Synthetic Characters Research Articles

Studies on the Limestone Vegetation of Sahasradhara near Dehradun (U. P.)-3. Phytosociological Studies: Synthetic Characters of Vegetation

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Shimpai Muyou: Confronting Child Suicides in Japan through a Serious Game & School-based Intervention

School bullying is responsible for a large number of child suicides in Japan. Serious games have proved to be effective and highly motivational educational tools capable of increasing awareness, changing behaviour, reduce risk factors and even improving protective skills. This paper presents a novel approach of using both participatory design and gameplay to sensitize children (aged 7–12​ years old) on bullying victimization. Action research strategy is used with intentions to improve the quality of school life in Japan through the use of a serious game called Shimpai Muyou. What makes it stand out from the rest of the crowd is that the entire intervention was design, developed and evaluated through partnering with children in a school setting. The research is largely qualitative and exploratory in nature, stemmed from interdisciplinary core ideas related to technology, education, psychology and interactive theatre. Findings from both formative and summative evaluations indicated that child-users empathically engaged with the synthetic characters, attributing a range of emotions to their actions e.g., empathy, compassion, sadness, anger etc., tackling ethical dilemmas and bullying situations with confidence. From these results, we can conclude that Shimpai Muyou is a useful and engaging school-based anti-bullying intervention.

Dynamic metabolic and transcriptomic profiling reveal synthetic characters and regulators of flavonoid biosynthesis in Camellia oleifera seeds

Flavonoids are natural bioactive substances with beneficial health effects against chronic diseases. Camellia oleifera Abel. ( C. oleifera ) has attracted attention because its seeds contain high levels of unsaturated fatty acids . Actually, flavonoids are also abundant in the C. oleifera seeds. However, the composition and distribution of flavonoid and overall molecular mechanism of flavonoid biosynthesis in the C. oleifera seeds have not been fully uncovered. To this end, metabolome , transcriptome , high-performance liquid chromatography, microscopic, and exogenous methyl jasmonate treatment analyses of C. oleifera seeds at different developmental stages were performed. Results revealed that the differential metabolites and genes were enriched in the flavonoid biosynthesis pathways in C. oleifera seeds. Flavonoid profiles presented dynamic patterns that changed with seed development, consistent with the pattern of gene regulation in the corresponding pathways. In total, 52 differentially accumulated flavonoids and 124 differentially expressed structural genes involved in flavonoid biosynthesis were identified. After weighted gene co-expression network analysis, three modules were highly interrelated with the accumulation of flavonoid components. The co-expression networks of these three modules were used to identify key candidate transcription factors associated with flavonoid biosynthesis, such as MYC2 , bHLH3 , bHLH18 , MYB44 , MYB86 , WRKY26 , and WRKY32 . Based on these differentially accumulated flavonoids and key genes, the genetic and metabolic regulatory networks of flavonoid biosynthesis was proposed. Moreover, exogenous methyl jasmonate influenced the accumulation of diverse flavonoids in C . oleifera seeds. Potential regulatory factors identified in this study will contribute to the provision of molecular traces for in-depth research on flavonoid biosynthesis and product development for C. oleifera with higher value. • In total, 148 flavonoids were identified in Camellia oleifera seeds. • Differentially expressed genes were enriched in the flavonoid biosynthesis pathways. • Seven key transcription factors related to flavonoid biosynthesis were screened. • A model was proposed in which flavonoid biosynthesis is induced by methyl jasmonate.

From Synthetic Characters to Virtual Actors

We discuss the extension of an emotionally-driven agent architecture already applied to the creation of emergent narratives. Synthetic characters are enhanced to perform as actors by carrying out a second cognitive appraisal, based on the OCC model, of the emotional impact of their projected actions before execution.

