404 research outputs found

    Social Robots as the Bride? Understanding the Construction of Gender in a Japanese Social Robot Product

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    This study critically investigates the construction of gender on a Japanese hologram animestyle social robot Azuma Hikari. By applying a mixed method merging the visual semiotic method and heterogeneous engineering approach in software studies, the signs in Azuma Hikari’s anthropomorphized image and the interactivity enabled by the multimedia interface have been analyzed and discussed. The analysis revealed a stereotyped representation of a Japanese “ideal bride” who should be cute, sexy, comforting, good at housework, and subordinated to “Master”-like husband. Moreover, the device interface disciplines users to play the role of “wage earner” in the simulated marriage and reconstructs the gender relations in reality. It suggests the humanization of the objects is often associated with the dehumanization and objectification of the human in reverse

    Selective AP-sequence Based Indoor Localization without Site Survey

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    In this paper, we propose an indoor localization system employing ordered sequence of access points (APs) based on received signal strength (RSS). Unlike existing indoor localization systems, our approach does not require any time-consuming and laborious site survey phase to characterize the radio signals in the environment. To be precise, we construct the fingerprint map by cutting the layouts of the interested area into regions with only the knowledge of positions of APs. This can be done offline within a second and has a potential for practical use. The localization is then achieved by matching the ordered AP-sequence to the ones in the fingerprint map. Different from traditional fingerprinting that employing all APs information, we use only selected APs to perform localization, due to the fact that, without site survey, the possibility in obtaining the correct AP sequence is lower if it involves more APs. Experimental results show that, the proposed system achieves localization accuracy < 5m with an accumulative density function (CDF) of 50% to 60% depending on the density of APs. Furthermore, we observe that, using all APs for localization might not achieve the best localization accuracy, e.g. in our case, 4 APs out of total 7 APs achieves the best performance. In practice, the number of APs used to perform localization should be a design parameter based on the placement of APs.Comment: VTC2016-Spring, 15-18 May 2016, Nanjing, Chin

    An image is worth 1000 lies: adversarial transferability across prompts on vision-language models

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    Different from traditional task-specific vision models, recent large VLMs can readily adapt to different vision tasks by simply using different textual instructions, i.e., prompts. However, a well-known concern about traditional task-specific vision models is that they can be misled by imperceptible adversarial perturbations. Furthermore, the concern is exacerbated by the phenomenon that the same adversarial perturbations can fool different task-specific models. Given that VLMs rely on prompts to adapt to different tasks, an intriguing question emerges: Can a single adversarial image mislead all predictions of VLMs when a thousand different prompts are given? This question essentially introduces a novel perspective on adversarial transferability: cross-prompt adversarial transferability. In this work, we propose the Cross-Prompt Attack (CroPA). This proposed method updates the visual adversarial perturbation with learnable textual prompts, which are designed to counteract the misleading effects of the adversarial image. By doing this, CroPA significantly improves the transferability of adversarial examples across prompts. Extensive experiments are conducted to verify the strong cross-prompt adversarial transferability of CroPA with prevalent VLMs including Flamingo, BLIP-2, and InstructBLIP in various different tasks

    Frank Aggregation Operators for Triangular Interval Type-2 Fuzzy Set and Its Application in Multiple Attribute Group Decision Making

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    This paper investigates an approach to multiple attribute group decision-making (MAGDM) problems, in which the individual assessments are in the form of triangle interval type-2 fuzzy numbers (TIT2FNs). Firstly, some Frank operation laws of triangle interval type-2 fuzzy set (TIT2FS) are defined. Secondly, some Frank aggregation operators such as the triangle interval type-2 fuzzy Frank weighted averaging (TIT2FFWA) operator and the triangle interval type-2 fuzzy Frank weighted geometric (TIT2FFWG) operator are developed for aggregation TIT2FNs. Furthermore, some desirable properties of the two aggregation operators are analyzed in detail. Finally, an approach based on TIT2FFWA (or TIT2FFWG) operator to solve MAGDM is developed. An illustrative example about supplier selection is provided to illustrate the developed procedures. The results demonstrate the practicality and effectiveness of our new method

    Numerical Simulation on Instability Mechanism of Section Coal Pillar in Shallow Buried Coal Seams

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    There is abundant coal resource of Jurassic period in Yulin City, and the problem of shallow buried coal seams mining will occur in every mine area. FLAC3D is used to analyze the plastic failure, deformation characteristic, and vertical stress on shallow buried coal seams mining, based on north No. 2 engineering geological conditions of Hongliulin Mining Corporation. In this paper, the results are shown as follows. The plastic failure fields of section coal pillar forming are smaller; the coal seam hosting is shallower. The elastic region of section coal pillar has a relatively large proportion, which is the coal seam first mined. The value of Z-Displacement for the first coal seam is relatively small. However, for the lower coal seam it is relatively big. The value of X-Displacement for each coal seam is relatively small. The coal wall of section coal pillar is in a steady state. The coal seam hosting is deeper; the more distant is from coal wall to peak point abutment pressure. The stress concentration factor for the first coal seam is relatively big. The research conclusion reveals instability mechanism of section coal pillar, while coal seams mining, which provides a theoretical basis for designing width vale and optimizing supporting scheme of section coal pillar, has engineering experience application value to other coalmines in Yulin City

    Model-agnostic origin attribution of generated images with few-shot examples

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    Recent progress in visual generative models enables the generation of high-quality images. To prevent the misuse of generated images, it is important to identify the origin model that generates them. In this work, we study the origin attribution of generated images in a practical setting where only a few images generated by a source model are available and the source model cannot be accessed. The goal is to check if a given image is generated by the source model. We first formulate this problem as a few-shot one-class classification task. To solve the task, we propose OCC-CLIP, a CLIP-based framework for few-shot oneclass classification, enabling the identification of an image’s source model, even among multiple candidates. Extensive experiments corresponding to various generative models verify the effectiveness of our OCC-CLIP framework. Furthermore, an experiment based on the recently released DALL ·E-3 API verifies the real-world applicability of our solution
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