Accessing forgotten memory traces from long-term memory via visual movements

Because memory retrieval often requires overt responses, it is difficult to determine to what extend forgetting occurs as a problem in explicit accessing of long-term memory traces. In this study, we used eye-tracking measures in combination with a behavioural task that favoured high forgetting rates to investigate the existence of memory traces from long-term memory in spite of failure in accessing them consciously. In 2 experiments, participants were encouraged to encode a large set of sound-picture56 location associations. In a later test, sounds were presented and participants were instructed to visually scan, before a verbal memory report, for the correct location of the associated pictures in an empty screen. We found the reactivation of associated memories by sound cues at test biased oculomotor behaviour towards locations congruent with memory representations, even when participants failed to consciously provide a memory report of it. These findings reveal the emergence of a memory-guided behaviour that can be used to map internal representations of forgotten memories from long-term memory.

Recognition of prior learning in online postgraduate education

The recognition of prior experiential learning (RPEL) involves the assessment ofskills and knowledge acquired by an individual through previous experience, which isnot necessarily related to an academic context. RPEL practices are far from generalisedin higher education, and there is a lack of specific guidelines on how to implement RPLprograms in particular settings, such as management education or online programs. TheRPEL pilot program developed in a Spanish virtual university is used throughout thearticle as the basis for further reflection on the design and implementation of RPEL inonline postgraduate education in the business field. The role of competences as a centraltheoretical foundation for RPEL is explained, and the context and characteristics of theRPEL program described. Special attention is paid to the key elements of the program¿sdesign and to the practical aspects of its implementation. The results of the program areassessed and general conclusions and suggestions for further research are discussed.

Shared feature extraction for nearest neighbor face recognition

In this paper, we propose a new supervised linearfeature extraction technique for multiclass classification problemsthat is specially suited to the nearest neighbor classifier (NN).The problem of finding the optimal linear projection matrix isdefined as a classification problem and the Adaboost algorithmis used to compute it in an iterative way. This strategy allowsthe introduction of a multitask learning (MTL) criterion in themethod and results in a solution that makes no assumptions aboutthe data distribution and that is specially appropriated to solvethe small sample size problem. The performance of the methodis illustrated by an application to the face recognition problem.The experiments show that the representation obtained followingthe multitask approach improves the classic feature extractionalgorithms when using the NN classifier, especially when we havea few examples from each class

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Optical Character Recognition for Symbian OS

This Master's thesis addresses the design and implementation of the optical character recognition (OCR) system for a mobile device working on the Symbian operating system. The developed OCR system, named OCRCapriccio, emphasizes the modularity, effective extensibility and reuse. The system consists of two parts which are the graphical user interface and the OCR engine that was implemented as a plug-in. In fact, the plug-in includes two implementations of the OCR engine for enabling two types of recognition: the bitmap comparison based recognition and statistical recognition. The implementation results have shown that the approach based on bitmap comparison is more suitable for the Symbian environment because of its nature. Although the current implementation of bitmap comparison is lacking in accuracy, further development should be done in its direction. The biggest challenges of this work were related to developing an OCR scheme that would be suitable for Symbian OS Smartphones that have limited computational power and restricted resources.

El papel de la memoria de trabajo en el cálculo mental un cuarto de siglo después de Hitch = The role of working memory in mental arithmetic a quarter of century after Hitch

Desde que Hitch (1978) publicó el primer estudio sobre el rol de la memoria de trabajo en el cálculo han idoaumentando las investigaciones en este campo. Muchos trabajos han estudiado un único subsistema, pero nuestroobjetivo es identificar qué subsistema de la memoria de trabajo (bucle fonológico, agenda viso-espacial o ejecutivocentral) está más implicado en el cálculo mental. Para ello hemos realizado un estudio correlacional en el quehemos administrado dos pruebas aritméticas y nueve pruebas de la “Bateria de Test de Memòria de Treball” dePickering, Baqués y Gathercole (1999) a una muestra de 94 niños españoles de 7-8 años. Nuestros resultadosindican que el bucle fonológico y sobretodo el ejecutivo central inciden de forma estadísticamente significativa enel rendimiento aritmético

