Mechanisms for the generation and regulation of sequential behaviour

A critical aspect of much human behaviour is the generation and regulation of sequential activities. Such behaviour is seen in both naturalistic settings such as routine action and language production and laboratory tasks such as serial recall and many reaction time experiments. There are a variety of computational mechanisms that may support the generation and regulation of sequential behaviours, ranging from those underlying Turing machines to those employed by recurrent connectionist networks. This paper surveys a range of such mechanisms, together with a range of empirical phenomena related to human sequential behaviour. It is argued that the empirical phenomena pose difficulties for most sequencing mechanisms, but that converging evidence from behavioural flexibility, error data arising from when the system is stressed or when it is damaged following brain injury, and between-trial effects in reaction time tasks, point to a hybrid symbolic activation-based mechanism for the generation and regulation of sequential behaviour. Some implications of this view for the nature of mental computation are highlighted

Towards a test generation approach for compositional real-time systems.

We can find many examples of Real-time Systems (RTS) in critical applications such as patient monitoring, air traffic control and others. A failure in this kind of system can be catastrophic. For example, it can harm human lives or increase project budgets. Hence, the testing of real-time systems must be accurate. Models are used to perform this task, since they contain information about how the system behaves and when actions may happen. Due to the complexity of the available systems, most RTS are composed of subsystems that interact as part of a bigger system. These subsystems are combined through operators to model their specification behavior. However, works on the testing of compositional models for RTS are practically nonexistent. Among the available approaches to perform testing for non-compositional RTS models, the tioco conformance testing theory focuses on generating test cases based on implementation and specification models. Moreover, a conformance relation defines whether success in testing means conformance between an implementation and a specification. To express specifications and to represent implementations under test, we use Timed Input Output Symbolic Transitions Systems (TIOSTS). These models store symbolic data and clock variables, avoiding the state space and region explosion problems. Regarding the testing of compositional models, some questions may arise: If two subsystem implementations are tioco conformant to their specifications, is it correct to assume that the composition of the implementations is also tioco conformant to the composition of their specifications? In this case, how can operators be defined to work with TIOSTS and tioco? To answer these questions, this thesis proposes the sequential, interruption and parallel operators for the TIOSTS model. For each operator, we study how the tioco conformance relation behaves with respect to subsystems and the composed system. We present results towards properties of compositional operators when the subsystems are composed, as well as implementing them. Besides, we show three examples where each operator can be used and illustrate the applicability of our approach in two exploratory studies. The first models components of a aircraft specification and the second presents application level interruptions in an Android system.We can nd many examples of Real-time Systems (RTS) in critical applications such as patient monitoring, air tra c control and others. A failure in this kind of system can be catastrophic. For example, it can harm human lives or increase project budgets. Hence, the testing of real-time systems must be accurate. Models are used to perform this task, since they contain information about how the system behaves and when actions may happen. Due to the complexity of the available systems, most RTS are composed of subsystems that interact as part of a bigger system. These subsystems are combined through operators to model their speci cation behavior. However, works on the testing of compositional models for RTS are practically nonexistent. Among the available approaches to perform testing for non-compositional RTS models, the tioco conformance testing theory focuses on generating test cases based on implementation and speci cation models. Moreover, a conformance relation de nes whether success in testing means conformance between an implementation and a speci cation. To express speci cations and to represent implementations under test, we use Timed Input Output Symbolic Transitions Systems (TIOSTS). These models store symbolic data and clock variables, avoiding the state space and region explosion problems. Regarding the testing of compositional models, some questions may arise: If two subsystem implementations are tioco conformant to their speci cations, is it correct to assume that the composition of the implementations is also tioco conformant to the composition of their speci cations? In this case, how can operators be de ned to work with TIOSTS and tioco? To answer these questions, this thesis proposes the sequential, interruption and parallel operators for the TIOSTS model. For each operator, we study how the tioco conformance relation behaves with respect to subsystems and the composed system. We present results towards properties of compositional operators when the subsystems are composed, as well as implementing them. Besides, we show three examples where each operator can be used and illustrate the applicability of our approach in two exploratory studies. The rst models components of a aircraft speci cation and the second presents application level interruptions in an Android system

Adults are more efficient in creating and transmitting novel signalling systems than children

Iterated language learning experiments have shown that meaningful and structured signalling systems emerge when there is pressure for signals to be both learnable and expressive. Yet such experiments have mainly been conducted with adults using language-like signals. Here we explore whether structured signalling systems can also emerge when signalling domains are unfamiliar and when the learners are children with their well-attested cognitive and pragmatic limitations. In Experiment 1, we compared iterated learning of binary auditory sequences denoting small sets of meanings in chains of adults and 5-7-year old children. Signalling systems became more learnable even though iconicity and structure did not emerge despite applying a homonymy filter designed to keep the systems expressive. When the same types of signals were used in referential communication by adult and child dyads in Experiment 2, only the adults, but not the children, were able to negotiate shared iconic and structured signals. Referential communication using their native language by 4-5-year old children in Experiment 3 showed that only interaction with adults, but not with peers resulted in informative expressions. These findings suggest that emergence and transmission of communication systems is unlikely to be driven by children, and point to the importance of cognitive maturity and pragmatic expertise of learners as well as feedback-based scaffolding of communicative effectiveness by experts during language evolution

Semiformal Verification of Embedded Software in Medical Devices Considering Stringent Hardware Constraints

