Study of behavioural and neural bases of visuo-spatial working memory with an fMRI paradigm based on an n-back task

The goal of this study was to propose a new functional magnetic resonance imaging (fMRI) paradigm using a language-free adaptation of a 2-back working memory task to avoid cultural and educational bias. We additionally provide an index of the validity of the proposed paradigm and test whether the experimental task discriminates the behavioural performances of healthy participants from those of individuals with working memory deficits. Ten healthy participants and nine patients presenting working memory (WM) deficits due to acquired brain injury (ABI) performed the developed task. To inspect whether the paradigm activates brain areas typically involved in visual working memory (VWM), brain activation of the healthy participants was assessed with fMRIs. To examine the task's capacity to discriminate behavioural data, performances of the healthy participants in the task were compared with those of ABI patients. Data were analysed with GLM-based random effects procedures and t-tests. We found an increase of the BOLD signal in the specialized areas of VWM. Concerning behavioural performances, healthy participants showed the predicted pattern of more hits, less omissions and a tendency for fewer false alarms, more self-corrected responses, and faster reaction times, when compared with subjects presenting WM impairments. The results suggest that this task activates brain areas involved in VWM and discriminates behavioural performances of clinical and non-clinical groups. It can thus be used as a research methodology for behavioural and neuroimaging studies of VWM in block-design paradigms.

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

Analysis of self-interference within DAG tasks

6th Real-Time Scheduling Open Problems Seminar (RTSOPS 2015), Lund, Sweden.

A Visual Programming Framework for Wireless Sensor Networks in Smart Home Applications

International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2015). 7 to 9, Apr, 2015. Singapure, Singapore.

A system model and stack for the parallelization of time-critical applications on many-core architectures

3rd Workshop on High-performance and Real-time Embedded Systems (HIRES 2015). 21, Jan, 2015. Amsterdam, Netherlands.

A Modular Programming Approach for IoTBased Wireless Sensor Networks

Poster presented in 12th European Conference on Wireless Sensor Network (EWSN 2015). 9 to 11, Feb, 2015. Porto, Portugal.

P-SOCRATES: A parallel software framework for time-critical many-core systems

Article in Press, Corrected Proof

Ensemble: an innovative approach to practice computer programming

Currently, the teaching-learning process in domains, such as computer programming, is characterized by an extensive curricula and a high enrolment of students. This poses a great workload for faculty and teaching assistants responsible for the creation, delivery, and assessment of student exercises. The main goal of this chapter is to foster practice-based learning in complex domains. This objective is attained with an e-learning framework—called Ensemble—as a conceptual tool to organize and facilitate technical interoperability among services. The Ensemble framework is used on a specific domain: computer programming. Content issues are tacked with a standard format to describe programming exercises as learning objects. Communication is achieved with the extension of existing specifications for the interoperation with several systems typically found in an e-learning environment. In order to evaluate the acceptability of the proposed solution, an Ensemble instance was validated on a classroom experiment with encouraging results.

Design a computer programming learning environment for Massive Open Online Courses

Teaching and learning computer programming is as challenging as difficult. Assessing the work of students and providing individualised feedback to all is time-consuming and error prone for teachers and frequently involves a time delay. The existent tools and specifications prove to be insufficient in complex evaluation domains where there is a greater need to practice. At the same time Massive Open Online Courses (MOOC) are appearing revealing a new way of learning, more dynamic and more accessible. However this new paradigm raises serious questions regarding the monitoring of student progress and its timely feedback. This paper provides a conceptual design model for a computer programming learning environment. This environment uses the portal interface design model gathering information from a network of services such as repositories and program evaluators. The design model includes also the integration with learning management systems, a central piece in the MOOC realm, endowing the model with characteristics such as scalability, collaboration and interoperability. This model is not limited to the domain of computer programming and can be adapted to any complex area that requires systematic evaluation with immediate feedback.

Spatial neighborhood matrix computation: Inverse distance weighted versus binary contiguity

Paper presented at Geo-Spatial Crossroad GI_Forum, Salzburg, Austria.

Predictivity Strength of the Spatial Variability of Phenanthrene Sorption Across Two Sandy Loam Fields

Sorption is commonly agreed to be the major process underlying the transport and fate of polycyclic aromatic hydrocarbons (PAHs) in soils. However, there is still a scarcity of studies focusing on spatial variability at the field scale in particular. In order to investigate the variation in the field of phenanthrene sorption, bulk topsoil samples were taken in a 15 × 15-m grid from the plough layer in two sandy loam fields with different texture and organic carbon (OC) contents (140 samples in total). Batch experiments were performed using the adsorption method. Values for the partition coefficient K d (L kg−1) and the organic carbon partition coefficient K OC (L kg−1) agreed with the most frequently used models for PAH partitioning, as OC revealed a higher affinity for sorption. More complex models using different OC compartments, such as non-complexed organic carbon (NCOC) and complexed organic carbon (COC) separately, performed better than single K OC models, particularly for a subset including samples with Dexter n < 10 and OC <0.04 kg kg−1. The selected threshold revealed that K OC-based models proved to be applicable for more organic fields, while two-component models proved to be more accurate for the prediction of K d and retardation factor (R) for less organic soils. Moreover, OC did not fully reflect the changes in phenanthrene retardation in the field with lower OC content (Faardrup). Bulk density and available water content influenced the phenanthrene transport mechanism phenomenon.

Re-Use Assessment of Thermoset Composite Wastes as Aggregate and Filler Replacement for Concrete-Polymer Composite Materials: A case study regarding GFRP pultrusion wastes

Glass fibre-reinforced plastics (GFRP), nowadays commonly used in the construction, transportation and automobile sectors, have been considered inherently difficult to recycle due to both the cross-linked nature of thermoset resins, which cannot be remoulded, and the complex composition of the composite itself, which includes glass fibres, polymer matrix and different types of inorganic fillers. Hence, to date, most of the thermoset based GFRP waste is being incinerated or landfilled leading to negative environmental impacts and additional costs to producers and suppliers. With an increasing awareness of environmental matters and the subsequent desire to save resources, recycling would convert an expensive waste disposal into a profitable reusable material. In this study, the effect of the incorporation of mechanically recycled GFRP pultrusion wastes on flexural and compressive behaviour of polyester polymer mortars (PM) was assessed. For this purpose, different contents of GFRP recyclates (0%, 4%, 8% and 12%, w/w), with distinct size grades (coarse fibrous mixture and fine powdered mixture), were incorporated into polyester PM as sand aggregates and filler replacements. The effect of the incorporation of a silane coupling agent was also assessed. Experimental results revealed that GFRP waste filled polymer mortars show improved mechanical behaviour over unmodified polyester based mortars, thus indicating the feasibility of GFRP waste reuse as raw material in concrete-polymer composites.