Nonverbal Social Sensing: What Social Sensing Can and Cannot Do for the Study of Nonverbal Behavior From Video

The study of nonverbal behavior (NVB), and in particular kinesics (i.e., face and body motions), is typically seen as cost-intensive. However, the development of new technologies (e.g., ubiquitous sensing, computer vision, and algorithms) and approaches to study social behavior [i.e., social signal processing (SSP)] makes it possible to train algorithms to automatically code NVB, from action/motion units to inferences. Nonverbal social sensing refers to the use of these technologies and approaches for the study of kinesics based on video recordings. Nonverbal social sensing appears as an inspiring and encouraging approach to study NVB at reduced costs, making it a more attractive research field. However, does this promise hold? After presenting what nonverbal social sensing is and can do, we discussed the key challenges that researchers face when using nonverbal social sensing on video data. Although nonverbal social sensing is a promising tool, researchers need to be aware of the fact that algorithms might be as biased as humans when extracting NVB or that the automated NVB coding might remain context-dependent. We provided study examples to discuss these challenges and point to potential solutions

Mobile 3D Visualization Techniques in Field Geology Education

Despite the fact that we are in the mobile computing age, student geologists still carry out geological fieldwork using centuries old tools and techniques. This thesis investigates the question “how can 3D visualization on smartphones and tablets help students learn during geological fieldwork?” To answer this question, the thesis first reviews the types of difficulty encountered by novice geologists, narrowing it down to one particular issue: the extrapolation of 2D geological features into the 3D real world. The tasks carried out by novice geologists during introductory fieldwork were analysed systemically. This thesis then explored how apps from Android and iOS app stores may be used in the field to carry out such tasks. The overall finding is that there is limited work focused on novice geologists' difficulties during fieldwork, particularly 2D to 3D extrapolation. Then, using a perception test, the options of representing a single strike and dip measurement in a 3D environment is explored. The results of the test was that there were more accurate methods to represent a measurement than a traditional symbol (e.g. a T-shape). Then, a hypothesis was evaluated which states that instead of using 2D geological maps alone, a 3D visualization of strike and dip measurements plotted on them can assist students in understanding geological structures. The thesis then outlines functionality of a prototype that can be used by higher education institutions as a foundation for a novice geologists' field app. Key findings of the present work are: there has been no apps developed with focus on issues faced by novice geologists doing fieldwork during the time of this study. There was only British Geological Survey's iGeology3D which was released at the time of the study which focused on 3D visualization of geological data to be used in the field. In a separate study an iPad2 was found to be accurate enough for taking strike and dip measurements. In a perception experiment a 3D visualization of strike and dip was deemed to be better for comprehending structural orientation of outcrops but found to be no better than other 2D shapes. Finally, an experiment comparing the use of 2D maps versus 2D maps overlaid with 3D visualization of structural data, the latter found to be more effective for structural interpretation by novice geologists

