Automatic Prediction of Facial Trait Judgments: Appearance vs. Structural Models

Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance) can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a) derive a facial trait judgment model from training data and b) predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations) and classification rules (4 rules) suggest that a) prediction of perception of facial traits is learnable by both holistic and structural approaches; b) the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c) for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

Computer-aided discovery of biological activity spectra for anti-aging and anti-cancer olive oil oleuropeins

Aging is associated with common conditions, including cancer, diabetes, cardiovascular disease, and Alzheimer"s disease. The type of multi‐targeted pharmacological approach necessary to address a complex multifaceted disease such as aging might take advantage of pleiotropic natural polyphenols affecting a wide variety of biological processes. We have recently postulated that the secoiridoids oleuropein aglycone (OA) and decarboxymethyl oleuropein aglycone (DOA), two complex polyphenols present in health‐promoting extra virgin olive oil (EVOO), might constitute a new family of plant‐produced gerosuppressant agents. This paper describes an analysis of the biological activity spectra (BAS) of OA and DOA using PASS (Prediction of Activity Spectra for Substances) software. PASS can predict thousands of biological activities, as the BAS of a compound is an intrinsic property that is largely dependent on the compound"s structure and reflects pharmacological effects, physiological and biochemical mechanisms of action, and specific toxicities. Using Pharmaexpert, a tool that analyzes the PASS‐predicted BAS of substances based on thousands of"mechanism‐ effect" and"effect‐mechanism" relationships, we illuminate hypothesis‐generating pharmacological effects, mechanisms of action, and targets that might underlie the anti‐aging/anti‐cancer activities of the gerosuppressant EVOO oleuropeins.

Una arqueometria del canvi tecnològic: producció i consum d'àmfores durant el canvi d'era en la zona nord de la costa catalana

L’objectiu de la recerca és definir un marc teòric i metodològic per a l’estudi del canvi tecnològic en Arqueologia. Aquest model posa èmfasi en caracteritzar els compromisos que configuren una tecnologia i avaluar-los en funció dels factors de situació —tècnics, econòmics, polítics, socials i ideològics. S’ha aplicat aquest model a un cas d’estudi concret: la producció d’àmfores romanes durant el canvi d’Era en la província Tarraconensis. L’estudi tecnològic dels envasos s’ha realitzat mitjançant diverses tècniques analítiques: Fluorescència de raigs X (FRX), Difracció de raigs X (DRX), Microscòpia òptica (MO) i Microscòpia electrònica de rastreig (MER). Les dades obtingudes permeten, a més, establir els grups de referència per a cada centre productor d’àmfores i, així, identificar la provinença dels individus recuperats en els centres consumidors. Donat que les àmfores en estudi són artefactes dissenyats específicament per a ser estibats en una nau i servir com a envàs de transport, l’estudi inclou la caracterització de les propietats mecàniques de resistència a la fractura i de tenacitat. En aquest sentit, i per primera vegada, s’ha aplicat l’Anàlisi d’Elements Finits (AEF) per a conèixer el comportament dels diferents dissenys d’àmfora en ésser sotmesos a diverses forces d’ús. L’AEF permet simular per ordinador les activitats en què les àmfores haurien participat durant el seu ús i avaluar-ne el seu comportament tècnic. Els resultats mostren una gran adequació entre les formulacions teòriques i el programa analític implementat per a aquest estudi. Respecte el cas d’estudi, els resultats mostren una gran variabilitat en les eleccions tecnològiques preses pels ceramistes de diferents tallers, però també al llarg del període de funcionament d’un mateix taller. L’aplicació del model ha permès proposar una explicació al canvi de disseny de les àmfores romanes.

Efficient knowledge retrieval to calibrate input variables in forest fire prediction

Forest fires are a serious threat to humans and nature from an ecological, social and economic point of view. Predicting their behaviour by simulation still delivers unreliable results and remains a challenging task. Latest approaches try to calibrate input variables, often tainted with imprecision, using optimisation techniques like Genetic Algorithms. To converge faster towards fitter solutions, the GA is guided with knowledge obtained from historical or synthetical fires. We developed a robust and efficient knowledge storage and retrieval method. Nearest neighbour search is applied to find the fire configuration from knowledge base most similar to the current configuration. Therefore, a distance measure was elaborated and implemented in several ways. Experiments show the performance of the different implementations regarding occupied storage and retrieval time with overly satisfactory results.

Sistema de monitorització Open Source: projecte d'empresa per Computer Technology Catalunya

L’objectiu del projecte consisteix en l’estudi, simulació i implantació d’un conjunt d’aplicacions que permeten tenir un control sobre possibles problemes que puguin succeir a la nostra xarxa. Aquest projecte és la solució als problemes de detecció d’errors en el funcionament de les infraestructures de networking de les que disposen els nostres clients.

