, complex applications, such as CAD, but were burdened with one inherent teething problem, poor performance. Physical database design is one tool that can provide performance improvements and it is the general area of concern for this thesis. Clustering is one fruitful design technique which can provide improvements in performance. However, clustering in object databases has not been explored in depth and so has not been truly exploited. Further, clustering, although a physical concern, can be determined from the logical model. The object model is richer than previous models, notably the relational model, and so it is anticipated that the opportunities with respect to clustering are greater. This thesis provides a thorough analysis of object clustering strategies with a view to highlighting any links between the object logical and physical model and improving performance. This is achieved by considering all possible types of object logical model construct and the implementation of those constructs in terms of theoretical clusterings strategies to produce actual clustering arrangements. This analysis results in a greater understanding of object clustering strategies, aiding designers in the development process and providing some valuable rules of thumb to support the design process.

The design of a support department simulator for use in the design of manufacturing systems

Manufacturing firms are driven by competitive pressures to continually improve the effectiveness and efficiency of their organisations. For this reason, manufacturing engineers often implement changes to existing processes, or design new production facilities, with the expectation of making further gains in manufacturing system performance. This thesis relates to how the likely outcome of this type of decision should be predicted prior to its implementation. The thesis argues that since manufacturing systems must also interact with many other parts of an organisation, the expected performance improvements can often be significantly hampered by constraints that arise elsewhere in the business. As a result, decision-makers should attempt to predict just how well a proposed design will perform when these other factors, or 'support departments', are taken into consideration. However, the thesis also demonstrates that, in practice, where quantitative analysis is used to evaluate design decisions, the analysis model invariably ignores the potential impact of support functions on a system's overall performance. A more comprehensive modelling approach is therefore required. A study of how various business functions interact establishes that to properly represent the kind of delays that give rise to support department constraints, a model should actually portray the dynamic and stochastic behaviour of entities in both the manufacturing and non-manufacturing aspects of a business. This implies that computer simulation be used to model design decisions but current simulation software does not provide a sufficient range of functionality to enable the behaviour of all of these entities to be represented in this way. The main objective of the research has therefore been the development of a new simulator that will overcome limitations of existing software and so enable decision-makers to conduct a more holistic evaluation of design decisions. It is argued that the application of object-oriented techniques offers a potentially better way of fulfilling both the functional and ease-of-use issues relating to development of the new simulator. An object-oriented analysis and design of the system, called WBS/Office, are therefore presented that extends to modelling a firm's administrative and other support activities in the context of the manufacturing system design process. A particularly novel feature of the design is the ability for decision-makers to model how a firm's specific information and document processing requirements might hamper shop-floor performance. The simulator is primarily intended for modelling make-to-order batch manufacturing systems and the thesis presents example models created using a working version of WBS/Office that demonstrate the feasibility of using the system to analyse manufacturing system designs in this way.

Impact of longitudinal power budget in coherent transmission systems employing digital back-propagation

We report the impact of longitudinal signal power profile on the transmission performance of coherently-detected 112 Gb/s m-ary polarization multiplexed quadrature amplitude modulation system after compensation of deterministic nonlinear fibre impairments. Performance improvements up to 0.6 dB (Q(eff)) are reported for a non-uniform transmission link power profile. Further investigation reveals that the evolution of the transmission performance with power profile management is fully consistent with the parametric amplification of the amplified spontaneous emission by the signal through four-wave mixing. In particular, for a non-dispersion managed system, a single-step increment of 4 dB in the amplifier gain, with respect to a uniform gain profile, at similar to 2/3(rd) of the total reach considerably improves the transmission performance for all the formats studied. In contrary a negative-step profile, emulating a failure (gain decrease or loss increase), significantly degrades the bit-error rate.

Impact of longitudinal power budget in coherent transmission systems employing digital back-propagation

We report the impact of longitudinal signal power profile on the transmission performance of coherently-detected 112 Gb/s m-ary polarization multiplexed quadrature amplitude modulation system after compensation of deterministic nonlinear fibre impairments. Performance improvements up to 0.6 dB (Q(eff)) are reported for a non-uniform transmission link power profile. Further investigation reveals that the evolution of the transmission performance with power profile management is fully consistent with the parametric amplification of the amplified spontaneous emission by the signal through four-wave mixing. In particular, for a non-dispersion managed system, a single-step increment of 4 dB in the amplifier gain, with respect to a uniform gain profile, at similar to 2/3(rd) of the total reach considerably improves the transmission performance for all the formats studied. In contrary a negative-step profile, emulating a failure (gain decrease or loss increase), significantly degrades the bit-error rate.

QPSK 3R regenerator using a phase sensitive amplifier

A black box phase sensitive amplifier based 3R regeneration scheme is proposed for non-return to zero quadrature phase shift keyed formatted signals. Performance improvements of more than 2 dB are achieved at the presence of input phase distortion.

System-on-a-Chip (SoC) based hardware acceleration in Register Transfer Level (RTL) design

Today, modern System-on-a-Chip (SoC) systems have grown rapidly due to the increased processing power, while maintaining the size of the hardware circuit. The number of transistors on a chip continues to increase, but current SoC designs may not be able to exploit the potential performance, especially with energy consumption and chip area becoming two major concerns. Traditional SoC designs usually separate software and hardware. Thus, the process of improving the system performance is a complicated task for both software and hardware designers. The aim of this research is to develop hardware acceleration workflow for software applications. Thus, system performance can be improved with constraints of energy consumption and on-chip resource costs. The characteristics of software applications can be identified by using profiling tools. Hardware acceleration can have significant performance improvement for highly mathematical calculations or repeated functions. The performance of SoC systems can then be improved, if the hardware acceleration method is used to accelerate the element that incurs performance overheads. The concepts mentioned in this study can be easily applied to a variety of sophisticated software applications. The contributions of SoC-based hardware acceleration in the hardware-software co-design platform include the following: (1) Software profiling methods are applied to H.264 Coder-Decoder (CODEC) core. The hotspot function of aimed application is identified by using critical attributes such as cycles per loop, loop rounds, etc. (2) Hardware acceleration method based on Field-Programmable Gate Array (FPGA) is used to resolve system bottlenecks and improve system performance. The identified hotspot function is then converted to a hardware accelerator and mapped onto the hardware platform. Two types of hardware acceleration methods – central bus design and co-processor design, are implemented for comparison in the proposed architecture. (3) System specifications, such as performance, energy consumption, and resource costs, are measured and analyzed. The trade-off of these three factors is compared and balanced. Different hardware accelerators are implemented and evaluated based on system requirements. 4) The system verification platform is designed based on Integrated Circuit (IC) workflow. Hardware optimization techniques are used for higher performance and less resource costs. Experimental results show that the proposed hardware acceleration workflow for software applications is an efficient technique. The system can reach 2.8X performance improvements and save 31.84% energy consumption by applying the Bus-IP design. The Co-processor design can have 7.9X performance and save 75.85% energy consumption.