Abstract

Abstract
Over the last decades the role of information systems (IS) has evolved and has become truly important within organizations. Despite this evidence, not all organizations have the internal resources and know-how required to develop it. The outsourcing of IS services have been presented as an alternative and strategic option in the management of this function in many organizations and various sectors of activity. Developing a better understanding of the main IS services outsourcing practices in the banking sector, given their particularities (eg with regard to confidentiality requirements and secrecy), is the central objective of this work. To this end, a survey was conducted based on a questionnaire in order to characterize, among other things, the services subject to outsourcing, the main motivations, risks, barriers and impacts associated with the outsourcing as well as contracting aspects, customer-supplier relationship and satisfaction. The main results are presented in this paper.

Abstract
We present Symbiosis: a concurrency debugging technique based on novel differential schedule projections (DSPs). A DSP shows the small set of memory operations and data-flows responsible for a failure, as well as a reordering of those elements that avoids the failure. To build a DSP, Symbiosis first generates a full, failing, multithreaded schedule via thread path profiling and symbolic constraint solving. Symbiosis selectively reorders events in the failing schedule to produce a non-failing, alternate schedule. A DSP reports the ordering and data-flow differences between the failing and non-failing schedules. Our evaluation on buggy real-world software and benchmarks shows that, in practical time, Symbiosis generates DSPs that both isolate the small fraction of event orders and data-flows responsible for the failure, and show which event reorderings prevent failing. In our experiments, DSPs contain 81% fewer events and 96% fewer data-flows than the full failure-inducing schedules. Moreover, by allowing developers to focus on only a few events, DSPs reduce the amount of time required to find a valid fix.

Abstract
Stress can negatively impact one's health and well-being, however, despite the recent evolution in stress assessment research methodologies, there is still little agreement about stress conceptualization and assessment. In an attempt to summarize and reflect on this evolution, this paper aims to systematically review research evidence of ecological approaches on psychophysiological stress assessment. Thus, a literature search of electronic databases was conducted spanning 22 years (1990-2012) and 55 studies were reviewed. Studies were considered for inclusion if they contemplated both psychological and physiological measures of stress under ecological settings. This review focuses on five themes: methodology terminology, research population, study design, measurement, and technology. Findings support the need to use a common methodology terminology in order to increase scientific rigor. Additionally, there seems to be an increasing tendency for the use of these methods by multidisciplinary teams among both clinical and nonclinical populations aiming to understand the relationship between stress and disease. Most of the studies reviewed contemplated a time-based protocol and different conceptualizations of stress were found, resulting in the use of different subjective measures. Findings reinforce the importance of combining subjective and objective measures while also controlling for possible time-or situation-dependent confounders'. Advances in technology were evident and different assessment techniques were found. The benefits and challenges of ecological protocols to assess stress are discussed and recommendations for future research are provided, aiming to overcome previous limitations and advance scientific knowledge in the area.

Abstract
Solving complex optimization problems with genetic algorithms (GAs) with custom computing architectures is a way to improve the execution time of this metaheuristic, which is known to consume considerable amounts of time to converge to final solutions. In this work, we present a scalable computing array architecture to accelerate the execution of cellular GAs (cGAs), a variant of genetic algorithms which can conveniently exploit the coarse- grain parallelism afforded by custom parallel processing. The proposed architecture targets Xilinx FPGAs and is used as an auxiliary processor of an embedded CPU (MicroBlaze). To handle different optimization problems, a high- level synthesis (HLS) design flow is proposed where the problem- dependent operations are specified in C++ and synthesised to custom hardware, thus requiring a minimum knowledge of digital design for FPGAs. The minimum energy broadcast (MEB) problem in wireless ad hoc networks is used as a case study. An existing software implementation of a GA to solve this problem is ported to the proposed computing array to demonstrate its effectiveness and the HLS- based design flow. Implementation results in a Virtex- 6 FPGA show significant speedups, while finding solutions with improved quality.

Abstract
Sectorization means dividing a whole into parts (sectors), a procedure that occurs in many contexts and applications, usually to achieve some goal or to facilitate an activity. The objective may be a better organization or simplification of a large problem into smaller sub-problems. Examples of applications are political districting and sales territory division. When designing/comparing sectors some characteristics such as contiguity, equilibrium and compactness are usually considered. This paper presents and describes new generic measures and proposes a new measure, desirability, connected with the idea of preference. © 2015, Springer International Publishing Switzerland.