Category Ambiguity Research Articles

Learning from feature and label spaces’ bias for uncertainty-adaptive facial emotion recognition

Developing an accurate deep model for facial emotion recognition is a long-term challenge. It is because the uncertainty of emotions, stemming from the ambiguity of different emotional categories and the difference of subjective annotations, can ruin the ability of model to achieve the desired optimization. This paper constructs two distinct datasets, namely original sample set and ambiguous sample set, to explore an effective ambiguous knowledge transfer method to realize the adaptive awareness of uncertainty in facial emotion recognition. The original sample set is the weakly-augmented data with relatively low uncertainty, as most emotions are clean in reality. Meanwhile, the ambiguous sample set is strongly-augmented data that introduces feature and label bias with regard to emotion, which are with relatively high uncertainty. The proposed framework consists of two sub-nets, which are trained using the original set and the ambiguous set respectively. To achieve uncertainty-adaptive learning for two sub-nets, we introduce two modules. One is the cross-space attention consistency learning module that performs attention coupling across original and ambiguous feature spaces, achieving uncertainty-aware representation learning in feature granularity. The other is the soft-label learning module that models and utilizes uncertainty in label granularity, through aligning the posterior distributions between original label space and ambiguous label space. Experimental studies on public datasets indicate that our method is competitive with the state-of-the-art.

Learning semantic categories of L2 verbs: The case of cutting and breaking verbs.

To attain native-like proficiency in second-language word usage, learners have to discover intricate semantic categories in the target language. We investigated the factors influencing the development of two aspects of second-language learners' semantic categories: the category center and category boundary of word meanings. In the experiment, second-language learners of Japanese, whose first language is Mandarin, were asked to produce the best verb for 28 videos depicting various cutting and breaking events. Descriptive analyses were conducted to compare the verb patterns used by second-language learners with those of native speakers. The second-language learners' verb use pattern suggested their struggle in delineating the semantic ranges of breaking verbs in a native-like manner. Model analyses further revealed that different factors contribute to learning two different aspects of word meanings. The learning category center of word meaning depended on the similarity between the lexical domains in the first and second languages. On the contrary, the success of learning the semantic boundaries of verbs required a large input frequency and smaller semantic coverage, and smaller category ambiguity. The results suggest that constructing a semantic domain in the second language should be evaluated from at least two different aspects of semantic representation.

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The difficulty of teaching doctors a bioethical block of disciplines (ethical and legal, related to communication, patient-centeredness) lies in the ambiguity of the ethical categories themselves, which differ both historically and culturally. The deontological imperative, which could become a universal measure of the ethical, has similar limitations and, even if it successfully fulfills a normative function, can lead to moral suffering if its implementation is impossible. Other versions of metaethics also have limitations. Additional complexity is created by the starting point for designating a norm in bioethics - the definition of health, which has a biopsychosocial nature. All together, this turns out to be a serious challenge for teaching the bioethical block of disciplines. A possible solution is virtue, the formation of a “virtuoso doctor” capable of coping with ethical relativism - that inevitability that is always present in interpersonal relationships.

The role of category ambiguity in normal and impaired lexical processing: can you paint without the paint?

