Abstract

Abstract
With the mushrooming of distributed renewable generation, energy storage unit (ESU) is becoming increasingly important in residential energy systems. This letter proposes a fractional programming model to determine the optimal power, and energy capacities of residential ESUs. The objective function maximizes the ratio between the reduced electricity tariff, and the investment cost of ESU, ensuring the minimal payback time. A decomposition algorithm is developed to solve the fractional program based on convex optimization; the subproblem is a dual convex quadratic program which provides cutting planes, and the master problem comes down to a linear program after variable transformations. Compared to the widely used cost-minimum method, the proposed model is cost-efficient: it enjoys a higher rate of return which is usually welcomed by small consumers.

Abstract
Narrative Extraction from text is a complex task that starts by identifying a set of narrative elements (actors, events, times), and the semantic links between them (temporal, referential, semantic roles). The outcome is a structure or set of structures which can then be represented graphically, thus opening room for further and alternative exploration of the plot. Such visualization can also be useful during the on-going annotation process. Manual annotation of narratives can be a complex effort and the possibility offered by the Brat annotation tool of annotating directly on the text does not seem sufficiently helpful. In this paper, we propose Brat2Viz, a tool and a pipeline that displays visualization of narrative information annotated in Brat. Brat2Viz reads the annotation file of Brat, produces an intermediate representation in the declarative language DRS (Discourse Representation Structure), and from this obtains the visualization. Currently, we make available two visualization schemes: MSC (Message Sequence Chart) and Knowledge Graphs. The modularity of the pipeline enables the future extension to new annotation sources, different annotation schemes, and alternative visualizations or representations. We illustrate the pipeline using examples from an European Portuguese news corpus.

Abstract
The use of Long-Period Fiber Gratings (LPFGs) as sensors has been thoroughly researched, given the multitude of parameters these structures can monitor by themselves (such as temperature, strain, curvature) and the potential for combination with other materials that allow for monitoring of parameters such as humidity, pH and chemical concentration, at a low price and with easy fabrication processes available. This interest has increased the need for the development of interrogation systems for these sensors, particularly in the C-band spectral region. Given the cost and physical limitations (such as size and weight) of traditional solutions like Optical Spectrum Analyzers (OSA), the development of low-cost approaches for LPFG spectral analysis became an important topic that needed further development. The development of a simple curve fitting routine for LPFG spectra is reported in this article, along with a framework for automatic detection of certain physical phenomena such as corrosion and the presence of chemical species, among others.

Abstract
Phasor measurement unit (PMU) provides beneficial information for dynamic power system stability, analysis, and control. One main application of such useful information is data-driven analysis and control. This article presents an approach for optimal signal selection and controller structure determination in PMU-based power system stabilizer (PSS) design. An algorithm is suggested for selecting the optimal input and output signals for PSS, in which a combination of system clustering, modal analysis, and principal component analysis techniques is used. The solution for the optimal PSS input-output selection is determined to increase the observability and damping of the power system. The approach can efficiently reduce the number of input-output signals, while the overall performance is not deteriorated. Then, a linear matrix inequality-based technique is elaborated to design the PMU-based PSS parameters. The stabilizer design approach is formulated as a convex optimization problem and the appropriate stabilizer for pole allocation of the closed-loop model is designed. This method is simulated on two sample power systems. Also, to compare the results with the previous methods, the system is simulated and the results of two previously developed algorithms are compared with the proposed approach. The results show the benefit of the suggested method in reducing the required signals, which decreases the number of required PMUs, while the system damping is not affected.

Abstract
After the Cold War, the defense industries found themselves at a crossroads. However, it seems that they are gaining new momentum, as new technologies such as robotics and artificial intelligence are enabling the development of autonomous, highly innovative and disruptive intelligent systems. Despite this new impetus, there are still doubts about where to invest limited financial resources to boost high-tech defense industries. In order to shed some light on the topic, we decided to conduct a systematic literature review by using the PRISMA protocol and content analysis. The results indicate that autonomous intelligent systems are being developed by the defense industry and categorized into three different modes-fully autonomous operations, partially autonomous operations, and smart autonomous decision-making. In addition, it is also important to note that, at a strategic level of war, there is limited room for automation given the need for human intervention. However, at the tactical level of war, there is a high probability of growth in industrial defense, since, at this level, structured decisions and complex analytical-cognitive tasks are carried out. In the light of carrying out those decisions and tasks, robotics and artificial intelligence can make a contribution far superior to that of human beings.