Self-scheduling and bidding strategies of thermal units with stochastic emission constraints

This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies. (C) 2014 Elsevier Ltd. All rights reserved.

Negotiation mechanism for self-organized scheduling system with collective intelligence

Current Manufacturing Systems challenges due to international economic crisis, market globalization and e-business trends, incites the development of intelligent systems to support decision making, which allows managers to concentrate on high-level tasks management while improving decision response and effectiveness towards manufacturing agility. This paper presents a novel negotiation mechanism for dynamic scheduling based on social and collective intelligence. Under the proposed negotiation mechanism, agents must interact and collaborate in order to improve the global schedule. Swarm Intelligence (SI) is considered a general aggregation term for several computational techniques, which use ideas and inspiration from the social behaviors of insects and other biological systems. This work is primarily concerned with negotiation, where multiple self-interested agents can reach agreement over the exchange of operations on competitive resources. Experimental analysis was performed in order to validate the influence of negotiation mechanism in the system performance and the SI technique. Empirical results and statistical evidence illustrate that the negotiation mechanism influence significantly the overall system performance and the effectiveness of Artificial Bee Colony for makespan minimization and on the machine occupation maximization.

Aryleneethynylene Trimers Bearing Calix[4]arenes: synthesis, optical properties and self-assembling studies

New homoditopic bis-calix[4]arene-carbazole conjugates, armed with hydrophilic carboxylic acid functions at their lower rims, are disclosed. Evidence for their self-association in solution was gathered from solvatochromic and thermochromic studies, as well as from gel-permeation chromatography analysis. Their ability to function as highly sensitive sensors toward polar electron-deficient aromatic compounds is demonstrated.

Double power laws, fractals and self-similarity

Power law (PL) distributions have been largely reported in the modeling of distinct real phenomena and have been associated with fractal structures and self-similar systems. In this paper, we analyze real data that follows a PL and a double PL behavior and verify the relation between the PL coefficient and the capacity dimension of known fractals. It is to be proved a method that translates PLs coefficients into capacity dimension of fractals of any real data.

Temperature-induced structural transitions in self-assembling magnetic nanocolloids

With the help of a unique combination of density functional theory and computer simulations, we discover two possible scenarios, depending on concentration, for the hierarchical self-assembly of magnetic nanoparticles on cooling. We show that typically considered low temperature clusters, i.e. defect-free chains and rings, merge into more complex branched structures through only three types of defects: four-way X junctions, three-way Y junctions and two-way Z junctions. Our accurate calculations reveal the predominance of weakly magnetically responsive rings cross-linked by X defects at the lowest temperatures. We thus provide a strategy to fine-tune magnetic and thermodynamic responses of magnetic nanocolloids to be used in medical and microfluidics applications.

Durability performance of self-compacting concrete (SCC) with binary and ternary mixes of fly ash and limestone filler

The basic objective of this work is to evaluate the durability of self-compacting concrete (SCC) produced in binary and ternary mixes using fly ash (FA) and limestone filler (LF) as partial replacement of cement. The main characteristics that set SCC apart from conventional concrete (fundamentally its fresh state behaviour) essentially depend on the greater or lesser content of various constituents, namely: greater mortar volume (more ultrafine material in the form of cement and mineral additions); proper control of the maximum size of the coarse aggregate; use of admixtures such as superplasticizers. Significant amounts of mineral additions are thus incorporated to partially replace cement, in order to improve the workability of the concrete. These mineral additions necessarily affect the concrete’s microstructure and its durability. Therefore, notwithstanding the many well-documented and acknowledged advantages of SCC, a better understanding its behaviour is still required, in particular when its composition includes significant amounts of mineral additions. An ambitious working plan was devised: first, the SCC’s microstructure was studied and characterized and afterwards the main transport and degradation mechanisms of the SCC produced were studied and characterized by means of SEM image analysis, chloride migration, electrical resistivity, and carbonation tests. It was then possible to draw conclusions about the SCC’s durability. The properties studied are strongly affected by the type and content of the additions. Also, the use of ternary mixes proved to be extremely favourable, confirming the expected beneficial effect of the synergy between LF and FA. © 2015 RILEM.