Many words are categorially ambiguous and can be used as a verb (to paint) or as a noun (the paint) due to the presence of unpronounced morphology or "zero morphology". On this account, the verb "paint" is derived from the noun "paint" through the addition of a silent category-changing morpheme. Past studies have uncovered the syntactic and semantic properties of these categorially ambiguous words, but no research has been conducted on how people process them during normal or impaired lexical processing. Are these two different uses of "paint" processed in the same way? Does this morphosyntactic structure have an effect on online sentence processing? This study presents two experiments that investigate the effect of morphosyntactic complexity in categorially ambiguous words presented in isolation (experiment 1) and in a sentential context (experiment 2). The first experiment tested the ability to process categorially unambiguous and ambiguous nouns and verbs in 30 healthy older adults and 12 individuals with aphasia, using a forced choice phrasal-completion task, in which individuals choose whether the or to is most compatible with target words. Healthy controls and individuals with fluent aphasia all showed: (1) a bias toward the base category in selection rates for the and to, where the was selected more frequently for words identified to be base nouns, and to was selected more frequently for base verbs, and (2) longer reaction times for ambiguous (over unambiguous) words. However, individuals with non-fluent agrammatic aphasia showed a base-category effect only for nouns, with chance performance for verbs. The second experiment, using an eye-tracking while reading paradigm with 56 young healthy adults, showed a reading time slowdown for derived forms (to paint) compared to their base-category counterparts (the paint) in sentence contexts. These findings suggest that categorially ambiguous words likely share a common root, and are related by zero-derivation, and that impaired access to the base-category (i.e., verbs like to visit) precludes associated morphological processes and therefore the retrieval of the derived-category (i.e., nouns like the visit) in non-fluent agrammatic aphasia. This study provides insights into the theory of zero morphology, and the principles that need to be accounted for in models of the lexicon.

The Tensions of Positionality Reflection

This is a contribution to the discussion forum "Conceptualizing Society after the Modern Territorial State and Nation." Marlene Laruelle agrees with the need for the decolonization of "Eurasia" as a political space and a research field, along with the deconstruction of Russia's "imperialness." By outlining the main tropes of the ongoing discussion, she points to the ambiguity of the key categories that frame it and hence to the tensions among the various meanings of those unclarified categories. She identifies the main tension between the proclaimed emancipatory goals, both political and epistemological, of the decolonization debate and the fundamental nation-centrism of the prevailing mode of social critique.

Legitimacy of Social Hybrids: Navigating the Ambiguity in Prosocial Category of B Corps

Hybrid organizations seeking social impact often pursue legitimation of their social commitment by aligning with a prosocial category -i.e, a context for entities aiming to prove the legitimacy of their social entrepreneurial attitude (Conger et al. 2018). However, hybrids often align with ambiguous categories - i.e. whose schema of norms and values allows very heterogeneous types of members to join (Durand and Paolella 2013) – such as B-Corps. Despite prior literature argues that aligning with an ambiguous category does not yield the benefits of legitimacy, we do not fully know the mechanisms underlying this relationship, especially for social hybrids who often struggle to achieve legitimacy. In this study, we ask what are the consequences of becoming a member of an organizational category whose meaning is ambiguous, and the mechanisms by which this relationship is attenuate or amplified? To answer this question, we draw on a sample of 186 Italian social hybrid organizations, of which 157 became B Corps and 29 did not. We found that membership in ambiguous organizational category generally does not pay-off. We found two mechanisms explaining this relationship. First, the degree of alignment with the organizational category amplifies the downsides of the relationship, i.e., over time, the more a social hybrid aligned with an ambiguous category the lower the benefits. Second, audience affording legitimation forgave category ambiguity when they could construe the boundaries of the business’s impact through its products/services. In other words, the level of concreteness of the product/services attenuated the negative implications of affiliating to the B-Corp category. We contribute to the literature on hybrid organizations by theorizing the mechanisms of alignment and boundary construal to explain when do audiences penalize hybrids aligning with ambiguous categories.

Remote sensing image description based on word embedding and end-to-end deep learning

This study proposes an end-to-end image description generation model based on word embedding technology to realise the classification and identification of Populus euphratica and Tamarix in complex remote sensing images by providing descriptions in precise and concise natural sentences. First, category ambiguity over large-scale regions in remote sensing images is addressed by introducing the co-occurrence matrix and global vectors for word representation to generate the word vector features of the object to be identified. Second, a new multi-level end-to-end model is employed to further describe the content of remote sensing images and to better advance the description tasks for P. euphratica and Tamarix in remote sensing images. Experimental results reveal that the natural language sentences generated using this method can better describe P. euphratica and Tamarix in remote sensing images compared with conventional deep learning methods.

