Abstract
In most challenging data analysis applications, data evolve over time and must be analyzed in near real time. Patterns and relations in such data often evolve over time, thus, models built for analyzing such data quickly become obsolete over time. In machine learning and data mining this phenomenon is referred to as concept drift. The objective is to deploy models that would diagnose themselves and adapt to changing data over time. This chapter provides an application oriented view towards concept drift research, with a focus on supervised learning tasks. First we overview and categorize application tasks for which the problem of concept drift is particularly relevant. Then we construct a reference framework for positioning application tasks within a spectrum of problems related to concept drift. Finally, we discuss some promising research directions from the application perspective, and present recommendations for application driven concept drift research and development.

Abstract
Rheumatoid arthritis (RA) is a chronic inflammatory disease that primarily affects the small joints of the hand. High frequency ultrasound imaging is used to measure the inflammatory activity in the joint capsule region of Metacarpophalangeal (MCP) joint. In our previous work, the problem of bones and joint capsule segmentation was addressed and in this work we aim to automatically identify the tendon using previously segmented structures. The extensor tendon is located above the metacarpal and phalange bone and the joint capsule. Tendon and bursal involvement are frequent and often clinically dominant in early RA. Ridge-like structures are enhanced and pre-processed to reduce speckle noise using a Log-Gabor filter. These regions are then simplified using medial axis transform and vertically connected lines are removed. Adjacent lines are connected using morphological operators and short lines are filtered by thresholding. Physiological information is used to create a distance map for all the lines using prior knowledge of the bone and capsule region location. Based on this distance map, the tendon is finally segmented and its shape refined by using active contours. The segmentation algorithm was tested on 90 images and experimental results demonstrate the accuracy of the proposed algorithm. The automatic segmentation was compared with an expert manual segmentation, and a mean error of 3.7 pixels and a standard deviation of 2 pixels were achieved, which are interested results for integration into future computer-assisted decision systems.

Abstract
The development of applications for high-performance embedded systems is a long and error-prone process because in addition to the required functionality, developers must consider various and often conflicting nonfunctional requirements such as performance and/or energy efficiency. The complexity of this process is further exacerbated by the multitude of target architectures and mapping tools. This article describes LARA, an aspect-oriented programming language that allows programmers to convey domain-specific knowledge and nonfunctional requirements to a toolchain composed of source-to-source transformers, compiler optimizers, and mapping/synthesis tools. LARA is sufficiently flexible to target different tools and host languages while also allowing the specification of compilation strategies to enable efficient generation of software code and hardware cores (using hardware description languages) for hybrid target architectures - a unique feature to the best of our knowledge not found in any other aspect-oriented programming language. A key feature of LARA is its ability to deal with different models of join points, actions, and attributes. In this article, we describe the LARA approach and evaluate its impact on code instrumentation and analysis and on selecting critical code sections to be migrated to hardware accelerators for two embedded applications from industry. Copyright (c) 2014 John Wiley & Sons, Ltd.

Abstract
Mobile phones are powerful tools to connect people. The streams of Call Detail Records (CDR’s) generating from these devices provide a powerful abstraction of social interactions between individuals, representing social structures. Call graphs can be deduced from these CDRs, where nodes represent subscribers and edges represent the phone calls made. These graphs may easily reach millions of nodes and billions of edges. Besides being large-scale and generated in real-time, the underlying social networks are inherently complex and, thus, difficult to analyze. Conventional data analysis performed by telecom operators is slow, done by request and implies heavy costs in data warehouses. In face of these challenges, real-time streaming analysis becomes an ever increasing need to mobile operators, since it enables them to quickly detect important network events and optimize business operations. Sampling, together with visualization techniques, are required for online exploratory data analysis and event detection in such networks. In this chapter, we report the burgeoning body of research in network sampling, visualization of streaming social networks, stream analysis and the solutions proposed so far. © 2016, Springer International Publishing Switzerland.

Abstract
Hybridisation is a systematic process along which the characteristic features of hybrid logic, both at the syntactic and the semantic levels, are developed on top of an arbitrary logic framed as an institution. It also captures the construction of first-order encodings of such hybridised institutions into theories in first-order logic. The method was originally developed to build suitable logics for the specification of reconfigurable software systems on top of whatever logic is used to describe local requirements of each system’s configuration. Hybridisation has, however, a broader scope, providing a fresh example of yet another development in combining and reusing logics driven by a problem from Computer Science. This paper offers an overview of this method, proposes some new extensions, namely the introduction of full quantification leading to the specification of dynamic modalities, and exemplifies its potential through a didactical application. It is discussed how hybridisation can be successfully used in a formal specification course in which students progress from equational to hybrid specifications in a uniform setting, integrating paradigms, combining data and behaviour, and dealing appropriately with systems evolution and reconfiguration.

Abstract
The first session of the 18th International Real Time Ada Workshop discussed two aspects of parallel programming in real-time systems, the use of executors in parallel systems, and syntax to guide the reduction of parallel computations to return a correct single answer. This report captures the discussions held and the decisions and recommendations of the workshop on these topics.