In recent days, the complexity of software has increased significantly in embedded products in such a way that the verification of Embedded Software (ESW) now plays an important role to ensure the product's quality. Embedded systems engineers usually face the problems of verifying properties that have to meet the application's deadline, access the memory region, handle concurrency, and control the hardware registers. This work proposes a semiformal verification approach that combines dynamic and static verification to stress and cover exhaustively the state space of the system. We perform a case study on embedded software used in the medical devices domain. We conclude that the proposed approach improves the coverage and reduces substantially the verification time

MU_PSYC : Algorithmic music composition with a music-psychology enriched genetic algorithm

Recent advancement of artificial intelligence (AI) techniques have impacted the field of algorithmic music composition, and that has been evidenced by live concert performances wherein the audience reportedly often could not tell whether music was composed by machine or by human. Among the various AI techniques, genetic algorithms dominate the field due to their suitability for both creativity and optimization. Many attempts have been made to incorporate rules from traditional music theory to design and automate genetic algorithms. Another popular approach is to incorporate statistical or mathematical measures of fitness. However, these rules and measures are rarely tested for their validity. This thesis is aimed at addressing the above limitation and hence paving the way to advance the field towards composing human-quality music. The basic idea is to look beyond this constrained set of traditional music rules and statistical/mathematical methods towards a more concrete foundation. We look to a field at the intersection of musicology and psychology, referred to as music-psychology. To demonstrate our proposed approach, we implemented a genetic algorithm exclusively using rules found in music-psychology. An online survey was conducted testing the quality of our algorithm’s output compositions. Moreover, algorithm performance was analyzed by experimental study. The initial results are encouraging and warrant further research. The societal implications of our work and other research in the field are also discussed

Interaction-aware analysis and optimization of real-time application and operating system

Mechanical and electronic automation was a key component of the technological advances in the last two hundred years. With the use of special-purpose machines, manual labor was replaced by mechanical motion, leaving workers with the operation of these machines, before also this task was conquered by embedded control systems. With the advances of general-purpose computing, the development of these control systems shifted more and more from a problem-specific one to a one-size-fits-all mentality as the trade-off between per-instance overheads and development costs was in favor of flexible and reusable implementations. However, with a scaling factor of thousands, if not millions, of deployed devices, overheads and inefficiencies accumulate; calling for a higher degree of specialization. For the area real-time operating systems (RTOSs), which form the base layer for many of these computerized control systems, we deploy way more flexibility than what is actually required for the applications that run on top of it. Since only the solution, but not the problem, became less specific to the control problem at hand, we have the chance to cut away inefficiencies, improve on system-analyses results, and optimize the resource consumption. However, such a tailoring will only be favorable if it can be performed without much developer interaction and in an automated fashion. Here, real-time systems are a good starting point, since we already have to have a large degree of static knowledge in order to guarantee their timeliness. Until now, this static nature is not exploited to its full extent and optimization potentials are left unused. The requirements of a system, with regard to the RTOS, manifest in the interactions between the application and the kernel. Threads request resources from the RTOS, which in return determines and enforces a scheduling order that will ensure the timely completion of all necessary computations. Since the RTOS runs only in the exception, its reaction to requests from the application (or from the environment) is its defining feature. In this thesis, I will grasp these interactions, and thereby the required RTOS semantic, in a control-flow-sensitive fashion. Extracted automatically, this knowledge about the reciprocal influence allows me to fit the implementation of a system closer to its actual requirements. The result is a system that is not only in its usage a special-purpose system, but also in its implementation and in its provided guarantees. In the development of my approach, it became clear that the focus on these interactions is not only highly fruitful for the optimization of a system, but also for its end-to-end analysis. Therefore, this thesis does not only provide methods to reduce the kernel-execution overhead and a system's memory consumption, but it also includes methods to calculate tighter response-time bounds and to give guarantees about the correct behavior of the kernel. All these contributions are enabled by my proposed interaction-aware methodology that takes the whole system, RTOS and application, into account. With this thesis, I show that a control-flow-sensitive whole-system view on the interactions is feasible and highly rewarding. With this approach, we can overcome many inefficiencies that arise from analyses that have an isolating focus on individual system components. Furthermore, the interaction-aware methods keep close to the actual implementation, and therefore are able to consider the behavioral patterns of the finally deployed real-time computing system

Towards a Better Comprehension of Adaptation to Information and Communication Technologies: A Multi-level Approach

Despite the variety of literature on ‘adaptation to technology’, the literature still witnesses a gap concerning the concept of adaptation especially about its multi-level nature. Recognizing the multilevel nature of IS adaptation, we rise the challenge of conducting an alternate template analysis of three cases of adaptation to IS in order to provide complementary explanations about the phenomenon. In order to expand the comprehension of the ‘adaptation’ concept, a multi-study dissertation model is adopted. The objective is to examine the adaptation concept on three different levels: the individual, the group level, and the organizational level. This thesis aims at 1) exploring the shaping of individual adaptive actions that knowledge workers engage towards technostress with a focus on the factors that influence their adaptation process; 2) examining the adaptive performance of a group facing an newlyimplemented technology based on the adaptive structuration theory (DeSanctis and Poole 1994) under which were puzzled the concepts of affordances (Leonardi 2011, Leonardi, Huysman et al. 2013) and the structure of usage (Burton-Jones and Straub Jr 2006, Burton-Jones and Gallivan 2007); 3) examining, through an organizational learning lens (Argyris and Schon 1978), the case of an organizational adaptation to environmental technological changes examined within a managerial cognition conceptual framework (Orlikowski and Gash 1994); (Bijker 1987, Bijker 1995). To answer the different research questions, the three studies adopt a qualitative approach falling within a critical realist perspective