Research on Intelligent Target Recognition Integrated With Knowledge

With the development of artificial intelligence technology, intelligent weapon systems that can automatically identify, lock on and strike targets have gradually appeared and can replace humans in executing simple decision-making commands. Target detection is a key part of intelligent weapons. At present, large-scale target detection has serious challenges such as long-tail data distributions, severe occlusion, and category ambiguity. The main detection algorithms only detect each independent area without considering the key semantic dependencies between objects. It has become a hot trend to apply deep learning to prior knowledge to form a model. This article uses both internal and external knowledge to instill a target detection system with human reasoning capabilities. Commonly used external embedded knowledge includes geometric relations, attributes, locations, etc. They have a common shortcoming in that they require large amounts of labeled data, and the integration costs are huge. The purpose of this article is to construct a general external prior knowledge module to guide network learning. By paying attention to the characteristics of each object in different semantic contexts, the characteristics of each object are adaptively enhanced, and the high-level semantics of all categories evolve on a global scale. Internal knowledge uses a convolutional attention module that can learn spatial and channel information at multiple scales. The experimental results show the superiority of our knowledge-YOLOv5. The proposed method achieved 1.7%, 2.2%, 1.1%, and 0.7% improvements over YOLOv5s, YOLOv5m, VOLOv51, and YOLOv5x, respectively, on the COCO data sets; and the proposed method also achieves a 0.9% improvement on the self-built data set. The trained lightweight model Knowledge-YOLOv5s is deployed on an NVIDIA Jetson TX2 through TensorRT acceleration, and the real-time detection frame is 20 ms, which meets the real-time detection requirements. This system can also be used as a module of an intelligent weapon system, which has certain referential significance for autonomous weapons and unmanned combat systems.

Detection of Disaster-Affected Cultural Heritage Sites from Social Media Images Using Deep Learning Techniques

This article describes a method for early detection of disaster-related damage to cultural heritage. It is based on data from social media, a timely and large-scale data source that is nevertheless quite noisy. First, we collect images posted on social media that may refer to a cultural heritage site. Then, we automatically categorize these images according to two dimensions: whether they are indeed a photo in which a cultural heritage resource is the main subject, and whether they represent damage. Both categorizations are challenging image classification tasks, given the ambiguity of these visual categories; we tackle both tasks using a convolutional neural network. We test our methodology on a large collection of thousands of images from the web and social media, which exhibit the diversity and noise that is typical of these sources, and contain buildings and other architectural elements, heritage and not-heritage, damaged by disasters as well as intact. Our results show that while the automatic classification is not perfect, it can greatly reduce the manual effort required to find photos of damaged cultural heritage by accurately detecting relevant candidates to be examined by a cultural heritage professional.

Persistent Category Ambiguity: The case of social entrepreneurship

Literature on categories recognizes that in the early stages of a category, ambiguity can arise from divergent frames used to define the category. Yet it also largely expects this ambiguity to be either temporary, or else detrimental to the survival and evolution of the category. In this study, we demonstrate and explain how, alternatively, category ambiguity can persist when multiple frames continue to be applied to a category as it progresses into maturity. Drawing on an in-depth qualitative study of the case of social entrepreneurship, we examine how and under what conditions this outcome occurs. We specify two co-occurring conditions that prompt category stakeholders to shift their framing from exclusive to inclusive, enabling category ambiguity to persist. We furthermore show how the use of category frames that draw from pre-existing resonant categories supports the persistence of category ambiguity. We contribute to literature on categories by clarifying the antecedents of category evolution towards a trajectory of persistent ambiguity.

Upbringing and parenting, style of upbringing and parenting style. Terminological analysis

The article presents considerations on the essence of education inspired by the perception of the ambiguity of categories used in psychology and concerning parenting, such as parenting style, style of upbringing and parental attitude. In the article, the differences between social influence and development and upbringing as well as key features of educational activities (intentionality, purposefulness, processuality, asymmetry of educational relation) were pointed out. The author treats upbringing as a long-lasting and intentional interpersonal interaction aimed at optimization the development of a pupil. The domain of educational activity is updating the developmental potential. Accepting such an assumption, she notes that not all parenting activities mean upbringing. Its influence can be destructive from the child's development point of view. However, the attempt to go beyond the caring and educational functions with which parenthood is most often identified has resulted in the author's approach to the parenting style. It is discussed on the basis of a complex network of factors differentiating the interpersonal and intrapsychic dimension of the parents' experiences.