Agora : unified framework for crowd simulation research

Crowd simulation focuses on modeling the movements and behaviors of large groups of people. This area of study has become increasingly important because of its several applications in various fields such as urban planning, safety, and entertainment. In each of these domains, the presence of virtual agents exhibiting realistic behavior greatly enhances the quality of the simulations. However, the inherently multifaceted and intricate nature of human behavior presents a unique challenge, necessitating the effective combination of multiple behavior models. This thesis introduces a novel theoretical framework for modeling human behavior in crowd simulations, addressing the unresolved issue of combining a plethora of behavior models, often developed in isolation. The proposed framework decomposes human behavior into fundamental driving stimuli, which are then represented graphically through the heatmap paradigm. Subsequently, the agent behavior is influenced by the heatmaps, which guide them toward attractive areas and steer them away from repulsive locations based on the encoded stimuli. A key advantage of this approach lies in the ability to combine heatmaps using well-defined color operations, effectively integrating different aspects of human behavior. Furthermore, the heatmap paradigm facilitates objective comparison of simulation output with real-world data, employing image similarity metrics to evaluate model accuracy. To realize this framework, the thesis presents a modular software architecture designed to support various tasks involved in crowd simulation, emphasizing the separation of concerns for each task. This architecture comprises a collection of abstract modules, which are subsequently implemented using appropriate software components to realize the underlying features, resulting in the Agora framework. To assess the ability of Agora to support the various tasks involved in crowd simulation, two case studies are implemented and analyzed. The first case study simulates tourists visiting Þingvellir national park in Iceland, examining how their behavior is influenced by the visibility of the surrounding environment. The second case study employs Agora to model the thermal and density comfort levels of virtual pedestrians in an urban setting. The results demonstrate that Agora successfully supports the development, combination, and evaluation of crowd simulation models against real-world data. The authoring process, assisted by Agora, is significantly more streamlined compared to its native counterpart. The integration of multiple models is achieved by combining the heatmaps, resulting in plausible behavior, and the model assessment is made convenient through the evaluator within the framework. The thesis concludes by discussing the implications of these findings for the field of crowd simulation, highlighting the contributions and potential future directions of the Agora framework.Mannfjöldahermun fæst við gerð líkana af hreyfingu og hegðun stórra hópa af fólki. Mikilvægi þessa rannsóknasviðs hefur vaxið stöðugt vegna hagnýtingar á margvíslegum vetvangi, eins og til dæmis á vetvangi borgarskipulags, öryggis og afþreyingar. Þegar sýndarmenni hegða sér á sannfærandi hátt, leiðir það til betri hermunar fyrir þessi notkunarsvið. En mannleg hegðun er í eðli sínu margbrotin og flókin og því er það sérstök áskorun við smíði sýndarmenna að sameina, með áhrifaríkum hætti, mörg mismunandi hegðunarlíkön. Þessi ritgerð kynnir nýja fræðilega umgjörð líkanasmíði mannlegrar hegðunar fyrir mannfjöldahermun, sem tekur á þeim óleysta vanda að sameina fjölda hegðunarlíkana, sem oft eru þróuð með aðskildum hætti. Umgjörðin brýtur mannlega hegðun niður í grundvallar drifáreiti, sem eru sett fram grafískt útfrá hugmyndafræði hitakorta. Sýndarmennin hegða sér síðan undir áhrifum frá hitakortunum, sem vísa þeim í áttina að aðlaðandi svæðum og stýra þeim burt frá fráhrindandi svæðum, útfrá hinu umritaða áreiti. Lykilkostur þessarar nálgunar er sá eiginleiki að geta blandað saman hitakortum með vel skilgreindum litaaðgerðum, sem eru þá í raun samþætting mismunandi hliða mannlegrar hegðunar. Hitakortshugmyndafræðin auðveldar ennfremur hlutlægan samanburð hermunarúttaks og raungagna með notkun myndsamanburðarmælinga, til að meta nákvæmni líkana. Varðandi útfærslu, þá kynnir þessi ritgerð einingadrifna hugbúnaðarhögun sem er hönnuð til að styðja við ýmsa ferla mannfjöldahermunar, með áherslu á aðskilnað helstu viðfangsefna hvers ferlis. Þessi högun inniheldur safn huglægra eininga, sem síðan eru útfærðar með viðeigandi hugbúnaðarhlutum, sem raungera undirliggjandi eiginleika. Útkoman er sjálf Agora umbjörðin. Tvö sýnidæmi eru útfærð og greind til að meta getu Agoru til að styðja við ýmis mannfjöldahermunarverkefni. Fyrra dæmið hermir eftir ferðamönnum sem heimsækja Þingvallaþjóðgarð, og skoðar hvernig hegðun þeirra verður fyrir áhrifum sýnileika umhverfisins sem umleikur þá. Seinna dæmið nýtir Agoru til að smíða líkan af hitauppstreymis- og þéttleikaþægindum hjá sýndarvegfarendum í borgarumhverfi. Niðurstöðurnar sýna góðan árangur Agoru við að styðja þróun, samþættingu og mat mannfjöldahermunarlíkana gagnvart raungögnum. Þróunarferlið er verulega þjálla með Agoru en með hefðbundnum aðferðum. Samþætting margra líkana tókst með blöndun hitakorta, möguleg hegðun var framkölluð og mat á líkönunum varð þægilegra með umgjörðinni. Ritgerðinni lýkur með því að fjalla um áhrif þessara niðurstaðna á svið mannfjöldahegðunar, með áherslu á nýstálegt framlag þessarar rannsóknar og mögulega framtíðarþróun Agora umgjarðarinnar

Skeletonization methods for image and volume inpainting

Image and shape restoration techniques are increasingly important in computer graphics. Many types of restoration techniques have been proposed in the 2D image-processing and according to our knowledge only one to volumetric data. Well-known examples of such techniques include digital inpainting, denoising, and morphological gap filling. However efficient and effective, such methods have several limitations with respect to the shape, size, distribution, and nature of the defects they can find and eliminate. We start by studying the use of 2D skeletons for the restoration of two-dimensional images. To this end, we show that skeletons are useful and efficient for volumetric data reconstruction. To explore our hypothesis in the 3D case, we first overview the existing state-of-the-art in 3D skeletonization methods, and conclude that no such method provides us with the features required by efficient and effective practical usage. We next propose a novel method for 3D skeletonization, and show how it complies with our desired quality requirements, which makes it thereby suitable for volumetric data reconstruction context. The joint results of our study show that skeletons are indeed effective tools to design a variety of shape restoration methods. Separately, our results show that suitable algorithms and implementations can be conceived to yield high end-to-end performance and quality of skeleton-based restoration methods. Finally, our practical applications can generate competitive results when compared to application areas such as digital hair removal and wire artifact removal

Women in Artificial intelligence (AI)

This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI

Habitus colaborativo Laboral

Grosso modo, el habitus colaborativo supone una serie de disposiciones heredadas y aprendidas con respecto a estilos de liderazgo, modos de dirección, motivación y emprendimiento, así como innovación y productividad. Empero, el factor del compromiso laboral, reportado como determinante del desempeño, ha sido soslayado por los estudios en virtud de que se trata de un tipo de actitud muy similar al habitus pero distinta en cuanto a la construcción de un proceso institucional. El objetivo del presente trabajo fue dilucidar las narrativas y los discursos en torno a; 1) la formación de una red colaborativa, 2) la producción del conocimiento y 3) el clima de relaciones conflictivas. Se llevó a cabo un estudio comprensivo-interpretativo, transversal y exploratorio con una selección intencional de practicantes profesionales. Los significados en torno a las categorías y dimensiones resaltan el liderazgo como gestor del conocimiento, pero se advierten líneas investigativas que especificarían las diferencias institucionales entre producción y reproducción del conocimiento