Adaptive languages and a new programming style

A programming style can be seen as a particular model of shaping thought or a special way of codifying language to solve a problem. Adaptive languages have the basic feature of allowing the expression of programs which self-modifying through adaptive actions at runtime. The conception of such languages calls for a new programming style, since the application of adaptive technology in the field of programming languages suggests a new way of thinking. With the adaptive style, programming language codes can be structured in such a way that the codified program therein modifies or adapts itself towards the needs of the problem. The adaptive programming style may be a feasible alternate way to obtain self-modifying consistent codes, which allow its use in modern applications for self-modifying code.

Using adaptive automata in a multi-paradigm programming environment

In this paper the architecture of an experimental multiparadigmatic programming environment is sketched, showing how its parts combine together with application modules in order to perform the integration of program modules written in different programming languages and paradigms. Adaptive automata are special self-modifying formal state machines used as a design and implementation tool in the representation of complex systems. Adaptive automata have been proven to have the same formal power as Turing Machines. Therefore, at least in theory, arbitrarily complex systems may be modeled with adaptive automata. The present work briefly introduces such formal tool and presents case studies showing how to use them in two very different situations: the first one, in the name management module of a multi-paradigmatic and multi-language programming environment, and the second one, in an application program implementing an adaptive automaton that accepts a context-sensitive language.

Postural control as a function of self- and object-motion perception

The goals of this study were to examine the visual information influence on body sway as a function of self- and object-motion perception and visual information quality. Participants that were aware (object-motion) and unaware (self-motion) of the movement of a moving room were asked to stand upright at five different distances from its frontal wall. The visual information effect on body sway decreased when participants were aware about the sensory manipulation. Moreover, while the visual influence on body sway decreased as the distance increased in the self-motion perception, no effects were observed in the object-motion mode. The overall results indicate that postural control system functioning can be altered by prior knowledge, and adaptation due to changes in sensory quality seem to occur in the self- but not in the object-motion perception mode. (C) 2004 Elsevier B.V.. All rights reserved.

Self-organising coordination systems

Many research fields are pushing the engineering of large-scale, mobile, and open systems towards the adoption of techniques inspired by self-organisation: pervasive computing, but also distributed artificial intelligence, multi-agent systems, social networks, peer-topeer and grid architectures exploit adaptive techniques to make global system properties emerge in spite of the unpredictability of interactions and behaviour. Such a trend is visible also in coordination models and languages, whenever a coordination infrastructure needs to cope with managing interactions in highly dynamic and unpredictable environments. As a consequence, self-organisation can be regarded as a feasible metaphor to define a radically new conceptual coordination framework. The resulting framework defines a novel coordination paradigm, called self-organising coordination, based on the idea of spreading coordination media over the network, and charge them with services to manage interactions based on local criteria, resulting in the emergence of desired and fruitful global coordination properties of the system. Features like topology, locality, time-reactiveness, and stochastic behaviour play a key role in both the definition of such a conceptual framework and the consequent development of self-organising coordination services. According to this framework, the thesis presents several self-organising coordination techniques developed during the PhD course, mainly concerning data distribution in tuplespace-based coordination systems. Some of these techniques have been also implemented in ReSpecT, a coordination language for tuple spaces, based on logic tuples and reactions to events occurring in a tuple space. In addition, the key role played by simulation and formal verification has been investigated, leading to analysing how automatic verification techniques like probabilistic model checking can be exploited in order to formally prove the emergence of desired behaviours when dealing with coordination approaches based on self-organisation. To this end, a concrete case study is presented and discussed.