Assessing supplier capabilities to exploit building information modelling

PurposeA number of governments are making building information modeling (BIM) a mandatory requirement for all public works construction projects. While main contractors may be ready to comply with such requirements, the supply chain as whole may be vulnerable as lower-tier suppliers may not be able to adopt BIM. There is currently no objective approach to assessing BIM maturity; hence, this paper aims to develop a new approach to determine suppliers’ current vision and execution-based capabilities to exploit BIM and their capacity to reach a higher maturity level.Design/methodology/approachBased on UK Government BIM maturity levels, the authors exploit a unique data set made available by a main contractor, to determine a data-driven approach, using K-means, to assess the capabilities and vision of its supply base.FindingsThe authors find a direct comparison between our suggested K-means clusters and the UK Government’s BIM maturity levels. However, in interrogating specific cases, the authors find that using a subjective approach would have wrongly categorized certain companies. The authors also determine what capability and strategic developments are required for companies to move to a higher level.Research limitations/implicationsThe method aligns with the existing UK BIM maturity model and enhances the model by determining the likelihood of a supplier in progressing to a higher level of maturity. The research was with a single case company, exploiting their existing survey instrument and data. A more comprehensive study could be adopted with a generic survey questionnaire.Practical implicationsThe research may be exploited by companies to take a strategic approach to assess suppliers in BIM adoption and to establish supplier development mechanisms.Originality/valueThe data-driven approach avoids ambiguity of categories and mis-categorizing suppliers.

The time course of contextual cohort effects in auditory processing of category-ambiguous words: MEG evidence for a single “clash” as noun or verb

ABSTRACTThe size and probability distribution of a word-form’s cohort of lexical competitors influence auditory processing and can be constrained by syntactic category information. This experiment employs noun/verb homonyms (e.g. “ache”) presented in syntactic context to clarify the mechanisms and representations involved in context-based cohort restriction. Implications for theories positing single versus multiple word-forms in cases of category ambiguity also arise. Using correlations between neural activity in auditory cortex, measured by magnetoencephalography (MEG), and standard and context-dependent cohort entropy and phoneme surprisal variables, we consider the possibility of cohort restriction on the basis of form or on the basis of category usage. Crucially, the form-conditional measure is consistent only with a single word-form view of category ambiguity. Our results show that noun/verb homonyms are derived from single category-neutral word-forms and that the cohort is restricted incrementally in context, by form and then by usage.

Understanding the Uncanny: Both Atypical Features and Category Ambiguity Provoke Aversion toward Humanlike Robots.

Robots intended for social contexts are often designed with explicit humanlike attributes in order to facilitate their reception by (and communication with) people. However, observation of an “uncanny valley”—a phenomenon in which highly humanlike entities provoke aversion in human observers—has lead some to caution against this practice. Both of these contrasting perspectives on the anthropomorphic design of social robots find some support in empirical investigations to date. Yet, owing to outstanding empirical limitations and theoretical disputes, the uncanny valley and its implications for human-robot interaction remains poorly understood. We thus explored the relationship between human similarity and people's aversion toward humanlike robots via manipulation of the agents' appearances. To that end, we employed a picture-viewing task (Nagents = 60) to conduct an experimental test (Nparticipants = 72) of the uncanny valley's existence and the visual features that cause certain humanlike robots to be unnerving. Across the levels of human similarity, we further manipulated agent appearance on two dimensions, typicality (prototypic, atypical, and ambiguous) and agent identity (robot, person), and measured participants' aversion using both subjective and behavioral indices. Our findings were as follows: (1) Further substantiating its existence, the data show a clear and consistent uncanny valley in the current design space of humanoid robots. (2) Both category ambiguity, and more so, atypicalities provoke aversive responding, thus shedding light on the visual factors that drive people's discomfort. (3) Use of the Negative Attitudes toward Robots Scale did not reveal any significant relationships between people's pre-existing attitudes toward humanlike robots and their aversive responding—suggesting positive exposure and/or additional experience with robots is unlikely to affect the occurrence of an uncanny valley effect in humanoid robotics. This work furthers our understanding of both the uncanny valley, as well as the visual factors that contribute to an agent's uncanniness.