An Abstraction Framework for Cooperation Among Agents and People in a Virtual World

With increasing sophistication in modeling interpersonal interactions, including cultural and social factors, it is now possible and desirable to bring together state-of-the-art human behavior models (HBMs) developed through different approaches in a framework that facilitates interoperability, composability, and comparison. Such a framework is needed in order for game or simulation environments to allow heterogeneous agents (synthetic characters driven by HBMs) to interact with each other and to interact with human players, even though their information needs and operating premises may differ. An important part of such an interoperability framework is an agent message system supporting multiple levels of abstraction. To demonstrate the viability of such a framework, we created an environment that supported synthetic characters interacting with each other and a human player in a common scenario. The agents were provided by different researchers built upon different technical approaches, yet were able to communicate through messages featuring multiple levels of abstraction to describe actions and events. In this paper, we describe our choices of message abstraction levels, what we developed, and the architecture of the framework that we used to mediate the interaction among all the participants, synthetic and human.

A Believable Agent for First-Person Shooter Games

In this paper, we present a principled approach to constructing believable game players that relies on a cognitive architecture. The resulting agent is capable of playing the game \uc/ in a plausible manner when faced with similar situations as its human counterparts. We discuss how architectural features like goal-directed but reactive execution and incremental learning can produce more believable synthetic characters.

Sequence Learning by Backward Chaining in Synthetic Characters

Many learning algorithms concern themselves with learning from large amounts of data without human interaction. Synthetic characters that interact with human beings present a wholly different problem: they must learn quickly from few examples provided by a non-expert teacher. Training must be intuitive, provide feedback, and still allow training of nontrivial new behaviours. We present a learning mechanism that allows an autonomous synthetic character to learn sequences of actions from natural interaction with a human trainer. The synthetic character learns from only a handful of training examples, in a realtime and complex environment. Building on an existing framework for training a virtual dog to perform single actions on command and explore its action and state space, we give the dog the ability to notice consistent reward patterns that follow sequences of actions. Using an approximate online algorithm to check the Markov property for an action, the dog can discover action sequences that reliably predict rewards and turn these sequences into actions, allowing them to be associated with speech commands. This framework leads to a natural and easy training procedure that is a version of Backward Chaining, a technique commonly used by animal trainers to teach sequences of actions.

ElderSim: A Synthetic Data Generation Platform for Human Action Recognition in Eldercare Applications

To train deep learning models for vision-based action recognition of elders’ daily activities, we need large-scale activity datasets acquired under various daily living environments and conditions. However, most public datasets used in human action recognition either differ from or have limited coverage of elders’ activities in many aspects, making it challenging to recognize elders’ daily activities well by only utilizing existing datasets. Recently, such limitations of available datasets have actively been compensated by generating synthetic data from realistic simulation environments and using those data to train deep learning models. In this paper, based on these ideas we develop ElderSim, an action simulation platform that can generate synthetic data on elders’ daily activities. For 55 kinds of frequent daily activities of the elders, ElderSim generates realistic motions of synthetic characters with various adjustable data-generating options and provides different output modalities including RGB videos, two- and three-dimensional skeleton trajectories. We then generate KIST SynADL, a large-scale synthetic dataset of elders’ activities of daily living, from ElderSim and use the data in addition to real datasets to train three state-of-the-art human action recognition models. From the experiments following several newly proposed scenarios that assume different real and synthetic dataset configurations for training, we observe a noticeable performance improvement by augmenting our synthetic data. We also offer guidance with insights for the effective utilization of synthetic data to help recognize elders’ daily activities.

Suppression of Sensorimotor Alpha Power Associated With Pain Expressed by an Avatar: A Preliminary EEG Study.

