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We introduce purely visual paradigms that convey the logical structure of illusory inferences from disjunction: (a AND b) OR c, a |- b. Although the logical information was conveyed entirely via non-linguistic means, we found that the visual paradigms induce reasoning fallacies, though less attractive than their linguistic counterparts. The visual paradigms highlight the role of alternative-based reasoning, or question-answer dynamics, as they control for narrowly interpretive processes that confound the study of their linguistic counterparts. To our knowledge, this is the first work to develop visual paradigms that represent reasoning fallacies committed by adults and involve multiple logical operators non-trivially embedded. Previous studies focused on pre-verbal children or non-human animals, and for this reason limited the scope of research to visually representing logically simple, valid inferences.

Accurate and robust localization is essential for autonomous mobile robots. Map matching based on Light Detection and Ranging (LiDAR) sensors has been widely adopted to estimate the global location of robots. However, map‐matching performance can be degraded when the environment changes or when sufficient features are unavailable. Indiscriminately incorporating inaccurate map‐matching poses for localization can significantly decrease the reliability of pose estimation. This paper aims to develop a robust LiDAR‐based localization method based on map matching. We focus on determining appropriate weights that are computed from the uncertainty of map‐matching poses. The uncertainty of map‐matching poses is estimated by the probability distribution over the poses. We exploit the normal distribution transform map to derive the probability distribution. A factor graph is employed to combine the map‐matching pose, LiDAR‐inertial odometry, and global navigation satellite system information. Experimental verification was successfully conducted outdoors on the university campus in three different scenarios, each involving changing or dynamic environments. We compared the performance of the proposed method with three LiDAR‐based localization methods. The experimental results show that robust localization performances can be achieved even when map‐matching poses are inaccurate in various outdoor environments. The experimental video can be found at https://youtu.be/L6p8gwxn4ak. [ABSTRACT FROM AUTHOR]

Vehicle localization using mounted sensors is an essential technology for various applications, including autonomous vehicles and road mapping. Achieving high positioning accuracy through the fusion of low-cost sensors is a topic of considerable interest. Recently, applications based on crowdsourced data from a large number of vehicles have received significant attention. Equipping standard vehicles with low-cost onboard sensors offers the advantage of collecting data from multiple drives over extensive road networks at a low operational cost. These vehicle trajectories and road observations can be utilized for traffic surveys, road inspections, and mapping. However, data obtained from low-cost devices are likely to be highly inaccurate. On urban roads, unlike highways, complex road structures and GNSS signal obstructions caused by buildings are common. This study proposes a reliable vehicle localization method using a large amount of crowdsourced data collected from urban roads. The proposed localization method is designed with consideration for the high inaccuracy of the data, the complexity of road structures, and the partial use of high-definition (HD) maps that account for environmental changes. The high inaccuracy of sensor data affects the reliability of localization. Therefore, the proposed method includes a reliability assessment of the localized vehicle poses. The performance of the proposed method was evaluated using data collected from buses operating in Seoul, Korea. The data used for the evaluation were collected 18 months after the creation of the HD maps. [ABSTRACT FROM AUTHOR]

AbstractThe conjunction fallacy is the well-documented reasoning error on which people rate a conjunction A∧B as more probable than one of its conjuncts, A. Many explanations appeal to the fact that B has a high probability in the given scenarios, but Katya Tentori and collaborators have challenged such approaches. They report experiments suggesting that degree of confirmation—rather than probability—is the central determinant of the conjunction fallacy. In this paper, we have two goals. First, we address a confound in Tentori et al.’s experiments: they failed to control for the fact that in their stimuli where B is confirmed, it is also conversationally relevant in the sense that it fits with the topic or question under discussion. Conversely, when B has a high probability but is not confirmed, it is conversationally irrelevant. Consequently, it is possible that conversational relevance, rather than confirmation, is responsible for the differences they found between confirmed and probable hypotheses. Second, inspired by recent theoretical work, we aim to give the first empirical investigation of the hypothesis that this type of conversational relevance on its own—independently of degree of confirmation—can be an important factor in the conjunction fallacy. We report on two experiments that vary Tentori et al.’s design by making B relevant without changing its degree of probability or confirmation. We found that doing so increases the rate of the conjunction fallacy, suggesting that relevance plays an important role in the conjunction fallacy. [ABSTRACT FROM AUTHOR]

Graphite is a versatile material used in various fields, particularly in the power source manufacturing industry. Nowadays, graphite holds a unique position in materials for anode electrodes in lithium-ion batteries. With a carbon content of over 99% being a requirement for graphite to serve as an electrode material, the graphite refinement process plays a pivotal role in the research and development of anode materials for lithium-ion batteries. This study used three different processes to purify spherical graphite through wet chemical methods. The spherical graphite after the purification processes was analysed for carbon content by using energy-dispersive X-ray (EDX) spectroscopy and was evaluated for structural and morphological characteristics through X-ray diffraction (XRD), scanning electron microscopy (SEM), and Brunauer–Emmett–Teller (BET) analyses. The analyses results indicate that the three-step process via H2SO4–NaOH–HCl cleaning can elevate the carbon content from 90% to above 99.9% while still maintaining the graphite structure and spherical morphology, thus enhancing the surface area of the material for anode application. Furthermore, the spherical graphite was studied for electrochemical properties when used as an anode for Li-ion batteries using cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) measurements. The results demonstrated that the purification process significantly improves the material's capacity with a specific capacity of 350 mAh/g compared to the 280 mAh/g capacity of the anode made of spherical graphite without purification. [ABSTRACT FROM AUTHOR]