Prediction of the economic cost of individual long-term care in the Spanish population

Pensions together with savings and investments during active life are key elements of retirement planning. Motivation for personal choices about the standard of living, bequest and the replacement ratio of pension with respect to last salary income must be considered. This research contributes to the financial planning by helping to quantify long-term care economic needs. We estimate life expectancy from retirement age onwards. The economic cost of care per unit of service is linked to the expected time of needed care and the intensity of required services. The expected individual cost of long-term care from an onset of dependence is estimated separately for men and women. Assumptions on the mortality of the dependent people compared to the general population are introduced. Parameters defining eligibility for various forms of coverage by the universal public social care of the welfare system are addressed. The impact of the intensity of social services on individual predictions is assessed, and a partial coverage by standard private insurance products is also explored. Data were collected by the Spanish Institute of Statistics in two surveys conducted on the general Spanish population in 1999 and in 2008. Official mortality records and life table trends were used to create realistic scenarios for longevity. We find empirical evidence that the public long-term care system in Spain effectively mitigates the risk of incurring huge lifetime costs. We also find that the most vulnerable categories are citizens with moderate disabilities that do not qualify to obtain public social care support. In the Spanish case, the trends between 1999 and 2008 need to be further explored.

Electronic voting system for computer supported collaborative learning

The EVS4CSCL project starts in the context of a Computer Supported Collaborative Learning environment (CSCL). Previous UOC projects created a CSCL generic platform (CLPL) to facilitate the development of CSCL applications. A discussion forum (DF) was the first application developed over the framework. This discussion forum was different from other products on the marketplace because of its focus on the learning process. The DF carried out the specification and elaboration phases from the discussion learning process but there was a lack in the consensus phase. The consensus phase in a learning environment is not something to be achieved but tested. Common tests are done by Electronic Voting System (EVS) tools, but consensus test is not an assessment test. We are not evaluating our students by their answers but by their discussion activity. Our educational EVS would be used as a discussion catalyst proposing a discussion about the results after an initial query or it would be used after a discussion period in order to manifest how the discussion changed the students mind (consensus). It should be also used by the teacher as a quick way to know where the student needs some reinforcement. That is important in a distance-learning environment where there is no direct contact between the teacher and the student and it is difficult to detect the learning lacks. In an educational environment, assessment it is a must and the EVS will provide direct assessment by peer usefulness evaluation, teacher marks on every query created and indirect assessment from statistics regarding the user activity.

Modelling the Human Values Scale from Consumers Transactional Data Bases

The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the data base used by the recommender systems, and which allow to resolve the specific problems of prediction and recommendation. In this work, we propose to extract the user's human values scale from the data base of the users, to improve their suitability in open environments, such as the recommender systems. For this purpose, the methodology is applied with the data of the user after interacting with the system. The methodology is exemplified with a case study

Embedding Emotional Context in Recommender Systems

Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems

Searching patterns in painting images with computer vision techniques

This paper presents a pattern recognition method focused on paintings images. The purpose is construct a system able to recognize authors or art styles based on common elements of his work (here called patterns). The method is based on comparing images that contain the same or similar patterns. It uses different computer vision techniques, like SIFT and SURF, to describe the patterns in descriptors, K-Means to classify and simplify these descriptors, and RANSAC to determine and detect good results. The method are good to find patterns of known images but not so good if they are not.

Human-Computer Interaction with older people through ethnographical lenses: everyday interactions with ICT

Report for the scientific sojourn carried out at the School of Computing of the University of Dundee, United Kingdom, from 2010 to 2012. This document is a scientific report of the work done, main results, publications and accomplishment of the objectives of the 2-year post-doctoral research project with reference number BP-A 00239. The project has addressed the topic of older people (60+) and Information and Communication Technologies (ICT), which is a topic of growing social and research interest, from a Human-Computer Interaction perspective. Over a 2-year period (June 2010-June 2012), we have conducted classical ethnography of ICT use in a computer clubhouse in Scotland, addressing interaction barriers and strategies, social sharing practices in Social Network Sites, and ICT learning, and carried out rapid ethnographical studies related to geo-enabled ICT and e-government services towards supporting independent living and active ageing. The main results have provided a much deeper understanding of (i) the everyday use of Computer-Mediated Communication tools, such as video-chats and blogs, and its evolution as older people’s experience with ICT increases over time, (ii) cross-cultural aspects of ICT use in the north and south of Europe, (iii) the relevance of cognition over vision in interacting with geographical information and a wide range of ICT tools, despite common stereotypes (e.g. make things bigger), (iv) the important relationship offline-online to provide older people with socially inclusive and meaningful eservices for independent living and active ageing, (v) how older people carry out social sharing practices in the popular YouTube, (vi) their user experiences and (vii) the challenges they face in ICT learning and the strategies they use to become successful ICT learners over time. The research conducted in this project has been published in 17 papers, 4 in journals – two of which in JCR, 5 in conferences, 4 in workshops and 4 in magazines. Other public output consists of 10 invited talks and seminars.

