Organizing resistance movements: contribution of the political discourse theory

The main purpose of this paper is to explore the possibility of articulating Political Discourse Theory (PDT) together with Organizational Studies (OS), while using the opportunity to introduce PDT to those OS scholars who have not yet come across it. The bulk of this paper introduces the main concepts of PDT, discussing how they have been applied to concrete, empirical studies of resistance movements. In recent years, PDT has been increasingly appropriated by OS scholars to problematize and analyze resistances and other forms of social antagonisms within organizational settings, taking the relational and contingent aspects of struggles into consideration. While the paper supports the idea of a joint articulation of PDT and OS, it raises a number of critical questions of how PDT concepts have been empirically used to explain the organization of resistance movements. The paper sets out a research agenda for how both PDT and OS can together contribute to our understanding of new, emerging organizational forms of resistance movements.

Current issues in Social Work Theory

São aqui analisados os discursos sobre as tendências gerais na teoria de Serviço Social. Estes discursos sobre o papel do Serviço Social são tratados no contexto da sociedade, bem como do cliente -assistente sócial -agência. A teoria da prática representa um discurso entre as perspectivas de Serviço Social nos seus aspectos transformacionais, terapêuticos e de ordem social. São também abordadas as suas várias combinações e interacções em todo o tipo de prática e organização de Serviço Social. O discurso sobre a eficácia baseia¬se em estudos comprovados da construção social, potenciação (empowerment), e realismo crítico ainda polémico. A prática reflectiva e crítica constitui os modelos actuais que interligam a teoria e a prática.

A flexible side information generation framework for distributed video coding

One of the most efficient approaches to generate the side information (SI) in distributed video codecs is through motion compensated frame interpolation where the current frame is estimated based on past and future reference frames. However, this approach leads to significant spatial and temporal variations in the correlation noise between the source at the encoder and the SI at the decoder. In such scenario, it would be useful to design an architecture where the SI can be more robustly generated at the block level, avoiding the creation of SI frame regions with lower correlation, largely responsible for some coding efficiency losses. In this paper, a flexible framework to generate SI at the block level in two modes is presented: while the first mode corresponds to a motion compensated interpolation (MCI) technique, the second mode corresponds to a motion compensated quality enhancement (MCQE) technique where a low quality Intra block sent by the encoder is used to generate the SI by doing motion estimation with the help of the reference frames. The novel MCQE mode can be overall advantageous from the rate-distortion point of view, even if some rate has to be invested in the low quality Intra coding blocks, for blocks where the MCI produces SI with lower correlation. The overall solution is evaluated in terms of RD performance with improvements up to 2 dB, especially for high motion video sequences and long Group of Pictures (GOP) sizes.

Low Complexity Intra Mode Selection for Efficient Distributed Video Coding

Motion compensated frame interpolation (MCFI) is one of the most efficient solutions to generate side information (SI) in the context of distributed video coding. However, it creates SI with rather significant motion compensated errors for some frame regions while rather small for some other regions depending on the video content. In this paper, a low complexity Infra mode selection algorithm is proposed to select the most 'critical' blocks in the WZ frame and help the decoder with some reliable data for those blocks. For each block, the novel coding mode selection algorithm estimates the encoding rate for the Intra based and WZ coding modes and determines the best coding mode while maintaining a low encoder complexity. The proposed solution is evaluated in terms of rate-distortion performance with improvements up to 1.2 dB regarding a WZ coding mode only solution.

Sistema de neurónios espelho no síndrome de down: estudo das variações dos ritmos Mu No Eeg

A capacidade de compreensão das acções dos outros e de imitação tem sido descrita como fundamental para a cognição social do ser humano. Recentemente tem sido atribuída a responsabilidade desta capacidade a um sistema neuronal denominado de Sistema de Neurónios Espelho, que se tem demonstrado estar afectado em perturbações mentais que se caracterizam por alterações severas da teoria da mente e da empatia, como é o caso do autismo. No caso do Síndrome de Down, verifica-se a coexistência de boas competências sociais e de capacidades práxicas e de imitação intactas, com dificuldades de interpretação de situações sociais e de reconhecimento de emoções, que nos levam a questionar acerca da actividade do seu Sistema de Neurónios Espelho. As oscilações do ritmo de frequências um (8-13 Hz) no córtex sensório-motor perante a observação de acções são consideradas um reflexo da actividade dos neurónios espelho, estando estabelecido que em pessoas saudáveis ocorre uma supressão mu na realização de movimentos com o membro superior e na sua observação quando realizados por outras pessoas. Neste estudo registou-se electroencefalograficamente a supressão dos ritmos mu em 11 pessoas com SD e em 20 pessoas sem SD nas seguintes condições: observação de um vídeo com duas bolas em movimento, observação de um vídeo com um movimento repetido de uma mão e realização movimentos com a mão. A baseline foi registada através da observação de um ponto estático. Constatamos que existe supressão dos ritmos mu na observação das acções dos outros em pessoas com Síndrome Down da mesma forma que ocorre na realização do próprio movimento, sugerindo uma relativa preservação do funcionamento dos neurónios espelho e dos mecanismos básicos de cognição social. Estes resultados vão de encontro aos estudos que apontam para a integridade das capacidades de imitação no Síndrome Down. Verificamos também que não se encontram diferenças significativas na supressão dos ritmos mu entre os grupos de pessoas com Síndrome Down e de Controlo em relação às condições usadas na investigação.

Augmented LDPC Graph for Distributed Video Coding with Multiple Side Information

The advances made in channel-capacity codes, such as turbo codes and low-density parity-check (LDPC) codes, have played a major role in the emerging distributed source coding paradigm. LDPC codes can be easily adapted to new source coding strategies due to their natural representation as bipartite graphs and the use of quasi-optimal decoding algorithms, such as belief propagation. This paper tackles a relevant scenario in distributedvideo coding: lossy source coding when multiple side information (SI) hypotheses are available at the decoder, each one correlated with the source according to different correlation noise channels. Thus, it is proposed to exploit multiple SI hypotheses through an efficient joint decoding technique withmultiple LDPC syndrome decoders that exchange information to obtain coding efficiency improvements. At the decoder side, the multiple SI hypotheses are created with motion compensated frame interpolation and fused together in a novel iterative LDPC based Slepian-Wolf decoding algorithm. With the creation of multiple SI hypotheses and the proposed decoding algorithm, bitrate savings up to 8.0% are obtained for similar decoded quality.

A hybrid intelligent system for distributed dynamic scheduling

This chapter addresses the resolution of dynamic scheduling by means of meta-heuristic and multi-agent systems. Scheduling is an important aspect of automation in manufacturing systems. Several contributions have been proposed, but the problem is far from being solved satisfactorily, especially if scheduling concerns real world applications. The proposed multi-agent scheduling system assumes the existence of several resource agents (which are decision-making entities based on meta-heuristics) distributed inside the manufacturing system that interact with other agents in order to obtain optimal or near-optimal global performances.

Energy and reserve provision dispatch considering distributed generation and demand response

In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .

Virtual power producers market strategies

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.