Human-robot interaction: the impact of robotic aesthetics on anticipated human trust

Background Human senses have evolved to recognise sensory cues. Beyond our perception, they play an integral role in our emotional processing, learning, and interpretation. They are what help us to sculpt our everyday experiences and can be triggered by aesthetics to form the foundations of our interactions with each other and our surroundings. In terms of Human-Robot Interaction (HRI), robots have the possibility to interact with both people and environments given their senses. They can offer the attributes of human characteristics, which in turn can make the interchange with technology a more appealing and admissible experience. However, for many reasons, people still do not seem to trust and accept robots. Trust is expressed as a person’s ability to accept the potential risks associated with participating alongside an entity such as a robot. Whilst trust is an important factor in building relationships with robots, the presence of uncertainties can add an additional dimension to the decision to trust a robot. In order to begin to understand how to build trust with robots and reverse the negative ideology, this paper examines the influences of aesthetic design techniques on the human ability to trust robots. Method This paper explores the potential that robots have unique opportunities to improve their facilities for empathy, emotion, and social awareness beyond their more cognitive functionalities. Through conducting an online questionnaire distributed globally, we explored participants ability and acceptance in trusting the Canbot U03 robot. Participants were presented with a range of visual questions which manipulated the robot’s facial screen and asked whether or not they would trust the robot. A selection of questions aimed at putting participants in situations where they were required to establish whether or not to trust a robot’s responses based solely on the visual appearance. We accomplished this by manipulating different design elements of the robots facial and chest screens, which influenced the human-robot interaction. Results We found that certain facial aesthetics seem to be more trustworthy than others, such as a cartoon face versus a human face, and that certain visual variables (i.e., blur) afforded uncertainty more than others. Consequentially, this paper reports that participant’s uncertainties of the visualisations greatly influenced their willingness to accept and trust the robot. The results of introducing certain anthropomorphic characteristics emphasised the participants embrace of the uncanny valley theory, where pushing the degree of human likeness introduced a thin line between participants accepting robots and not. By understanding what manipulation of design elements created the aesthetic effect that triggered the affective processes, this paper further enriches our knowledge of how we might design for certain emotions, feelings, and ultimately more socially acceptable and trusting robotic experiences.

APPLICATION OF DIGITAL STRUCTURE SIMULATION AS A TOOL FOR THE EXPLORATION OF WIDE SPAN STRUCTURE IDEAS

Review on structure behaviour and visual appearance of a building is needed in generating creativity in the making of an architectural design. The use of any specific structure software will facilitate this in the process. This research aims to prove the effectiveness with which designers can compose alternative forms of architectural appearance through the use of the software. One of the tools in the creative process used in the exploration of 2-dimensional frame structures is DR FRAME. The observations were carried in the Structure and Construction IV Studio at Itenas Architecture Study Program Bandung through a digital simulation using DR. FRAME software demo version. Several students are invited to explore various forms of wide-span truss structures at the level of unified integration. The results through the program execution show various diagrams which can be implemented in the design of the form and the type of structural components. DR.FRAME software enriches ideas in the wide-span structure design which provides an understanding of the relationship between structural behaviour and the appearance of architectural design. The use of other supporting software is supposed to be applied as an alternative search for various structural design ideas for architecture students

Use of fruit epicarps to formulate pectin-based bioactive films / Utilização de epicarpos de frutos para formulação de filmes bioativos à base de pectinas

The functional properties of biofilms can vary according to the biopolymer used as the raw material; thus, in the search for alternative sources for preparation of biodegradable films, fruits and vegetables have been used to extract compounds of interest with applications in the food industry. The objective of this work was to obtain and characterize bioactive films based on pectin extracted from the epicarps (skin) of the fruit. The genipap (Genipa americana), red pitaya (Hylocereus polyrhizus) and star fruit (Averrhoa carambola) were collected, washed, pulped and dried at 50 °C for 24 h, and their epicarps were ground and subjected to pectin extraction using the casting method. The films were characterized as to their visual appearance, moisture, pH, water solubility and antioxidant activity. The pectin-based films of G. americana and H. polyrhizus showed a yellowish color, while A. carambola was dark brown. The highest pectin yield (29%) and moisture content (13.9%) were obtained from the H. polyrhizus film, while A. carambola showed the highest solubility in water (98.6%) and had the highest pH (3.9). Additionally, the film based on A. carambola showed greater antioxidant potential against ABTS (30.5%) and DPPH (34%), as well as greater reducing power (0.262 absorbance at 750 nm) and content of total phenolic compounds (553 mg GAE/100 g), whereas H. polyrhizus had a higher percentage of chelating ability (27%). The physicochemical characteristics and bioactive properties exhibited make the film formulation a viable alternative for the food industry.