Comparative study on the localization of adult Schistosoma mansoni worms in albino mice anesthetized with pentobarbital sodium, ether or chlorophorm

The effect of anesthetic drugs on the localization of adult worms in albino mice was compared. The animals with 56 days of infection were anesthetized with pentobarbital sodium, ether or chlorophorm. Perfusion was carried out immediately after, recovering the worms and classifying them in relation to their localization on the liver or portal vein and the mesenteric veins. Our results showed that pentobarbital sodium produced a greater displacement of the worms to the liver (89%) than ether (76%) and chlorophorm (34%) did, when compared to the control group (22%). The difference between pentobarbital sodium and ether was significant (p < 0.05). We suggest that anesthetic drugs may not be used in studies on the distribution of adult worms in several hosts.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.

Geo-localization System for People with Cognitive Disabilities

Technology is present in almost every simple aspect of the people’s daily life. As an instance, let us refer to the smartphone. This device is usually equipped with a GPS modulewhich may be used as an orientation system, if it carries the right functionalities. The problem is that these applications may be complex to operate and may not be within the bounds of everybody. Therefore, the main goal here is to develop an orientation system that may help people with cognitive disabilities in their day-to-day journeys, when the caregivers are absent. On the other hand, to keep paid helpers aware of the current location of the disable people, it will be also considered a localization system. Knowing their current locations, caregiversmay engage in others activities without neglecting their prime work, and, at the same time, turning people with cognitive disabilities more independent.

Step count algorithm adapted to indoor localization

This paper presents a step count algorithm designed to work in real-time using low computational power. This proposal is our first step for the development of an indoor navigation system, based on Pedestrian Dead Reckoning (PDR). We present two approaches to solve this problem and compare them based in their error on step counting, as well as, the capability of their use in a real time system.

Traveled Distance Estimation Algorithm for Indoor Localization

This paper presents an ankle mounted Inertial Navigation System (INS) used to estimate the distance traveled by a pedestrian. This distance is estimated by the number of steps given by the user. The proposed method is based on force sensors to enhance the results obtained from an INS. Experimental results have shown that, depending on the step frequency, the traveled distance error varies between 2.7% and 5.6%.

Person Localization Using Sensor Information Fusion

Nowadays the incredible grow of mobile devices market led to the need for location-aware applications. However, sometimes person location is difficult to obtain, since most of these devices only have a GPS (Global Positioning System) chip to retrieve location. In order to suppress this limitation and to provide location everywhere (even where a structured environment doesn’t exist) a wearable inertial navigation system is proposed, which is a convenient way to track people in situations where other localization systems fail. The system combines pedestrian dead reckoning with GPS, using widely available, low-cost and low-power hardware components. The system innovation is the information fusion and the use of probabilistic methods to learn persons gait behavior to correct, in real-time, the drift errors given by the sensors.

Localization system for pedestrians based on sensor and information fusion

Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device's GPS chip. This means that in indoor or in more dense environments these applications don't work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.

Viscosity and self-diffusion coefficients of dialkyl adipates: a correlation scheme with predictive capabilities

A correlation and predictive scheme for the viscosity and self-diffusivity of liquid dialkyl adipates is presented. The scheme is based on the kinetic theory for dense hard-sphere fluids, applied to the van der Waals model of a liquid to predict the transport properties. A "universal" curve for a dimensionless viscosity of dialkyl adipates was obtained using recently published experimental viscosity and density data of compressed liquid dimethyl (DMA), dipropyl (DPA), and dibutyl (DBA) adipates. The experimental data are described by the correlation scheme with a root-mean-square deviation of +/- 0.34 %. The parameters describing the temperature dependence of the characteristic volume, V-0, and the roughness parameter, R-eta, for each adipate are well correlated with one single molecular parameter. Recently published experimental self-diffusion coefficients of the same set of liquid dialkyl adipates at atmospheric pressure were correlated using the characteristic volumes obtained from the viscosity data. The roughness factors, R-D, are well correlated with the same single molecular parameter found for viscosity. The root-mean-square deviation of the data from the correlation is less than 1.07 %. Tests are presented in order to assess the capability of the correlation scheme to estimate the viscosity of compressed liquid diethyl adipate (DEA) in a range of temperatures and pressures by comparison with literature data and of its self-diffusivity at atmospheric pressure in a range of temperatures. It is noteworthy that no data for DEA were used to build the correlation scheme. The deviations encountered between predicted and experimental data for the viscosity and self-diffusivity do not exceed 2.0 % and 2.2 %, respectively, which are commensurate with the estimated experimental measurement uncertainty, in both cases.

Utilização do algoritmo Self-Organizing Map na caracterização de organizações públicas portuguesas.

Dissertação apresentada como requisito parcial para a obtenção do grau de mestre em Estatística e Gestão de Informação.