Unsupervised Neural Network Quantifies the Cost of Visual Information Processing

information processingneural networksdecision makingflowersvisionvisual signalsgrayscalecognitionUntrained, “flower-naïve” bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees’ unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators’ cognitive constraints.Orbán, L.L., & Chartier, S. (2015). Unsupervised Neural Network Quantifies the Cost of Visual Information Processing. PLoS One, 10(7), e0132218. doi: 10.1371/journal.pone.0132218Peer reviewe

Visual choice behaviour by bumblebees (Bombus impatiens) confirms unsupervised neural network's predictions

bumblebeessymmetryvisual preferencesneural networksunlearned behaviorThe behavioral experiment herein tests the computational load hypothesis generated by an unsupervised neural network to examine bumblebee (Bombus impatiens) behavior at 2 visual properties: spatial frequency and symmetry. Untrained “flower-naïve” bumblebees were hypothesized to prefer symmetry only when the spatial frequency of artificial flowers is high and therefore places great information-processing demands on the bumblebees’ visual system. Bumblebee choice behavior was recorded using high-definition motion-sensitive camcorders. The results support the computational model’s prediction: 1-axis symmetry influenced bumblebees’ preference behavior at low and high spatial frequency patterns. Additionally, increasing the level of symmetry from 1 axis to 4 axes amplified preference toward the symmetric patterns of both low and high spatial frequency patterns. The results are discussed in the context of the artificial neural network model and other hypotheses generated from the behavioral literature.Orbán, L.L., Plowright, C.M.S., Chartier, S., Thompson, E., & Xu, V. (2015). Visual choice behaviour by bumblebees (Bombus impatiens) confirms unsupervised neural network's predictions. Journal of Comparative Psychology, 129(3), 229 - 236. doi: 10.3791/52033We are grateful for Charles Collins’ help with producing the experimental stimuli and are grateful to Michael Richards for helping with constructing MySQL queries. We also thank Emily Sibbald and Amandeep Bassi for their helpful comments on the manuscript, Kinga Orbán for help with data analysis, and Koppert Canada for their bumblebee colony donations. Research grants to Catherine M. S. Plowright and Sylvain Chartier from the Natural Sciences and Engineering Research Council of Canada supported this work.Peer revieweddoi: 10.3791/5203

Getting to the Start Line: How Bumblebees and Honeybees are Visually Guided towards their First Floral Contact

visual recognitionbumblebeeshoneybeesinnateunlearned behaviourflower-naiveOrbán, L. L. & Plowright, C. M. S. (2014). Getting to the start line: How bumblebees and honeybees are visually guided towards their first floral contact. Insectes Sociaux, 61, 325-336. doi:10.1007/s00040-014-0366-2Peer reviewedMust link to publisher version. http://link.springer.com/article/10.1007/s00040-014-0366-

Assessing remote sensing application on rangeland insurance in Canadian prairies

Part of the problem with implementing a rangeland insurance program is that the acreage of different pasture types, which is required in order to determine an indemnity payment, is difficult to measure on the ground over large areas. Remote sensing techniques provide a potential solution to this problem. This study applied single-date SPOT (Satellite Pour I’Observation de la Terre) imagery, field collected data, and geographic information system (GIS) data to study the classification of land cover and vegetation at species level. Two topographic correction models, Minnaert model and C-correction, and two classifying algorithms, maximum likelihood classifier (MLC) and artificial neural network (ANN), were evaluated. The feasibility of discriminating invasive crested wheatgrass from natives was investigated, and an exponential normalized difference vegetation index (ExpNDMI) was developed to increase the separability between crested wheatgrass and natives. Spectral separability index (SSI) was used to select proper bands and vegetation indices for classification. The results show that topographic corrections can be effective to reduce intra-class rediometric variation caused by topographic effect in the study area and improve the classification. An overall accuracy of 90.5% was obtained by MLC using Minnaert model corrected reflectance, and MLC obtained higher classification accuracy (~5%) than back-propagation based ANN. Topographic correction can reduce intra-class variation and improve classification accuracy at about 4% comparing to the original reflectance. The crested wheatgrass was over-estimated in this study, and the result indicated that single-date SPOT 5 image could not classify crested wheatgrass with satisfactory accuracy. However, the proposed ExpNDMI can reduce intra-class variation and enlarge inter-class variation, further, improve the ability to discriminate invasive crested wheatgrass from natives at 4% of overall accuracy. This study revealed that single-date SPOT image may perform an effective classification on land cover, and will provide a useful tool to update the land cover information in order to implement a rangeland insurance program