Significant Change Spotting for Periodic Human Motion Segmentation of Cleaning Tasks Using Wearable Sensors.

The proportion of the aging population is rapidly increasing around the world, which will cause stress on society and healthcare systems. In recent years, advances in technology have created new opportunities for automatic activities of daily living (ADL) monitoring to improve the quality of life and provide adequate medical service for the elderly. Such automatic ADL monitoring requires reliable ADL information on a fine-grained level, especially for the status of interaction between body gestures and the environment in the real-world. In this work, we propose a significant change spotting mechanism for periodic human motion segmentation during cleaning task performance. A novel approach is proposed based on the search for a significant change of gestures, which can manage critical technical issues in activity recognition, such as continuous data segmentation, individual variance, and category ambiguity. Three typical machine learning classification algorithms are utilized for the identification of the significant change candidate, including a Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Naive Bayesian (NB) algorithm. Overall, the proposed approach achieves 96.41% in the F1-score by using the SVM classifier. The results show that the proposed approach can fulfill the requirement of fine-grained human motion segmentation for automatic ADL monitoring.

A comparative assessment of the poverty impacts of pond and cage aquaculture in Ghana

Aquaculture is being promoted for poverty reduction in Low Income Countries. Theoretically, aquaculture can impact poverty directly by increasing income and food security of poor fish farming households, and indirectly by generating food and economic growth. However, there is limited empirical evidence of aquaculture significantly impacting poverty, especially in sub-Saharan Africa. The emerging paradigm in aquaculture development argues that indirect poverty impacts from commercial small and medium enterprises (SMEs) are greater than direct poverty impacts on small-scale producers. This paper assesses the potential poverty impacts of small-scale pond aquaculture and SME cage aquaculture in Ghana, comparing the relative significance of their direct and indirect impacts. Non-poor small-scale pond fish farmers who have been trained and/or use better management practices (BMPs) (termed fish farming type A) are found to hold the most potential to impact poverty indirectly through generating economic growth. These indirect impacts are higher than the direct impacts on poor small-scale fish farmers and the indirect impacts from SMEs. The findings support the current move away from a narrow focus on poor producers. However, it is unclear whether the arguments for expanding support to include SMEs are fully supported due to the ambiguity of standard fish farmer categories. If type A fish farmers are categorised as ‘commercial micro enterprises’ the findings support the paradigm shift. However, it is more likely that these farmers lie between ‘non commercial’ and ‘commercial’ categories. A more nuanced approach to aquaculture development, accounting for the wide spectrum of farmers whose characteristics differ between contexts, is required.

Public challenge and endorsement of sex category ambiguity in online debate: 'The sooner people stop thinking that gender is a matter of choice the better'.

Despite academic feminist debate over several decades, the binary nature of sex as a (perhaps the) primary social classification is often taken for granted, as is the assumption that individuals can be unproblematically assigned a biological sex at birth. This article presents analysis of online debate on the BBC news website in November 2013, comprising 864 readers' responses to an article entitled ‘Germany allows ‘indeterminate’ gender at birth’. It explores how discourse reflecting Western essentialist beliefs about people having one sex or ‘the other’ is maintained in debates conducted in this online public space. Comments were coded thematically and are presented under five sub‐headings: overall evaluation of the German law; discussing and disputing statistics and ‘facts’; binary categorisations; religion and politics; and ‘conversations’ and threads. Although for many the mapping of binary sex onto gender was unquestionable, this view was strongly disputed by commentators who questioned the meanings of ‘natural’ and ‘normal’, raised the possibility of removing societal binary male‐female distinctions or saw maleness–femaleness as a continuum. While recognising that online commentators are anonymous and can control their self‐presentation, this animated discussion suggests that social classifications as male or female, even if questioned, remain fundamental in public debate in the early 21st century.