Comparison of Three Individual Identification Algorithms for Sperm Whales (Physeter macrocephalus) after Automated Detection

Photo-identification of individual sperm whales (Physeter macrocephalus) is the primary technique for mark-recapture-based population analyses for the species The visual appearance of the fluke - with its distinct nicks and notches - often serves as the primary visual differentiator, allowing humans to make recorded sightings of specific individuals. However, the advent of digital photography and the significant increase in volume of images from multiple projects in combination with pre-existing historical catalogs has made applying the method more challenging.with the required human labor for de-duplication (reduction of Type II errors) and reconciliation of sightings between large datasets too cost- and time- prohibitive. To address this, we trained and evaluated the accuracy of PIE v2 (a triplet loss network) along with two existing fluke trailing edge-matching algorithms, CurvRank v2 and Dynamic Time Warping (DTW), as a mean to speed comparison among a high volume of photographs. Analyzed data were collected from a curated catalog of well-known sperm whales sighted across years (2005-2018) off the island of Dominica. The newly-trained PIE model outperformed the older CurvRank and DTW algorithms, and PIE provided the following top-k individual ID matching accuracy on a standard min-3/max-10 sighting training data set: Rank-1: 87.0%, Rank-5: 90.5%, and Rank-12: 92.5%. An essential aspect of PIE is that it can learn new individuals without network retraining, which can be immediately applied in the presence of (and for the resolution of) duplicate individuals in overlapping catalogs. Overall, our results recommend the use of PIE v2 and CurvRank v2 for ID reconciliation in combination due to their complementary performance.

PulseEdit: Editing Physiological Signal in Facial Videos for Privacy Protection

Recent studies have shown that physiological signals can be remotely captured from human faces using a portable color camera under ambient light. This technology, namely remote photoplethysmography (rPPG), can be used to collect users' physiological status who are sitting in front of a camera, which may raise physiological privacy issues. To avoid the privacy abuse of the rPPG technology, this paper develops PulseEdit, a novel and efficient algorithm that can edit the physiological signals in facial videos without affecting visual appearance to protect the user's physiological signal from disclosure. PulseEdit can either remove the trace of the physiological signal in a video or transform the video to contain a target physiological signal chosen by a user. Experimental results show that PulseEdit can effectively edit physiological signals in facial videos and prevent heart rate measurement based on rPPG. It is possible to utilize PulseEdit in adversarial scenarios against some rPPG-based visual security algorithms. We present analyses on the performance of PulseEdit against rPPG-based liveness detection and rPPG-based deepfake detection, and demonstrate its ability to circumvent these visual security algorithms.

Machine Learning-Based Lie Detector Applied to a Novel Annotated Game Dataset

Lie detection is considered a concern for everyone in their day-to-day life, given its impact on human interactions. Thus, people normally pay attention to both what their interlocutors are saying and to their visual appearance, including the face, to find any signs that indicate whether or not the person is telling the truth. While automatic lie detection may help us to understand these lying characteristics, current systems are still fairly limited, partly due to lack of adequate datasets to evaluate their performance in realistic scenarios. In this work, we collect an annotated dataset of facial images, comprising both 2D and 3D information of several participants during a card game that encourages players to lie. Using our collected dataset, we evaluate several types of machine learning-based lie detectors in terms of their generalization, in person-specific and cross-application experiments. We first extract both handcrafted and deep learning-based features as relevant visual inputs, then pass them into multiple types of classifier to predict respective lie/non-lie labels. Subsequently, we use several metrics to judge the models’ accuracy based on the models predictions and ground truth. In our experiment, we show that models based on deep learning achieve the highest accuracy, reaching up to 57% for the generalization task and 63% when applied to detect the lie to a single participant. We further highlight the limitation of the deep learning-based lie detector when dealing with cross-application lie detection tasks. Finally, this analysis along the proposed datasets would potentially be useful not only from the perspective of computational systems perspective (e.g., improving current automatic lie prediction accuracy), but also for other relevant application fields, such as health practitioners in general medical counselings, education in academic settings or finance in the banking sector, where close inspections and understandings of the actual intentions of individuals can be very important.