A chemometric approach to investigating South African wine behaviour using chemical and sensory markers

Thesis (PhDAgric)--Stellenbosch University, 2021.ENGLISH ABSTRACT: The aim of this dissertation was to demonstrate the value of comprehensive narratives and elucidate critical steps in data handling in Oenology, while highlighting some common misconceptions and misinterpretations related to the process. This compilation was a journey through different stages of dealing with oenological data, with increasing complexity in both the strategies and the techniques used (sensory, chemistry, and statistics). To achieve this aim, different strategies and multivariate tools were used under two prime objectives. Firstly, several multivariate descriptive approaches were used to investigate two oenological problems and lay out the contextual foundations for the statistics-focused work (Chapters 3 and 5). Secondly, in increasing levels of complexity, statistical strategies of constructing comprehensive data fusion as well as pattern recognition models were investigated (Chapters 4 and 6). A comprehensive literature review (Chapter 2) examined and addressed common misconceptions in the different stages of data handling Oenology. The first oenological problem, described in Chapter 3, investigated the evolution of the sensory perception of aroma, as well as the antioxidant-related parameters and volatile compound composition of Sauvignon Blanc and Chenin Blanc wines stored under different conditions and durations. The study applied an appropriate sensory method for this research question, namely, Pivot©Profiling. The study was able to show the evolution of Sauvignon Blanc from ‘fruity’ and ‘herbaceous’ and of Chenin Blanc from ‘fruity’ and ‘tropical’ both towards ‘toasted’, ‘oak’, and ‘honey’ attributes. Chemically, the volatile composition did not show any trends. However, wines stored at higher temperatures for longer periods had relatively higher UV-Vis absorbance, colour density as well as higher b* (yellow) values and lower clarity in terms of L* index, compared to the control. The second oenological problem, described in Chapter 5, investigated the typicality of South African old vine Chenin Blanc perceptually and conceptually using a typicality rating and a flexible sorting task. The sensory methodology followed published strategies for investigating typicality. This study did not find a unique sensory space of the old vine Chenin Blanc due to a lack of perceptual consensus among the industry professionals for the wines included in the study. However, it did find that the industry professionals had unified ideas about the attributes of an ideal old vine Chenin Blanc wine. The first of the statistics-focused studies, described in Chapter 4, explored data fusion at low and mid-level using principal component analysis - PCA (low and mid-level) and multiple factor analysis - MFA (mid-level). The study looked at data pre-processing and matrix compatibility, which are important data handling stages for data fusion. Like the contextual chapters (Chapter 3 and 5), and keeping with the aim of this compilation, this chapter gave a detailed descriptive narrative of the data handling. Through detailed examination of the process, the study found that MFA was the most appropriate data fusion strategy. The second statistics-focused study, described in Chapter 6, continued to exploit the multiple advantages of multiblock approach of MFA. Additionally, this chapter showed the reliability of fuzzy k-means clustering compared to agglomerative hierarchical clustering (AHC).AFRIKAANSE OPSOMMING: Die doel van hierdie proefskrif was om die waarde van omvattende vertellings