Sähköinen tarkastuslista rakennusteollisuuden laadunvalvonnan tukena

Rakennusteollisuus on tunnettu useita muita aloja hitaammasta uuden teknologian käyttöönotosta. Yleisesti käytössä on hyvin perinteinen paperia ja kynää hyödyntävä tiedontallennuskäytäntö. Paperin käytössä tiedon tallennusvälineenä on useita ongelmia kuten säilytettävyys ja hallittavuus, joista päästään eroon siirtymällä sähköiseen tiedon tallennukseen. Laadun varmistamiseksi voidaan käyttää tarkastuslistoja, jotka toimivat tarkastuksien suorittajan muistin tukena. Muutettaessa tarkastuslista sähköiseen muotoon, voidaan välttyä paperisen tarkastuslistan ongelmilta, kuten käsialan tunnistamiselta ja merkintätapojen vaihtelevuudelta. Tässä diplomityössä käsitellään rakennusteollisuuden laadunhallinnan nykytilaa sekä sähköisen tarkastuslistan käyttöä rakennusteollisuuden laadunvalvonnassa. Lisäksi esitellään prototyyppi sähköisestä tarkastuslistasta osana laadunvalvontaa. Sähköinen tarkastuslista toteutetaan dynaamisesti niin, että tarkastuslistojen pohjalta on mahdollista luoda käyttöliittymä kyseessä olevan listan mukaisesti päätelaitteelle. Sähköisen tarkastuslistan prototyyppi on toteutettu WWW-sovelluspalveluna (World Wide Web), joka mahdollistaa useiden erilaisten päätelaitteiden hyödyntämisen.

Towards a lightweight adaptative multicomponential affective recognition system

As part of the Affective Computing research field, the development of automatic affective recognition systems can enhance human-computer interactions by allowing the creation of interfaces that react to the user's emotional state. To that end, this Master Thesis brings affect recognition to nowadays most used human computer interface, mobile devices, by developing a facial expression recognition system able to perform detection under the difficult conditions of viewing angle and illumination that entails the interaction with a mobile device. Moreover, this Master Thesis proposes to combine emotional features detected from expression with contextual information of the current situation, to infer a complex and extensive emotional state of the user. Thus, a cognitive computational model of emotion is defined that provides a multicomponential affective state of the user through the integration of the detected emotional features into appraisal processes. In order to account for individual differences in the emotional experience, these processes can be adapted to the culture and personality of the user.

Studying Memory Encoding to Promote Reliable Engagement of the Medial Temporal Lobe at the Single-subject Level

The medial temporal lobe (MTL)-comprising hippocampus and the surrounding neocortical regions-is a targeted brain area sensitive to several neurological diseases. Although functional magnetic resonance imaging (fMRI) has been widely used to assess brain functional abnormalities, detecting MTL activation has been technically challenging. The aim of our study was to provide an fMRI paradigm that reliably activates MTL regions at the individual level, thus providing a useful tool for future research in clinical memory-related studies. Twenty young healthy adults underwent an event-related fMRI study consisting of three encoding conditions: word-pairs, face-name associations and complex visual scenes. A region-of-interest analysis at the individual level comparing novel and repeated stimuli independently for each task was performed. The results of this analysis yielded activations in the hippocampal and parahippocampal regions in most of the participants. Specifically, 95% and 100% of participants showed significant activations in the left hippocampus during the face-name encoding and in the right parahippocampus, respectively, during scene encoding. Additionally, a whole brain analysis, also comparing novel versus repeated stimuli at the group level, showed mainly left frontal activation during the word task. In this group analysis, the face-name association engaged the HP and fusiform gyri bilaterally, along with the left inferior frontal gyrus, and the complex visual scenes activated mainly the parahippocampus and hippocampus bilaterally. In sum, our task design represents a rapid and reliable manner to study and explore MTL activity at the individual level, thus providing a useful tool for future research in clinical memory-related fMRI studies.

Physical Realization of an Optical Automatic Target Recognition System

In the modern warfare there is an active development of a new trend connected with a robotic warfare. One of the critical elements of robotics warfare systems is an automatic target recognition system, allowing to recognize objects, based on the data received from sensors. This work considers aspects of optical realization of such a system by means of NIR target scanning at fixed wavelengths. An algorithm was designed, an experimental setup was built and samples of various modern gear and apparel materials were tested. For pattern testing the samples of actively arm engaged armies camouflages were chosen. Tests were performed both in clear atmosphere and in the artificial extremely humid and hot atmosphere to simulate field conditions.

Memory as acquaintance with the past: some Lessons from Russell, 1912-1914

Russell's theory of memory as acquaintance with the past seems to square uneasily with his definition of acquaintance as the converse of the relation of presentation of an object to a subject. We show how the two views can be made to cohere under a suitable construal of 'presentation', which has the additional appeal of bringing Russell's theory of memory closer to contemporary views on direct reference and object-dependent thinking than is usually acknowledged. The drawback is that memory as acquaintance with the past falls short of fulfilling Russell's requirement that knowledge by acquaintance be discriminating knowledge - a shortcoming shared by contemporary externalist accounts of knowledge from memory.