Several studies using functional magnetic resonance imaging (fMRI) showed that empathic capabilities are associated with the activation (and deactivation) of relatively specific neural circuits. A growing number of electroencephalography studies also suggest that it might be useful to assess empathy. The main goal of this study was to use quantitative electroencephalography (qEEG) to test whether observation of pain expressed by an avatar (virtual reality) induces a suppression of alpha waves over sensorimotor cortical areas, as it is observed with human stimuli. Not only was it the case, but also the magnitude of alpha suppression was correlated with perspective-taking capacity of participants. Both empathy levels and magnitude of sensorimotor alpha suppression (SAS) were significantly higher in women than men. Interestingly, a significant interaction emerged between levels of individual empathy and specificity of experimental instructions, where SAS in participants with good perspective-taking was higher during passive observation of the distressed avatar, while the opposite was true during an active (trying to understand) condition. These results suggest that: (1) synthetic characters are able to elicit SAS; (2) SAS is indeed associated with perspective-taking capacities; (3) Persons with poorer perspective-taking capacities can show significant SAS when proper instructions are provided. Therefore, qEEG represents a low-cost objective approach to measure perspective-taking abilities.

Increasing Valid Profiles in Phallometric Assessment of Sex Offenders with Child Victims: Combining the Strengths of Audio Stimuli and Synthetic Characters.

Penile plethysmography (PPG) is a measure of sexual interests that relies heavily on the stimuli it uses to generate valid results. Ethical considerations surrounding the use of real images in PPG have further limited the content admissible for these stimuli. To palliate this limitation, the current study aimed to combine audio and visual stimuli by incorporating computer-generated characters to create new stimuli capable of accurately classifying sex offenders with child victims, while also increasing the number of valid profiles. Three modalities (audio, visual, and audiovisual) were compared using two groups (15 sex offenders with child victims and 15 non-offenders). Both the new visual and audiovisual stimuli resulted in a 13% increase in the number of valid profiles at 2.5mm, when compared to the standard audio stimuli. Furthermore, the new audiovisual stimuli generated a 34% increase in penile responses. All three modalities were able to discriminate between the two groups by their responses to the adult and child stimuli. Lastly, sexual interest indices for all three modalities could accurately classify participants in their appropriate groups, as demonstrated by ROC curve analysis (i.e., audio AUC=.81, 95% CI [.60, 1.00]; visual AUC=.84, 95% CI [.66, 1.00], and audiovisual AUC=.83, 95% CI [.63, 1.00]). Results suggest that computer-generated characters allow accurate discrimination of sex offenders with child victims and can be added to already validated stimuli to increase the number of valid profiles. The implications of audiovisual stimuli using computer-generated characters and their possible use in PPG evaluations are also discussed.

Hacia la construcción de un dispositivo de asistencia para personas no videntes en el juego de cuarenta

El presente trabajo tiene como objetivo el desarrollo de un sistema de reconocimiento automático de una carta de baraja ubicada sobre una mesa, como parte del proyecto más general de crear un dispositivo para asistir a personas no videntes en el juego de azar denominado “cuarenta”. El objeto de dicho dispositivo será informar al usuario de las cartas en juego, vía audio. Para esta fase del proyecto se utilizó el algoritmo de k-vecinos más cercanos entrenado con un conjunto de caracteres alfanuméricos sintéticos. El conjunto de prueba constó de fotografías tomadas en condiciones controladas de iluminación, con las cartas ubicadas en orientación arbitraria. La parametrización del algoritmo arrojó un valor de 1 como k óptimo, con el cual se obtuvo un error de clasificación en el conjunto de prueba de 5%. Solo dos caracteres fueron confundidos por el clasificador, la “A” y la “J”, con errores de 20% y 40% cada uno. El algoritmo fue implementado en un sistema embebido Raspberry Pi 3, obteniendo un tiempo de respuesta de 5 segundos, incluida la conversión a audio, y una ocupación de memoria RAM que no superó el 60% de la capacidad del sistema. Estos resultados sugieren su aplicabilidad en dispositivos portátiles.