te demonstreer en om kritiese stappe in die hantering van data in die wynkunde toe te lig, terwyl enkele algemene wanopvattings en verkeerde interpretasies in verband met die proses uitgelig word. Hierdie samestelling was 'n reis deur verskillende stadiums van die hantering van wynkundige data, met toenemende kompleksiteit in beide die strategieë en die gebruikte tegnieke (sensoriese, chemie en statistieke). Om hierdie doel te bereik, is verskillende strategieë en meerveranderlike instrumente onder twee hoofdoelstellings gebruik. Eerstens is verskeie multivariate beskrywingsbenaderings gebruik om twee oenologiese probleme te ondersoek en die kontekstuele grondslae vir die statistiekgerigte werk uit te lê (hoofstukke 3 en 5). Tweedens, in toenemende vlakke van kompleksiteit, is statistiese strategieë vir die konstruering van omvattende datafusie sowel as patroonherkenningsmodelle ondersoek (hoofstukke 4 en 6). 'N Omvattende literatuuroorsig (hoofstuk 2) het algemene misverstande in die verskillende stadiums van datahantering van wynkunde ondersoek en behandel. Die eerste wynprobleem, wat in hoofstuk 3 beskryf word, het die evolusie van die sintuiglike waarneming van aroma ondersoek, asook die antioksidant-verwante parameters en die vlugtige samestelling van Sauvignon Blanc- en Chenin Blanc-wyne wat onder verskillende toestande en duur gestoor is. Die studie het 'n toepaslike sensoriese metode vir hierdie navorsingsvraag toegepas, naamlik Pivot©Profiling. Die studie kon die evolusie van Sauvignon Blanc van 'vrugtige' en 'kruidagtige' en van Chenin Blanc van 'vrugtige' en 'tropiese' sowel as 'geroosterde', 'eikehout' en 'heuning'-eienskappe aantoon. Chemies het die vlugtige samestelling geen neigings getoon nie. Wyne wat vir langer tydperke by hoër temperature gestoor is, het egter relatief hoër UV-Vis- absorbansie, kleurdigtheid sowel as hoër b * (geel) waardes en laer helderheid in terme van L * - indeks, vergeleke met die kontrole. Die tweede wynprobleem, wat in hoofstuk 5 beskryf word, het die tipiesheid van die Suid- Afrikaanse ou wingerdstok Chenin Blanc perseptueel en konseptueel ondersoek met behulp van 'n tipiese klassifikasie en 'n buigsame sorteertaak. Die sensoriese metodologie het gepubliseerde strategieë vir die ondersoek na tipiesheid gevolg. Hierdie studie het nie 'n unieke sensoriese ruimte vir die ou wingerdstok Chenin Blanc gevind nie, omdat daar 'n gebrek aan konseptuele konsensus tussen die professionele persone vir die wyne wat in die studie opgeneem is, was. Dit het egter gevind dat professionele persone in die bedryf eenvormige idees gehad het oor die eienskappe van 'n ideale ou wynstok Chenin Blanc-wyn. Die eerste van die statistiekgerigte studies, wat in hoofstuk 4 beskryf word, het datafusie op lae en middelvlak ondersoek met hoofkomponentanalise - PCA (lae en middelvlak) en meervoudige faktorontleding - MFA (middelvlak). Die studie het gekyk na die voorverwerking van data en matriksversoenbaarheid, wat belangrike stadiums vir die hantering van data is vir die versmelting van data. Net soos die kontekstuele hoofstukke (Hoofstuk 3 en 5), en in ooreenstemming met die doel van hierdie samestelling, het hierdie hoofstuk 'n gedetailleerde beskrywende vertelling van die datahantering gegee. Deur middel van 'n uitvoerige ondersoek van die proses, het die studie bevind dat MFA die mees geskikte strategie vir data-fusie was. Die tweede statistiekgerigte studie, wat in hoofstuk 6 beskryf word, het voortgegaan om die veelvuldige voordele van multiblokke benadering van MFA te benut. Verder het hierdie hoofstuk die betroubaarheid van fuzzy k-middelgroepering vergeleke met agglomeratiewe hiërargiese groepering (AHC) getoon.Doctora

