Abstract
Intelligent transportation systems based on automated data collection frameworks are widely used by the major transit companies around the globe. This paper describes the current state of the art on improving both planning and control on public road transportation companies using automatic vehicle location (AVL) data. By surveying this topic, the expectation is to help develop a better understanding of the nature, approaches, challenges, and opportunities with regard to these problems. This paper starts by presenting a brief review on improving the network definition based on historical location-based data. Second, it presents a comprehensive review on AVL-based evaluation techniques of the schedule plan (SP) reliability, discussing the existing metrics. Then, the different dimensions on improving the SP reliability are presented in detail, as well as the works addressing such problem. Finally, the automatic control strategies are also revised, along with the research employed over the location-based data. A comprehensive discussion on the techniques employed is provided to encourage those who are starting research on this topic. It is important to highlight that there are still gaps in AVL-based literature, such as the following: 1) long-term travel time prediction; 2) finding optimal slack time; or 3) choosing the best control strategy to apply in each situation in the event of schedule instability. Hence, this paper includes introductory model formulations, reference surveys, formal definitions, and an overview of a promising area, which is of interest to any researcher, regardless of the level of expertise.

Abstract
Large scale social networks streaming and visualization has been a hot topic in recent research. Researchers strive to achieve efficient streaming methods and to be able to gather knowledge from the results. Moreover treating the data as a continuous real time flow is a demand for immediate response to events in daily life. Our contribution is to treat the data as a continuous stream and represent it by streaming the egocentric networks (Ego-Networks) for particular nodes. We propose a non-standard node forgetting factor in the representation of the network data stream. Thus, this representation is sensible to recent events in users networks and less sensible for the past node events. The aim of these techniques is the visualization of large scale Ego-Networks from telecommunications social networks with power law distributions.

Abstract
This paper proposes an offering strategy for a wind power producer (WPP) that participates in both day-ahead (DA) and balancing oligopoly markets as a price maker. Penetration of demand response (DR) resources into smart grids is modeled by intraday demand response exchange (IDRX) architecture. A bilevel optimization framework is proposed based on multiagent system and incomplete information game theory. Modeling the WPPs in high penetration of wind power as price makers can reflect the capability of this market player to directly affect the market prices. Simulation results indicate that the price-taker model ofWPP is not accurate for WPPs that have significant market shares. By comparing the results obtained from modeling the WPPs as price makers with the ones as price takers, it can be concluded that WPPs have the market power not only to increase the prices of both DA and balancing markets, but also to reduce the amount of DR through IDRX market mechanism.

Abstract
The mainstream of embedded software development as of today is dominated by C programming. To aid the development, hardware abstractions, libraries, kernels and lightweight operating systems are commonplace. Such kernels and operating systems typically impose a thread based abstraction to concurrency. However, in general thread based programming is hard, plagued by race conditions and dead-locks. For this paper we take an alternative outset in terms of a language abstraction, RTFM-core, where the system is modelled directly in terms of tasks and resources. In compliance to the Stack Resource Policy (SRP) model, the language enforces (well-formed) LIFO nesting of claimed resources, thus SRP based analysis and scheduling can be readily applied. For the execution onto bare-metal single core architectures, the rtfm-core compiler performs SRP analysis on the model and render an executable that is deadlock free and (through RTFM-kernel primitives) exploits the underlying interrupt hardware for efficient scheduling. The RTFM-core language embeds C-code and links to C-object files and libraries, and is thus applicable to the mainstream of embedded development. However, while the language enforces well-formed resource management, control flow in the embedded C-code may violate the LIFO nesting requirement. In this paper we address this issue by lifting a subset of C into the RTFM-core language allowing arbitrary control flow at the model level. In this way well-formed LIFO nesting can be enforced, and models ensured to be correct by construction. We demonstrate the feasibility by means of a prototype implementation in the rtfm-core compiler. Additionally, we develop a set of running examples and show in detail how control flow is handled at compile time and during run-time execution. © 2015 IEEE.

Abstract
TV White Spaces (TVWS) technology allows wireless devices to opportunistically use locally-available TV channels enabled by a geolocation database. The UK regulator Ofcom has initiated a pilot of TVWS technology in the UK. This paper concerns a large-scale series of trials under that pilot. The purposes are to test aspects of white space technology, including the white space device and geolocation database interactions, the validity of the channel availability/powers calculations by the database and associated interference effects on primary services, and the performances of the white space devices, among others. An additional key purpose is to perform research investigations such as on aggregation of TVWS resources with conventional resources and also aggregation solely within TVWS, secondary coexistence issues and means to mitigate such issues, and primary coexistence issues under challenging deployment geometries, among others. This paper provides an update on the trials, giving an overview of their objectives and characteristics, some aspects that have been covered, and some early results and observations.

Abstract
This paper presents analog building blocks that find potential applications in display panels. A buffer (source-follower), subtractor, adder, and high-gain amplifier, employing only n-type enhancement amorphous gallium-indium-zinc-oxide thin-film transistors (a-GIZO TFTs), were designed, simulated, fabricated, and characterized. Circuit simulations were carried out using a neural model developed in-house from the measured characteristics of the transistors. The adder-subtractor circuit presents a power consumption of 0.26 mW, and the amplifier presents a gain of 34 dB and a power consumption of 0.576 mW, with a load of 10 M Omega//16 pF. To the authors' knowledge, this is the highest gain reported so far for a single-stage amplifier with a-GIZO TFT technology.