Explainable Agency for Intelligent Autonomous Systems

As intelligent agents become more autonomous, sophisti- cated, and prevalent, it becomes increasingly important that humans interact with them effectively. Machine learning is now used regularly to acquire expertise, but common techniques produce opaque content whose behavior is difficult to interpret. Before they will be trusted by humans, autonomous agents must be able to explain their decisions and the reasoning that produced their choices. We will refer to this general ability as explainable agency. This capacity for explaining decisions is not an academic exercise. When a self-driving vehicle takes an unfamiliar turn, its passenger may desire to know its reasons. When a synthetic ally in a computer game blocks a player’s path, he may want to understand its purpose. When an autonomous military robot has abandoned a high-priority goal to pursue another one, its commander may request justification. As robots, vehicles, and synthetic characters become more selfreliant, people will require that they explain their behaviors on demand. The more impressive these agents’ abilities, the more essential that we be able to understand them.

Phylogenetic Relationships of Nine Cultivars of Strawberries (Fragaria spp.) Based on Anatomical and Morphological Characters

Strawberry cultivation in Indonesia is centred at Citrus and Subtropical Fruit Research Institute, which collects different cultivars of Fragaria spp. Information on classification based on phenotypic characters of Fragaria spp. has not been studied as a whole. The purpose of the present study was to identify and determine phylogenic relationships of nine cultivars of strawberries based on the anatomical and morphological characters. The present study identified morphologically nine strawberry cultivars by referring to the IPGRI (1986) and the UPOV (2012) and Hofer et al . (2012). Anatomical preparations of roots, stems and leaves were made by the embedding method. Phylogenetic relationships were determined using MVSP software with UPGMA algorithm through the Gower General Similarity Coefficient method. Subsequently, the principal components were analyzed using the Euclidian Biplots algorithm depicted in a Scatter plot. Results showed that there were 37 anatomical and morphological characters that play a role in the characterization of nine cultivars (25 synthetic characters and 12 diagnostics characters) where the shape of the fruit and type of attachment of the flowers were the main characters distinguishing among the nine cultivars studied. The phylogenetic relationship produced two clusters with 79% similarity index. The closely related cultivars were Festival and Rosa Linda with a similarity index of 94%, and Earlibrite and Aerut with a similarity index of 86%

Dynamic metabolic and transcriptomic profiling of methyl jasmonate-treated hairy roots reveals synthetic characters and regulators of lignan biosynthesis in Isatis indigotica Fort.

SummaryA molecular description of lignan biosynthesis in Isatis indigotica displaying its synthetic characteristics and regulatory mechanism is of great importance for the improvement of the production of this class of active compounds. To discover the potential key catalytic steps and regulatory genes, I. indigotica hairy roots elicited by methyl jasmonate (MeJA) were used as a source of systematic variation for exploring the metabolic/transcriptional changes and candidate genes that might play key roles in lignan biosynthesis. The reprogramming modulated by MeJA was classified into three distinct phases, referred to as signal responding, transcriptional activation of metabolic pathways and accumulation of metabolites. Candidate genes were pooled according to the three phases and applied to co‐expression network analysis. In total, 17 genes were identified as hub genes. 4CL3 was selected to validate its impact on lignan biosynthesis. RNAi of 4CL3 resulted in a significant reduction in lignan production. Taken together with its catalytic property, a major route of lignan biosynthesis in I. indigotica was highlighted, which was catalysed by 4CL3 via the esterization of caffeic acid. In conclusion, this study provides new insights into lignan biosynthesis as well as potential targets for metabolic engineering in I. indigotica.

3D-Model-Based Video Analysis for Computer Generated Faces Identification

Modern computer graphics technologies brought realism in computer-generated characters, making them achieve truly natural appearance. Besides traditional virtual reality applications such as avatars, games, or cinema, these synthetic characters may be used to generate realistic fakes, which may lead to improper use of the technology. This fact raises the demand for advanced tools able to discriminate real and artificial human faces in digital media. In this paper, we propose a method to distinguish between computer generated and natural faces by modeling and evaluating their dynamic behavior. Because of a 3D-model-based video analysis, the proposed technique allows identifying synthetic characters by detecting their more limited variability over time. Experimental results demonstrate the effectiveness of the proposed approach also on very challenging and realistic video sequences.