Impacts des polluants métalliques sur l'abeille : de la colonie au cerveau

Les abeilles sont des pollinisateurs essentiels. Une pléthore de facteurs de stress environnementaux, tels que les produits agrochimiques, a été identifiée comme contribuant à leur déclin mondial. En particulier, ces facteurs de stress altèrent les processus cognitifs impliqués dans les comportements fondamentaux. Jusqu'à présent, cependant, on ne sait pratiquement rien de l'impact de l'exposition à des métaux lourds, dont la toxicité est avérée chez de nombreux organismes. Pourtant, leurs émissions mondiales résultant des activités humaines ont élevé leurs concentrations bien au-dessus des niveaux naturels dans l'air, le sol, l'eau et la flore, exposant ainsi les abeilles à tous les stades de leur vie. Le but de ma thèse était d'examiner les effets de la pollution métallique sur l'abeille domestique en utilisant une approche multi-échelle, du cerveau à la colonie, en laboratoire et sur le terrain. J'ai d'abord observé que les abeilles exposées à une gamme de concentrations de trois métaux communs (arsenic, plomb et zinc) en laboratoire étaient incapables de percevoir et éviter des concentrations usuelles, néanmoins nocives, de ces métaux dans leur nourriture. J'ai ensuite exposé de façon chronique des colonies à des concentrations réalistes de plomb dans la nourriture et démontré que la consommation de ce métal altérait la cognition et le développement morphologique des abeilles. Comme les polluants métalliques se trouvent souvent dans des mélanges complexes dans l'environnement, j'ai exploré l'effet des cocktails de métaux, montrant que l'exposition au plomb, à l'arsenic ou au cuivre seul était suffisante pour ralentir l'apprentissage et perturber le rappel de la mémoire, et que les combinaisons de ces métaux induisaient des effets négatifs additifs sur ces deux processus cognitifs. J'ai finalement étudié l'impact de l'exposition naturelle aux polluants métalliques dans un environnement contaminé, en collectant des abeilles à proximité d'une ancienne mine d'or, et montré que les individus des populations les plus exposées aux métaux présentaient des capacités d'apprentissage et de mémoire plus faibles, et des altérations de leur développement conduisant à une réduction de la taille de leur cerveau. Une analyse plus systématique des abeilles non exposées a révélé une relation entre la taille de la tête, la morphométrie du cerveau et les performances d'apprentissage dans différentes tâches comportementales, suggérant que l'exposition aux polluants métalliques amplifie ces variations naturelles. Ainsi, mes résultats suggèrent que les abeilles domestiques sont incapables d'éviter l'exposition à des concentrations réalistes de métaux qui sont préjudiciables au développement et aux fonctions cognitives, et appellent à une révision des niveaux environnementaux considérés comme "sûrs". Ma thèse est la première analyse intégrée de l'impact de plusieurs polluants métalliques sur la cognition, la morphologie et l'organisation cérébrale chez l'abeille, et vise à encourager de nouvelles études sur la contribution de la pollution métallique dans le déclin signalé des abeilles, et plus généralement, des insectes.Honey bees are crucial pollinators. A plethora of environmental stressors, such as agrochemicals, have been identified as contributors to their global decline. Especially, these stressors impair cognitive processes involved in fundamental behaviours. So far however, virtually nothing is known about the impact of metal pollutants, despite their known toxicity to many organisms. Their worldwide emissions resulting from human activities have elevated their concentrations far above natural baselines in the air, soil, water and flora, exposing bees at all life stages. The aim of my thesis was to examine the effects of metallic pollution on honey bees using a multiscale approach, from brain to colonies, in laboratory and field conditions. I first observed that bees exposed to a range of concentrations of three common metals (arsenic, lead and zinc) in the laboratory were unable to perceive and avoid, low, yet harmful, field-realistic concentrations of those metals in their food. I then chronically exposed colonies to field-realistic concentrations of lead in food and demonstrated that consumption of this metal impaired bee cognition and morphological development, leading to smaller adult bees. As metal pollutants are often found in complex mixtures in the environment, I explored the effect of cocktails of metals, showing that exposure to lead, arsenic or copper alone was sufficient to slow down learning and disrupt memory retrieval, and that combinations of these metals induced additive negative effects on both cognitive processes. I finally investigated the impact of natural exposure to metal pollutants in a contaminated environment, by collecting bees in the vicinity of a former gold mine, and showed that individuals from populations most exposed to metals exhibited lower learning and memory abilities, and development impairments conducing to reduced brain size. A more systematic analysis of unexposed bees revealed a relationship between head size, brain morphometrics and learning performances in different behavioural tasks, suggesting that exposure to metal pollutants magnifies these natural variations. Hence, altogether, my results suggest that honey bees are unable to avoid exposure to field-realistic concentrations of metals that are detrimental to development and cognitive functions; and call for a revision of the environmental levels considered as 'safe'. My thesis is the first integrated analysis of the impact of several metal pollutants on bee cognition, morphology and brain structure, and should encourage further studies on the contribution of metal pollution in the reported decline of honey bees, and more generally, of insects