Image-to-Image Translation as a Pretext for Unsupervised Detection of Cancerous Regions in Histology Imagery

Detection of visual anomalies refers to the problem of finding patterns in different imaging data that do not conform to the expected visual appearance, and is a widely studied problem in different domains. Due to the nature of anomaly occurrences and underlying generating processes, it is hard to characterize them and obtain labelled data. Obtaining labelled data is especially difficult in biomedical applications, where only trained domain experts can provide labels, which are often diverse and complex to a large degree. The recently presented approaches for unsupervised detection of visual anomalies omit the need for labelled data and demonstrate promising results in domains where anomalous samples significantly deviate from the normal appearance. Despite promising results, the performance of such approaches still lags behind supervised approaches and does not provide a universal solution. In this work, we present an image-to-image translation-based framework that significantly surpasses the performance of existing unsupervised methods and approaches the performance of supervised methods in a challenging domain of cancerous region detection in histology imagery.

Implementation and Optimization of Image Processing on the Map of SABRE i.MX_6

Vision relieves humans to understand the environmental deviations over a period. These deviations are seen by capturing the images. The digital image plays a dynamic role in everyday life. One of the processes of optimizing the details of an image whilst removing the random noise is image denoising. It is a well-explored research topic in the field of image processing. In the past, the progress made in image denoising has advanced from the improved modeling of digital images. Hence, the major challenges of the image process denoising algorithm is to advance the visual appearance whilst preserving the other details of the real image. Significant research today focuses on wavelet-based denoising methods. This research paper presents a new approach to understand the Sobel imaging process algorithm on the Linux platform and develop an effective algorithm by using different optimization techniques on SABRE i.MX_6. Our work concentrated more on the image process algorithm optimization. By using the OpenCV environment, this paper is intended to simulate a Salt and Pepper noisy phenomenon and remove the noisy pixels by using Median Filter Algorithm. The Sobel convolution method included and used in the design of a Sobel Filter and then process the image following the median filter, to achieve an effective edge detection result. Finally, this paper optimizes the algorithm on SABRE i.MX_6 Linux environment. By using algorithmic optimization (lower complexity algorithm in the mathematical sense, using appropriate data structures), optimization for RISC (loop unrolling) processors, including optimization for efficient use of hardware resources (access to data, cache management and multi-thread), this paper analyzed the different response parameters of the system with varied inputs, different compiler options (O1, O2, or O3), and different doping degrees. The proposed denoising algorithm shows the meaningful addition of the visual quality of the images and the algorithmic optimization assessment.

Effect of Diamond Polishing and Thermal Treatment on Carbon Paramagnetic Centers’ Nature and Structure

Diamonds contain carbon paramagnetic centers (stable carbon radicals) in small concentrations (at the level of ~1 × 1012 spins/mg) that can help in elucidating the structure of the nitrogen atoms’ contaminants in the diamond crystal. All diamonds that undergo polishing are exposed to high temperatures, owing to the friction force during the polishing process, which may affect the carbon-centered radicals’ concentration and structure. The temperature is increased appreciably; consequently, the black body radiation in the visible range turns orange. During polishing, diamonds emit an orange light (at a wavelength of about 600 nm) that is typical of a black body temperature of 900 °C or higher. Other processes in which color-enhanced diamonds are exposed to high temperatures are thermal treatments or the high-pressure, high-temperature (HPHT) process in which the brown color (resulting from plastic deformation) is bleached. The aim of the study was to examine how thermal treatment and polishing influence the paramagnetic centers in the diamond. For this purpose, four rough diamonds were studied: two underwent a polishing process, and the other two were thermally treated at 650 °C and 1000 °C. The diamonds were analyzed pre- and post-treatment by EPR (Electron Paramagnetic resonance), FTIR (Fourier transform infrared, fluorescence, and their visual appearance. The results indicate that the polishing process results in much more than just thermal heating the paramagnetic centers.