Brain-Computer Interfaces for augmented communication: Asynchronous and adaptive algorithms and evaluation with end users

This thesis aimed at addressing some of the issues that, at the state of the art, avoid the P300-based brain computer interface (BCI) systems to move from research laboratories to end users’ home. An innovative asynchronous classifier has been defined and validated. It relies on the introduction of a set of thresholds in the classifier, and such thresholds have been assessed considering the distributions of score values relating to target, non-target stimuli and epochs of voluntary no-control. With the asynchronous classifier, a P300-based BCI system can adapt its speed to the current state of the user and can automatically suspend the control when the user diverts his attention from the stimulation interface. Since EEG signals are non-stationary and show inherent variability, in order to make long-term use of BCI possible, it is important to track changes in ongoing EEG activity and to adapt BCI model parameters accordingly. To this aim, the asynchronous classifier has been subsequently improved by introducing a self-calibration algorithm for the continuous and unsupervised recalibration of the subjective control parameters. Finally an index for the online monitoring of the EEG quality has been defined and validated in order to detect potential problems and system failures. This thesis ends with the description of a translational work involving end users (people with amyotrophic lateral sclerosis-ALS). Focusing on the concepts of the user centered design approach, the phases relating to the design, the development and the validation of an innovative assistive device have been described. The proposed assistive technology (AT) has been specifically designed to meet the needs of people with ALS during the different phases of the disease (i.e. the degree of motor abilities impairment). Indeed, the AT can be accessed with several input devices either conventional (mouse, touchscreen) or alterative (switches, headtracker) up to a P300-based BCI.

Effect of Classroom Gender Composition on Students' Development of Self-Regulated Learning Competencies

Success in any field depends on a complex interplay among environmental and personal factors. A key set of personal factors for success in academic settings are those associated with self-regulated learners (SRL). Self-regulated learners choose their own goals, select and organize their learning strategies, and self-monitor their effectiveness. Behaviors and attitudes consistent with self-regulated learning also contribute to self-confidence, which may be important for members of underrepresented groups such as women in engineering. This exploratory study, drawing on the concept of "critical mass", examines the relationship between the personal factors that identify a self-regulated learner and the environmental factors related to gender composition of engineering classrooms. Results indicate that a relatively student gender-balanced classroom and gender match between students and their instructors provide for the development of many adaptive SRL behaviors and attitudes.

"Self" and "nonself" manipulation of interferon defense during persistent infection: bovine viral diarrhea virus resists alpha/beta interferon without blocking antiviral activity against unrelated viruses replicating in its host cells

Bovine viral diarrhea virus (BVDV), together with Classical swine fever virus (CSFV) and Border disease virus (BDV) of sheep, belongs to the genus Pestivirus of the Flaviviridae. BVDV is either cytopathic (cp) or noncytopathic (ncp), as defined by its effect on cultured cells. Infection of pregnant animals with the ncp biotype may lead to the birth of persistently infected calves that are immunotolerant to the infecting viral strain. In addition to evading the adaptive immune system, BVDV evades key mechanisms of innate immunity. Previously, we showed that ncp BVDV inhibits the induction of apoptosis and alpha/beta interferon (IFN-alpha/beta) synthesis by double-stranded RNA (dsRNA). Here, we report that (i) both ncp and cp BVDV block the induction by dsRNA of the Mx protein (which can also be induced in the absence of IFN signaling); (ii) neither biotype blocks the activity of IFN; and (iii) once infection is established, BVDV is largely resistant to the activity of IFN-alpha/beta but (iv) does not interfere with the establishment of an antiviral state induced by IFN-alpha/beta against unrelated viruses. The results of our study suggest that, in persistent infection, BVDV is able to evade a central element of innate immunity directed against itself without generally compromising its activity against unrelated viruses ("nonself") that may replicate in cells infected with ncp BVDV. This highly selective "self" and "nonself" model of evasion of the interferon defense system may be a key element in the success of persistent infection in addition to immunotolerance initiated by the early time point of fetal infection.