What If ChatGPT Wrote It? A Research On Consumers Perception

openThis research thesis can be divided in two parts, the first part (chapter 1, chapter 2 and chapter 3) focuses on the literature, while the second part (chapter 4) sees the unravelling of the research, starting from the research question and the methodology, and ending with the research itself and its results. Chapter 1, simply called “Artificial Intelligence”, starts with a series of definitions in order to set the ground for the subsequent chapters. Following, the history of AI is recalled from the 1950s till today, and finally I list the risks and bring real-life examples of the benefits of this technology. Chapter 2, “Artificial Intelligence in Marketing”, starts with a recollection of academic studies concerning AI marketing divided into four subjects (1) technical AI algorithms for solving specific marketing problems, (2) customer’s psychological reactions to AI, (3) effects of AI on jobs and society and (4) managerial and strategic issues related to AI, focusing on the last one in particular (Huang & Rust 2020). Then it shows through reports and case studies how companies are implementing AI in their marketing strategies. The chapter closes considering the benefits and the risks of using AI for marketing reasons and finally how consumers perceive it. Chapter 3 builds the foundations for the research, focusing on one of the most discussed AI tools, ChatGPT. It explains what kind of artificial intelligence it is, referencing also how OpenAI has improved its algorithm over time, but also its pervasive adoption and media coverage. Then I rely on Sohail’s (2023) taxonomy to explain the possible applications of ChatGPT in different fields – medicine, marketing, finance, software engineering, academic writing, education, environmental science, natural language processing and tourism. I focus on how marketers are in fact using it now, explaining the best practices to benefit the most from its use. Lastly, I consider its risks and limitations, like biases, hallucinations, inaccuracies, and ethical dilemmas. The last chapter is dedicated to the research, where I delve into the specific use of ChatGPT for writing copy and the perception of people towards it. To answer the research question « Does the perception of the copy changes when potential customers know that it has been written by ChatGPT? » I chose a well-known brand – IKEA –, rewrote the written content of a post using ChatGPT and surveyed 115 people on their perception of the copy. Even though the sample is not representative of the Italian population aged between 20 and 35, my analysis shows that there are in fact some statistical differences on the perception between those who knew and those who didn’t know that I used an artificial intelligence to write the promotional content

Computer-Aided Biomimetics : Semi-Open Relation Extraction from scientific biological texts

Engineering inspired by biology – recently termed biom* – has led to various groundbreaking technological developments. Example areas of application include aerospace engineering and robotics. However, biom* is not always successful and only sporadically applied in industry. The reason is that a systematic approach to biom* remains at large, despite the existence of a plethora of methods and design tools. In recent years computational tools have been proposed as well, which can potentially support a systematic integration of relevant biological knowledge during biom*. However, these so-called Computer-Aided Biom* (CAB) tools have not been able to fill all the gaps in the biom* process. This thesis investigates why existing CAB tools fail, proposes a novel approach – based on Information Extraction – and develops a proof-of-concept for a CAB tool that does enable a systematic approach to biom*. Key contributions include: 1) a disquisition of existing tools guides the selection of a strategy for systematic CAB, 2) a dataset of 1,500 manually-annotated sentences, 3) a novel Information Extraction approach that combines the outputs from a supervised Relation Extraction system and an existing Open Information Extraction system. The implemented exploratory approach indicates that it is possible to extract a focused selection of relations from scientific texts with reasonable accuracy, without imposing limitations on the types of information extracted. Furthermore, the tool developed in this thesis is shown to i) speed up a trade-off analysis by domain-experts, and ii) also improve the access to biology information for nonexperts

Computer-aided biomimetics : semi-open relation extraction from scientific biological texts

Engineering inspired by biology – recently termed biom* – has led to various ground-breaking technological developments. Example areas of application include aerospace engineering and robotics. However, biom* is not always successful and only sporadically applied in industry. The reason is that a systematic approach to biom* remains at large, despite the existence of a plethora of methods and design tools. In recent years computational tools have been proposed as well, which can potentially support a systematic integration of relevant biological knowledge during biom*. However, these so-called Computer-Aided Biom* (CAB) tools have not been able to fill all the gaps in the biom* process. This thesis investigates why existing CAB tools fail, proposes a novel approach – based on Information Extraction – and develops a proof-of-concept for a CAB tool that does enable a systematic approach to biom*. Key contributions include: 1) a disquisition of existing tools guides the selection of a strategy for systematic CAB, 2) a dataset of 1,500 manually-annotated sentences, 3) a novel Information Extraction approach that combines the outputs from a supervised Relation Extraction system and an existing Open Information Extraction system. The implemented exploratory approach indicates that it is possible to extract a focused selection of relations from scientific texts with reasonable accuracy, without imposing limitations on the types of information extracted. Furthermore, the tool developed in this thesis is shown to i) speed up a trade-off analysis by domain-experts, and ii) also improve the access to biology information for non-exper

Desentrañando los intricados patrones de variación en el complejo diploid-poliploide complex Veronica subsect. Pentasepalae Benth. (Veronica L., Plantaginaceae sensu APG IV). Relación con las variaciones climáticas del periodo cuaternario

Tesis por compendio de publicaciones[ES]La poliploidía y la hibridación serán los leitmotive de los capítulos que componen esta Tesis Doctoral, cuyo objetivo principal es contribuir al entendimiento de la historia evolutiva y las relaciones entre las entidades que forman parte del complejo diploide-poliploide Veronica subsección Pentasepalae Benth