Geographic Named Entity Recognition (GNER) focuses on extracting geographic entity names from text and classifying them into pre-defined categories. Previous methods have not paid much attention to identifying fine-grained categories of geographic entities in sparse data situations, thus remaining limited in serving various geographic applications. To address this limitation, this paper presents a fine-grained GNER task and proposes a fine-grained GNER model, LH-FGNER, which incorporates a prototype network and hierarchical contrastive learning to improve fine-grained GNER. Specifically, the model designs label-guided sentence-level prototypes to capture the contextual semantics of geographic entities. It introduces a hierarchy tree to guide the construction of prototypes in vector space, which utilizes the hierarchy as a priori knowledge to improve the discrimination of fine-grained categories. In addition, two datasets are constructed to support the study of the fine-grained GNER task. Experimental results show that the proposed model is superior to the baseline and is robust. This work provides a methodological reference for few-shot GNER, which can be used to facilitate various geographic applications with text.

Historically, transgender people of color (TPOC) have been silenced in white trans spaces for not fitting into transnormativity - the typical white, binary, skinny, and privileged image of trans people, and for raising concerns related to race, culture, and ethnicity. Social media and online communities serve as supportive spaces for transgender (shortened to trans) individuals; however, trans people of color require even more support combating systematic oppression, managing increased levels of discrimination, and navigating their cultural backgrounds. In order to understand how TPOC use social media, we explore the experiences of TPOC on Reddit. We used the Reddit API to obtain Reddit posts from four prominent transgender subreddits (r/ftm, r/mtf, r/trans, and r/Non-Binary) which included the phrase "people of color" or the abbreviation "POC", resulting in a total of 145 posts and 2867 comments. Thematic analysis was then used to identify three themes of discussion - alienation, support, and existing in physical spaces, which informed our design considerations. Experiences shared in the Reddit posts indicated that TPOC feel overshadowed by white trans individuals in online communities and desire to build connections with other TPOC both online and in person. We propose design recommendations for both Reddit as a platform and subreddit moderators that regulate online trans communities to encourage growing networks among TPOC, improve communication among users and moderators, and design spaces that center POC voices within subreddits, all of which provide a much more supportive online environment for TPOC.

Researchers are increasingly facilitating qualitative research studies online. While this has made research more accessible for participation, there have been notable encounters with “fraudulent” participants. By fraudulent, we refer to individuals who are deceptive about meeting the inclusion criteria, their identity, or experiences. Fraudulent participants have generated new challenges for researchers who have to interact 1:1 with these individuals, face ethical dilemmas on appropriate next steps, diagnose and prevent the issue from happening again, and deal with their own identity as a scholar. In this study, we interview 16 HCI researchers to understand and learn from their experiences. We contribute: (1) an understanding of how HCI qualitative researchers deal with fraudulent participants; (2) a guide for qualitative HCI researchers on how to handle fraudulence; and (3) a reflection on how the HCI research community might better improve our science and training efforts.

Meals are a central (and messy) part of family life. Previous design framings for mealtime technologies have focused on supporting dietary needs or social and celebratory interactions at the dinner table; however, family meals involve the coordination of many activities and complicated family dynamics. In this paper, we report on findings from interviews and design sessions with 18 families from the Midwestern United States (including both partners/parents and children) to uncover important family differences and tensions that arise around domestic meal experiences. Drawing on feminist theory, we unpack the work of feeding a family as a form of care, drawing attention to the social and emotional complexity of family meals. Critically situating our data within current design narratives, we propose the sensitizing concepts of generative and systemic discontents as a productive way towards troubling the design space of family-food interaction to contend with the struggles that are a part of everyday family meal experiences.

Smart speakers have become pervasive in family homes, creating the potential for these devices to influence parent-child dynamics and parenting behaviors. We investigate the impact of introducing a smart speaker to 10 families with children, over four weeks. We use pre- and post- deployment interviews with the whole family and in-home audio capture of parent-child interactions with the smart speaker for our analysis. Despite the smart speaker causing occasional conflict in the home, we observed that parents lever-aged the smart speaker to further parenting goals. We found three forms of influence the smart speaker has on family dynamics: 1) fostering communication, 2) disrupting access, and 3) augmenting parenting. All of these influences arise from a communally accessible, stand-alone voice interface which democratizes family access to technology. We discuss design implications in furthering parenting practices and behaviors as the capabilities of the technology continue to improve.

In recent years, video forensics has become an important issue. Video inter-frame forgery detection is a significant branch of forensics. In this paper, a new algorithm based on the consistency of velocity field is proposed to detect video inter-frame forgery (i.e., consecutive frame deletion and consecutive frame duplication). The generalized extreme studentized deviate (ESD) test is applied to identify the forgery types and locate the manipulated positions in forged videos. Experiments show the effectiveness of our algorithm.

The term "shitsukan" refers to the perception of materials and surface qualities of natural and manmade objects. The main goal of our study is to extend the current content-based image retrieval (CBIR) systems to develop a shitsukan-based image retrieval (SBIR) system. This paper focuses on Japanese onomatopoeias as a feature for SBIR and verifies their suitability based on psychophysical experiments. In this study, we conducted two different experiments. In the first experiment, subjects assigned suitable onomatopoeias to 50 test images. In the second experiment, they selected perceptually similar images for each test image from the other 49 test images. Then, we investigated the relationship between the assigned onomatopoeias and the selected similar images. The results indicate that perceptually similar images were assigned to the same onomatopoeias with correlation, and that onomatopoeias were effective as a feature for SBIR.

Computing the encoding delay and bandwidth on the nodes is important for the deployment and implementation of network coding. However, the existing researches merely use the methods of experimental measurement or rough estimation to investigate it. In order to accurately compute the delay and bandwidth on the nodes with network coding implemented, this paper proposes a novel method to quantify encoding delay and encoding bandwidth. Firstly, network coding is applied to design a new network. And then, the encoding procedure is systematically investigated on the source node, the intermediate node, and also the decoding procedure is systematically investigated at the destination node. And the method, which can be used to compute the node encoding delay and encoding bandwidth, is presented, Thus the method of computing total delay of network with network coding is derived. Finally, the experiments validate the correctness of this method.