A Cooperative and Adaptive Variable Neighborhood Search for the Multi Depot Vehicle Routing Problem with Time Windows

In this paper we propose two cooperation schemes to compose new parallel variants of the Variable Neighborhood Search (VNS). On the one hand, a coarse-grained cooperation scheme is introduced which is well suited for being enhanced with a solution warehouse to store and manage the so far best found solutions and a self-adapting mechanism for the most important search parameters. This makes an a priori parameter tuning obsolete. On the other hand, a fine-grained scheme was designed to reproduce the successful properties of the sequential VNS. In combination with the use of parallel exploration threads all of the best solutions and 11 out of 20 new best solutions for the Multi Depot Vehicle Routing Problem with Time Windows were found.

Adaptive Materialbereitstellung in flexiblen Produktionssystemen auf Grundlage einer agentenbasierten Transportsteuerung

Zur Sicherstellung einer schnellen und flexiblen Anpassung an sich ändernde Anforderungen sind innerbetriebliche Materialbereitstellungskonzepte in immer stärkerem Maße zu flexibilisieren. Hierdurch kann die Erreichung logistischer Ziele in einem dynamischen Produktionsumfeld gesteigert werden. Der Beitrag stellt ein Konzept für eine adaptive Materialbereitstellung in flexiblen Produktionssystemen auf Grundlage einer agentenbasierten Transportplanung und -steuerung vor. Der Fokus liegt hierbei auf der Planung und Steuerung der auf Basis von Materialbedarfsmeldungen ausgelösten innerbetrieblichen Transporte. Neben Pendeltouren zur Versorgung des Produktionssystems findet auch das dynamische Pickup-and-Delivery-Problem Berücksichtigung. Das vorgestellte Konzept ist an den Anforderungen selbstorganisierender Produktionsprozesse ausgerichtet.

Traffic-Adaptive and Link-Quality-Aware Communication in Wireless Sensor Networks

This paper is a summary of the main contribu- tions of the PhD thesis published in [1]. The main research contributions of the thesis are driven by the research question how to design simple, yet efficient and robust run-time adaptive resource allocation schemes within the commu- nication stack of Wireless Sensor Network (WSN) nodes. The thesis addresses several problem domains with con- tributions on different layers of the WSN communication stack. The main contributions can be summarized as follows: First, a a novel run-time adaptive MAC protocol is intro- duced, which stepwise allocates the power-hungry radio interface in an on-demand manner when the encountered traffic load requires it. Second, the thesis outlines a metho- dology for robust, reliable and accurate software-based energy-estimation, which is calculated at network run- time on the sensor node itself. Third, the thesis evaluates several Forward Error Correction (FEC) strategies to adap- tively allocate the correctional power of Error Correcting Codes (ECCs) to cope with timely and spatially variable bit error rates. Fourth, in the context of TCP-based communi- cations in WSNs, the thesis evaluates distributed caching and local retransmission strategies to overcome the perfor- mance degrading effects of packet corruption and trans- mission failures when transmitting data over multiple hops. The performance of all developed protocols are eval- uated on a self-developed real-world WSN testbed and achieve superior performance over selected existing ap- proaches, especially where traffic load and channel condi- tions are suspect to rapid variations over time.

Perceived malleability of self versus the world and its impact on youths’ control orientation and well-being in the US, Germany, and India

Primary control is defined as changing the world to fit the self, while secondary control is defined as changing the self to fit the world. To understand why different individuals prefer different kinds of control processes, we proposed a research project looking at US, German and Indian young adults. We hypothesize that theories of self and the world (fixed vs. malleable; Dweck, 1999) affect the prevailing mode of control used. Furthermore, adolescents’ cultural background is assumed to affect their self-world theories as well as the adaptiveness of specific modes of control. For example, in the US, where the self is tended to be seen as fixed and the world as malleable, primary control prevails and is more adaptive than secondary control while the reverse is expected for India. We present the theoretical outline and methodology of the study as well as first results.

