EMOTAG: AN APPROACH TO AUTOMATED MARKUP OF EMOTIONS IN TEXTS

This paper presents an approach to the automated markup of texts with emotional labels. The approach considers two possible representations of emotions in parallel: emotional categories (emotional tags used to refer to emotions) and emotional dimensions (measures that try to model the essential aspects of emotions numerically). For each representation, a corpus of example texts previously annotated by human evaluators is mined for an initial assignment of emotional features to words. This results in a list of emotional words (LEW) which becomes a useful resource for later automated markup. The algorithm proposed for the automated markup of text closely mirrors the steps taken during feature extraction, employing a combination of the LEW resource and the ANEW word list for the actual assignment of emotional features, and WordNet for knowledge‐based expansion of words not occurring in either and an ontology of emotional categories. The algorithm for automated markup is tested and the results are discussed with respect to three main issues: the relative adequacy of each of the representations used, correctness and coverage of the proposed algorithm, and additional techniques and solutions that may be employed to improve the results. The average percentage of success obtained by our approach when it marks up with emotional dimensions is around 80% and when it marks up with emotional categories is around 50%. The main contribution of the approach presented in this paper is that it allows dimensions and categories at different levels of abstraction to operate simultaneously during markup.     

Operation mode control of a hybrid power system based on fuel cell/battery/ultracapacitor for an electric tramway

This paper focuses on describing a control strategy for a real tramway, in Zaragoza (Spain), whose current propulsion system is to be replaced by a hybrid system based on fuel cell (FC) as primary energy source and batteries and ultracapacitors (UCs) as secondary energy sources. Due to its slow dynamic response, the FC needs other energy sources support during the starts and accelerations, which are used as energy storage devices in order to harness the regenerative energy generated during brakings and decelerations. The proposed energy management system is based on an operation mode control, which generates the FC reference power, and cascade controls, which define the battery and UC reference powers in order to achieve a proper control of the DC bus voltage and states of charge (SOC) of battery and UC. The simulations, performed by using the real drive cycle of the tramway, show that the proposed hybrid system and energy management system are suitable for its application in this tramway.     

The conceptual framing,design and evaluation of device ecologies for collaborative activities

A variety of computing technologies, in addition to the personal computer, are now commonly used in many settings. As networking infrastructures mature, it is increasingly feasible and affordable to consider closer integration and use of these heterogeneous devices in tandem. However, little is known about how best to design or evaluate such ‘device ecologies’; in particular, how best to combine devices to achieve a desired type of collaborative user experience. A central concern is how users switch their attention between devices, to utilize the various elements to best effect. We describe here the development of an ecology of devices for groups of students to use when engaged in collaborative inquiry-learning activities. This included a multi-touch tabletop, laptops, projections, video streams and telephone. In situ studies of students and tutors using it in three different settings showed how individuals and groups switched their foci between the multiple devices. We present our findings, using a novel method for analysing users’ transitions between foci, identifying patterns and emergent characteristics. We then discuss the importance of designing for transitions that enable groups to appropriately utilise an ecology of devices, using the concepts of seams, bridges, niches and focal character.     

A bargaining-specific architecture for supporting automated service agreement negotiation systems

The provision of services is often regulated by means of agreements that must be negotiated beforehand. Automating such negotiations is appealing insofar as it overcomes one of the most often cited shortcomings of human negotiation: slowness. Our analysis of the requirements of automated negotiation systems in open environments suggests that some of them cannot be tackled in a protocol-independent manner, which motivates the need for a protocol-specific architecture. However, current state-of-the-art bargaining architectures fail to address all of these requirements together. Our key contribution is a bargaining architecture that addresses all of the requirements we have identified. The definition of the architecture includes a logical view that identifies the key architectural elements and their interactions, a process view that identifies how the architectural elements can be grouped together into processes, a development view that includes a software framework that provides a reference implementation developers can use to build their own negotiation systems, and a scenarios view by means of which the architecture is illustrated and validated.     

Extracting multilayered Communities of Interest from semantic user profiles: Application to group modeling and hybrid recommendations

A Community of Interest is a specific type of Community of Practice. It is formed by a group of individuals who share a common interest or passion. These people exchange ideas and thoughts about the given passion. However, they are often not aware of their membership to the community, and they may know or care little about each other outside of this clique. This paper describes a proposal to automatically identify Communities of Interest from the tastes and preferences expressed by users in personal ontology-based profiles. The proposed strategy clusters those semantic profile components shared by the users, and according to the clusters found, several layers of interest networks are built. The social relations of these networks might then be used for different purposes. Specifically, we outline here how they can be used to model group profiles and make semantic content-based collaborative recommendations.     