An Assessment of Phytosociological Diversity of Kuther Watershed, Himachal Pradesh, India

A plant community acquires many characteristics which are not found in its constituents, (organisms or population). A community is described through species diversity, life forms, structure, dominance and developmental status. To delineate these aspects two significant parameters like analytical characters (quantitative - frequency, density, abundance and cover; qualitative - physiognomy, phenology, sociability, vitality and life form) and synthetic characters (constancy, fidelity and dominance) were studied. The present study focuses on species composition, phytosociological diversity and concentration of dominance of various tree species of Kuther watershed of Himachal Pradesh, India.DOI: http://dx.doi.org/10.3126/ije.v3i4.11732 International Journal of Environment Volume-3, Issue-4, Sep-Nov 2014Page: 74-90

An Agent Model for the Appraisal of Normative Events Based in In-Group and Out-Group Relations

Emotional synthetic characters are able to evaluate (appraise) events as positive or negative with their emotional states being triggered by several factors. Currently, the vast majority of models for appraisal in synthetic characters consider factors related to the goals and preferences of the characters. We argue that appraisals that only take into consideration these "personal" factors are incomplete as other more social factors, such as the normative and the social context, including in-group and out-group relations, should be considered as well. Without them, moral emotions such as shame cannot be appraised, limiting the believability of the characters in certain situations. We present a model for the appraisal of characters' actions that evaluates whether actions by in-group and out-group members which conform, or not, to social norms generate different emotions depending on the social relations between the characters. The model was then implemented in an architecture for virtual agents and evaluated with humans. Results suggest that the emotions generated by our model are perceived by the participants, taking into account the social context and that participants experienced very similar emotions, both in type and intensity, to the emotions appraised and generated by the characters.

Building Empathic Agents? Comment on “Computational Modelling of Culture and Affect” by Aylett and Paiva

This comment discusses work by Aylett and Paiva (2012) which describes a synthetic approach to building a virtual world inhabited by synthetic characters where the user can experience subjective culture, that is, the experience of social reality, and learn how to empathetically communicate with people in other cultures. It provides a computational theory for integrating recent findings on emotion and cultural sensitivities into an interactive drama played by interacting characters with varying personalities. The FAtiMA-PSI, the implementation of their theory, has advanced a critical step towards basing affective intelligence on a firmer ground. Future challenges include building an empathic agent on the simulated physiology level that can be recognized as an independent ego with its own personality and presence.

Infants prefer the faces of strangers or mothers to morphed faces: an uncanny valley between social novelty and familiarity

The ‘uncanny valley’ response is a phenomenon involving the elicitation of a negative feeling and subsequent avoidant behaviour in human adults and infants as a result of viewing very realistic human-like robots or computer avatars. It is hypothesized that this uncanny feeling occurs because the realistic synthetic characters elicit the concept of ‘human’ but fail to satisfy it. Such violations of our normal expectations regarding social signals generate a feeling of unease. This conflict-induced uncanny valley between mutually exclusive categories (human and synthetic agent) raises a new question: could an uncanny feeling be elicited by other mutually exclusive categories, such as familiarity and novelty? Given that infants prefer both familiarity and novelty in social objects, we address this question as well as the associated developmental profile. Using the morphing technique and a preferential-looking paradigm, we demonstrated uncanny valley responses of infants to faces of mothers (i.e. familiarity) and strangers (i.e. novelty). Furthermore, this effect strengthened with the infant's age. We excluded the possibility that infants detect and avoid traces of morphing. This conclusion follows from our finding that the infants equally preferred strangers’ faces and the morphed faces of two strangers. These results indicate that an uncanny valley between familiarity and novelty may accentuate the categorical perception of familiar and novel objects.

Experience and the Ultimacy of God: In Memoriam John Edwin Smith

Experience and the Ultimacy of God: In Memoriam John Edwin Smith