Self-control in social decision making: A neurobiological perspective

Self-control is defined as the process in which thoughts, emotions, or prepotent responses are inhibited to efficiently enact a more focal goal. Self-control not only allows for more adaptive individual decision making but also promotes adaptive social decision making. In this chapter, we examine a burgeoning area of interdisciplinary research: the neuroscience of self-control in social decision making. We examine research on self-control in complex social contexts examined from a social neuroscience perspective. We review correlational evidence from neuroimaging studies and causal evidence from neuromodulation studies (i.e., brain stimulation). We specifically highlight research that shows that self-control involves the lateral prefrontal cortex (PFC) across a number of social domains and behaviors. Research has also begun to directly integrate nonsocial with social forms of self-control, showing that the basic neurobiological processes involved in stopping a motor response appear to be involved in social contexts that require self-control. Further, neural traits, such as baseline activation in the lateral PFC, can explain sources of individual differences in self-control capacity. We explore whether techniques that change brain functioning could target neural mechanisms related to self-control capacity to potentially enhance self-control in social behavior. Finally, we discuss several research questions ripe for examination. We broadly suggest that future research can now turn to exploring how neural traits and situational affordances interact to impact self-control in social decision making in order to continue to elucidate the processes that allow people to maintain and realize stable goals in a dynamic and often uncertain social environment.

Messung dispositioneller Selbstkontroll-Kapazität: Eine deutsche Adaptation der Kurzform der Self-Control Scale (SCS-K-D)

Self-control is defined as the overriding or modification of one’s own response tendencies. Dispositional self control capacity is positively linked to various kinds of adaptive behavior. In order to economically measure self-control capacity in German-speaking samples, the brief version of the Self-Control Scale by Tangney, Baumeister and Boone (2004) was adapted into German. The translated entire Self-Control Scale consisting of 36 items was administered to university students (N = 316, study 1) and secondary school students (N = 335, study 2). The brief version consisting of 13 items, which were included in the entire scale, proved to be one-dimensional, reliable, and valid in terms of expected correlations with criteria. The comparison between the brief and the entire scale showed that the costs of the more economical brief measure with regard to reliability and validity are low.

DNA-Grafted Supramolecular Polymers: Helical Ribbon Structures Formed by Self-Assembly of Pyrene-DNA Chimeric Oligomers

The controlled arraying of DNA strands on adaptive polymeric platforms remains a challenge. Here, the noncovalent synthesis of DNA-grafted supramolecular polymers from short chimeric oligomers is presented. The oligomers are composed of an oligopyrenotide strand attached to the 5′-end of an oligodeoxynucleotide. The supramolecular polymerization of these oligomers in an aqueous medium leads to the formation of one-dimensional (1D) helical ribbon structures. Atomic force and transmission electron microscopy show rod-like polymers of several hundred nanometers in length. DNA-grafted polymers of the type described herein will serve as models for the development of structurally and functionally diverse supramolecular platforms with applications in materials science and diagnostics.

Bio-inspired FPGA Architecture for Self-Calibration of an Image Compression Core based on Wavelet Transforms in Embedded Systems

A generic bio-inspired adaptive architecture for image compression suitable to be implemented in embedded systems is presented. The architecture allows the system to be tuned during its calibration phase. An evolutionary algorithm is responsible of making the system evolve towards the required performance. A prototype has been implemented in a Xilinx Virtex-5 FPGA featuring an adaptive wavelet transform core directed at improving image compression for specific types of images. An Evolution Strategy has been chosen as the search algorithm and its typical genetic operators adapted to allow for a hardware friendly implementation. HW/SW partitioning issues are also considered after a high level description of the algorithm is profiled which validates the proposed resource allocation in the device fabric. To check the robustness of the system and its adaptation capabilities, different types of images have been selected as validation patterns. A direct application of such a system is its deployment in an unknown environment during design time, letting the calibration phase adjust the system parameters so that it performs efcient image compression. Also, this prototype implementation may serve as an accelerator for the automatic design of evolved transform coefficients which are later on synthesized and implemented in a non-adaptive system in the final implementation device, whether it is a HW or SW based computing device. The architecture has been built in a modular way so that it can be easily extended to adapt other types of image processing cores. Details on this pluggable component point of view are also given in the paper.