Developing methodologies to allow the robust prediction dynamic context dominated by perturbations

El principal objectiu del projecte era desenvolupar millores conceptuals i metodològiques que permetessin una millor predicció dels canvis en la distribució de les espècies (a una escala de paisatge) derivats de canvis ambientals en un context dominat per pertorbacions. En un primer estudi, vàrem comparar l'eficàcia de diferents models dinàmics per a predir la distribució de l'hortolà (Emberiza hortulana). Els nostres resultats indiquen que un model híbrid que combini canvis en la qualitat de l'hàbitat, derivats de canvis en el paisatge, amb un model poblacional espacialment explícit és una aproximació adequada per abordar canvis en la distribució d'espècies en contextos de dinàmica ambiental elevada i una capacitat de dispersió limitada de l'espècie objectiu. En un segon estudi abordarem la calibració mitjançant dades de seguiment de models de distribució dinàmics per a 12 espècies amb preferència per hàbitats oberts. Entre les conclusions extretes destaquem: (1) la necessitat de que les dades de seguiment abarquin aquelles àrees on es produeixen els canvis de qualitat; (2) el biaix que es produeix en la estimació dels paràmetres del model d'ocupació quan la hipòtesi de canvi de paisatge o el model de qualitat d'hàbitat són incorrectes. En el darrer treball estudiarem el possible impacte en 67 espècies d’ocells de diferents règims d’incendis, definits a partir de combinacions de nivells de canvi climàtic (portant a un augment esperat de la mida i freqüència d’incendis forestals), i eficiència d’extinció per part dels bombers. Segons els resultats dels nostres models, la combinació de factors antropogènics del regim d’incendis, tals com l’abandonament rural i l’extinció, poden ser més determinants per als canvis de distribució que els efectes derivats del canvi climàtic. Els productes generats inclouen tres publicacions científiques, una pàgina web amb resultats del projecte i una llibreria per a l'entorn estadístic R.

SGP-1: prediction and validation of homologous genes based on sequence alignments

Conventional methods of gene prediction rely on the recognition of DNA-sequence signals, the coding potential or the comparison of a genomic sequence with a cDNA, EST, or protein database. Reasons for limited accuracy in many circumstances are species-specific training and the incompleteness of reference databases. Lately, comparative genome analysis has attracted increasing attention. Several analysis tools that are based on human/mouse comparisons are already available. Here, we present a program for the prediction of protein-coding genes, termed SGP-1 (Syntenic Gene Prediction), which is based on the similarity of homologous genomic sequences. In contrast to most existing tools, the accuracy of SGP-1 depends little on species-specific properties such as codon usage or the nucleotide distribution. SGP-1 may therefore be applied to nonstandard model organisms in vertebrates as well as in plants, without the need for extensive parameter training. In addition to predicting genes in large-scale genomic sequences, the program may be useful to validate gene structure annotations from databases. To this end, SGP-1 output also contains comparisons between predicted and annotated gene structures in HTML format. The program can be accessed via a Web server at http://soft.ice.mpg.de/sgp-1. The source code, written in ANSI C, is available on request from the authors.

An assessment of gene prediction accuracy in large DNA sequences

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

Comparative gene prediction in human and mouse

The completion of the sequencing of the mouse genome promises to help predict human genes with greater accuracy. While current ab initio gene prediction programs are remarkably sensitive (i.e., they predict at least a fragment of most genes), their specificity is often low, predicting a large number of false-positive genes in the human genome. Sequence conservation at the protein level with the mouse genome can help eliminate some of those false positives. Here we describe SGP2, a gene prediction program that combines ab initio gene prediction with TBLASTX searches between two genome sequences to provide both sensitive and specific gene predictions. The accuracy of SGP2 when used to predict genes by comparing the human and mouse genomes is assessed on a number of data sets, including single-gene data sets, the highly curated human chromosome 22 predictions, and entire genome predictions from ENSEMBL. Results indicate that SGP2 outperforms purely ab initio gene prediction methods. Results also indicate that SGP2 works about as well with 3x shotgun data as it does with fully assembled genomes. SGP2 provides a high enough specificity that its predictions can be experimentally verified at a reasonable cost. SGP2 was used to generate a complete set of gene predictions on both the human and mouse by comparing the genomes of these two species. Our results suggest that another few thousand human and mouse genes currently not in ENSEMBL are worth verifying experimentally.