Dispensing pleasantries? Responding to legitimacy and reputation in online medical marijuana marketing

PurposeThe purpose of this paper is to develop theory regarding reputation and legitimacy signaling by organizations in contested emerging fields characterized by category ambiguity. Because impression management becomes increasingly important as category boundaries become fuzzy, the authors examine how highly participatory audiences in contested emerging fields respond to organizational attempts to seek acceptance and manage impressions.Design/methodology/approachUsing a database of web-based advertisements by 1,226 medical marijuana dispensaries, the authors test the effect that dispensary attempts to signal either legitimacy or reputation have on audience approval.FindingsThe authors find that audiences react differently to communication strategies intended to build reputation vs those intended to build legitimacy. Under conditions of highly contested category legitimation, audiences respond positively to signals of legitimacy but negatively to signals of reputation.Originality/valueThis study advances the understanding of category emergence and category building under conditions of contestation. The study adds to the growing body of work that suggests category creation involves unique collaborative processes between organizations and audiences, and the authors show that these processes constrain organizational attempts at impression management.

Understanding the robot: Comments on Goudey and Bonnin (2016)

Goudey and Bonnin provide an important demonstration of our willingness to accept robots regardless of the degree to which they look like us. This comment seeks to expand their insights in two ways. First, by broadening our conception of what constitutes a robot, I argue that we have already accepted many non-humanoid robots, and that even robotic entities without a visual presence can be compelling and engaging. Second, I suggest expanding the original paper’s psychological treatment of category ambiguity through the anthropological treatment of Mary Douglas. Douglas suggests that category ambiguity is abhorrent because things perceived to transgress categorical boundaries challenge our cultural beliefs and social order. In the case of robots, the beliefs that are challenged are our basic understandings of what makes humans unique and privileged in the world. As machines grow more and more capable, by some accounts they threaten to eclipse and even supplant the human race. I identify several behavioral and ethical research issues that are imperative if we are to deal with and prepare for such possibilities.

Beyond Gangnam Style: The Global Diffusion of Korean Pop Culture

As Korean popular culture has achieved success in global markets over the past decade, most notably with Psy’s “Gangnam Style,” the global diffusion of Korean popular culture has become a phenomenon of great interest to management scholars. However, as of yet, there is a dearth of research that examines the phenomenon in business scholarship. This symposium brings together four presentations that will advance the study of this exciting phenomenon from many angles: 1) how cultural distance can explain the outcomes of Korean pop culture in global markets, 2) how K-pop producers incorporate foreign creative content to increase the chances of a product’s success, 3) how K-pop producers learn and strategize in the ambiguous environment of cultural industries, and 4) a practitioner’s view on the global diffusion of Korean pop culture. By incorporating both academic and practitioner perspectives that investigate the production and market processes of the Korean pop culture’s global expansion, this symposium contributes to multiple literatures in international management, organizational theory, and strategy. Control and Conceal: Open networks and leveraging foreign copyrights among the K-pop songwriters Presenter: Yonghoon G Lee; Hong Kong U. of Science and Technology The Diffusion of Korean Pop Culture: What Determines the Popularity of Foreign Cultural Products? Presenter: Heeyon Kim; National U. of Singapore Presenter: Chi-Nien Chung; National U. of Singapore How Individual Market Strategies and Performance Increase Category Ambiguity: The Case of K-Pop Presenter: Youjin Jenna Song; Columbia Business School Presenter: Damon J Phillips; Columbia Business School Presenter: Jaeyong Song; Seoul National U.