Gridchain: an investigation of privacy for the future local distribution grid

As part of building the smart grid, there is a massive deployment of so-called smart meters that aggregate information and communicate with the back-end office, apart from measuring properties of the local network. Detailed measurements and communication of, e.g., consumption allows for remote billing, but also in finding problems in the distribution of power and overall to provide data to be used to plan future upgrades of the network. From a security perspective, a massive deployment of such Internet of Things (IoT) components increases the risk that some may be compromised or that collected data are used for privacy-sensitive inference of the consumption of households. In this paper, we investigate the privacy concerns regarding detailed readings of smart meters for billing purposes. We present Gridchain, a solution where households can opt-in to hide their consumption patterns and thus make Non-Intrusive Load Monitoring (NILM) more challenging. Households form groups where they can trade real consumption among themselves to achieve reported consumption that would be resistant to NILM. Gridchain is built on a publish/subscribe model and uses a permissioned blockchain to record any trades, meaning that dishonest households can be discovered and punished if they steal from other households in the group or the electricity company in the end. We implement and release a proof of concept of Gridchain and use public datasets to allow reproducibility. Our results show that even if an attacker has access to the reported electricity consumption of any member of a Gridchain group, this reported consumption is significantly far from the actual consumption to allow for a detailed fingerprint of the household activities.

     

Toward minimum size self-assembled counters

DNA self-assembly is a promising paradigm for nanotechnology. In this paper we study the problem of finding tile systems of minimum size that assemble a given shape in the Tile Assembly Model, defined by Rothemund and Winfree (Proceedings of the thirty-second annual ACM symposium on theory of computing, 2000). We present a tile system that assembles an rectangle in asymptotically optimal time. This tile system has only 7 tiles. Earlier constructions need at least 8 tiles (Chen et al. Proceedings of symposium on discrete algorithms, 2004). We managed to reduce the number of tiles without increasing the assembly time. The new tile system works at temperature 3. The new construction was found by the combination of exhaustive computerized search of the design space and manual adjustment of the search output.     

An experimental study on the applicability of SYN cookies to networked constrained devices

The Internet protocol suite is increasingly used on devices with constrained resources that operate as both clients and servers within the Internet of Things paradigm. However, these devices usually apply few—if any—security measures. Therefore, they are vulnerable to network attacks, particularly to denial of service attacks. The well‐known SYN flood attack works by filling up the connection queue with fake SYN requests. When the queue is full, new connections cannot be opened until some entries are removed after a time‐out. Class 2 constrained devices—according to the RFC 7228—are highly vulnerable to this attack because of their limited available memory, even in low‐rate attacks. This paper analyses and compares in a class 2 constrained device the performance of 2 commonly used defence mechanisms (ie, recycle half‐open connections and SYN cookies) during a low‐rate SYN flood. We first review 2 SYN cookies implementations (ie, Linux and FreeBSD) and compare them with a hybrid approach in a class 2 device. Finally, experimental results prove that the proposed SYN cookies implementation is more effective than recycling the oldest half‐open connections.     

Distributed decision support system for airport ground handling management using WSN and MAS

The economic situation in the air transportation industry claims for new business models supported by accurate management processes, which need constant feedback of the real status of the environment. The objective of this work is to achieve an updated/real decision support systems (DSS) to allocate resources in an airport even when disturbances occur by combining artificial intelligent techniques with visibility technologies. This work proposes the combined use of Multi-agent systems (MAS) along with Wireless Sensor Networks (WSN) to provide the required information on the status of the resources and the environment. The MAS is based on a double layer of decision-taking levels and on a Markov reward function whereas the WSN is based on a Zigbee network of Radio Frequency Identification (RFID) readers with active tags as end nodes, which are carried by the physical resources. The proposed distributed DSS has been tested at Ciudad Real Central Airport in Spain.     

Model-based energy-aware data movement optimization in the storage I/O stack

The increasing data demands of applications from various domains and the decreasing relative power cost of CPU computation have gradually exposed data movement cost as the prominent factor of energy consumption in computing systems. The traditional organization of the computer system software into a layered stack, while providing a straightforward modularity, poses a significant challenge for the global optimization of data movement in particular and, thus, the energy efficiency in general. Optimizing the energy efficiency of data movement in large-scale systems is a difficult tasks because it depends on a complex interplay of various factors at different system layers. In this work, we address the challenge of optimizing the data movement of the storage I/O stack in a holistic manner. Our approach consists of a model-based system driver that obtains the current I/O power regime and adapts the CPU frequency level according to this information. On the one hand, for simplifying the understanding of the relation between data movement and energy efficiency, this paper proposes novel energy prediction models for data movement based on series of runtime metrics from several I/O stack layers. We provide an in-depth study of the energy consumption in the data path, including the identification and analysis of power and performance regimes that synthesize the energy consumption patterns in a cross-layer approach. On the other hand, we propose and prototype a kernel driver that exploits data movement awareness for improving the current CPU-centric energy management.