Concept Hierarchy Research Articles

Interrogating Hierarchies to Build a Humanitarian Literacy Research Architecture: Multiple Perspectives

This year's conference theme was a collective invitation to face how we, as a literacy research collective, may have played a role in marginalization and disenfranchisement and the further promotion and perpetuation of conceptual and linguistic hierarchies. The conference theme also became an invitation to propose ways to counter these existing hierarchies and how we use research as part of that solution. That was the spirit behind this year's Integrative Research Review Panel. This panel brought together five scholars, encompassing four perspectives, to tackle this year's conference theme of “Interrogating Hierarchies.” The four papers approached the conversation about hierarchies from research on Black writing, English as a global affair, the science of reading, and social design-based experiments, not only outlining the pressing issues but also proposing solutions that our research community can embrace. As we read the four papers comprising this panel, it is worth pointing out how, despite the divergent departure points that each panelist's work represents, the four papers organically lay out a series of agreements about the need to rethink how we conceive English to avoid disenfranchisement, the importance of valuing minoritized and marginalized voices to rethink literacy, and the challenges to align our research with advocacy efforts.

Analysis on Applications of Mind Map in English Writing Teaching

At the present stage, the teaching activities aim at promoting students’ learning quality and creative accomplishments. This demands teachers to create more teaching activities to facilitate students’ creative potential. As an efficient tool for thinking, mind map can achieve the visualization of thinking through presenting the hierarchy of concepts and the sequence of thinking. Naturally, it will be helpful to promote both students’ creativity and memory. It also can arouse students’ writing interest and cultivate students’ logical thinking ability. Therefore, this paper is going to have a brief introduce in the problems existing in students’ English writing. Furthermore, it will improve students’ English writing ability by applying mind map during the writing teaching process. Last but not least, it can arouses students’ critical thinking.

Not all money is created equal: The concept of a hierarchy of money

Abstract The concept of a hierarchy of money or the idea that a number of instruments constitute money and that they are hierarchically related to one another is relatively recent and yet quite widespread. However, it is argued, that its comprehension differs. The most elaborated cases in which differing treatments of the term can be found are Modern Money Theory (MMT) and the Money View. At first sight, the MMT’s model of money hierarchy focuses on a hierarchy within a specific unit of account whereas the Money View perceives hierarchy not only within an individual unit of account but also across various units of accounts. But, as is shown, differences are more fundamental. It is argued that different comprehension can be explained by the different distinctions between money and credit and concept of monetary sovereignty within each approach rather than the concept of hierarchy itself. The concept of hierarchy acts, in fact, as a framework that ensures consistency in the use of different money instruments on those level.

Modeling the skeleton-language uncertainty for 3D action recognition

Human 3D skeleton-based action recognition has received increasing interest in recent years. Inspired by the excellent ability of the multi-modal model, some pioneer attempts to employ diverse modalities, i.e., skeleton and language, to construct the skeleton-language model and have shown compelling results. Yet, these attempts model the data representation as deterministic point estimation, ignoring a key issue that descriptions of similar motions are uncertain and ambiguous, which brings about restricted comprehension of complex concept hierarchies and impoverished cross-modal alignment reliability. To tackle this challenge, this paper proposes a new Uncertain Skeleton-Language Learning Framework (USLLF) to capture the semantic ambiguity among diverse modalities in a probabilistic manner for the first time. USLLF consists of both inter- and intra-modal uncertainties. Specifically, first, we integrate the language (text) generated by ChatGPT with the generic skeleton-based network and develop a deterministic multi-modal baseline, which can be easily achieved via any off-the-shelf skeleton and text encoders. Then, based on this baseline, we explicitly model the intra-modal (skeleton/language) uncertainties as the Gaussian distributions using the new uncertainty networks capable of learning the distributional embeddings of modalities. Following this, these embeddings are aligned and formulated as inter-modal (skeleton-language) uncertainty using both the contrastive and negative log-likelihood objectives to alleviate the cross-modal alignment error. Experimental results on NTU RGB+D, NTU RGB+D 120, and NW-UCLA datasets show that our approach outperforms the proposed baseline and achieves comparable performance with a high inference efficiency compared to the state-of-the-art methods. Besides, we also deliver insightful analyses on how learned uncertainty reduces the impact of uncertain and ambiguous data on model performance.

"Everything is in order, but in a different way": reinterpretation of the Areopagite concept of hierarchy

"Order", "subordination", "power", "repression" are the phenomena with which the concept of "hierarchy" is most often associated. As far as we know, the term "hierarchy" is found for the first time in the Areopagite corpus. After a hermeneutic analysis of the definition of hierarchy in its first usage, a number of some new and not so obvious meanings are revealed: hierarchy is not only an order, but also a knowledge, an action (or energy) and an imitation of God, it is associated with a difference in the nature of things, but at the same time it is dynamic, not static. In the basis of the central role the concept of "Divine action (or energy)" plays in describing hierarchy, we argue that in the Areopagitics can be traced the procedural logic of the Arab-Muslim world, rather than the substantial logic of the Greek-Western European world. An explanation of this paradox is proposed based on the commensurability of the Areopagite and Akbari traditions, which is confirmed by historical data.

Predicting Future Disorders via Temporal Knowledge Graphs and Medical Ontologies.

Despite the vast potential for insights and value present in Electronic Health Records (EHRs), it is challenging to fully leverage all the available information, particularly that contained in the free-text data written by clinicians describing the health status of patients. The utilization of Named Entity Recognition and Linking tools allows not only for the structuring of information contained within free-text data, but also for the integration with medical ontologies, which may prove highly beneficial for the analysis of patient medical histories with the aim of forecasting future medical outcomes, such as the diagnosis of a new disorder. In this paper, we propose MedTKG, a Temporal Knowledge Graph (TKG) framework that incorporates both the dynamic information of patient clinical histories and the static information of medical ontologies. The TKG is used to model a medical history as a series of snapshots at different points in time, effectively capturing the dynamic nature of the patient's health status, while a static graph is used to model the hierarchies of concepts extracted from domain ontologies. The proposed method aims to predict future disorders by identifying missing objects in the quadruple 〈s, r, ?, t 〉, where s and r denote the patient and the disorder relation type, respectively, and t is the timestamp of the query. The method is evaluated on clinical notes extracted from MIMIC-III and demonstrates the effectiveness of the TKG framework in predicting future disorders and of medical ontologies in improving its performance.

The metamorphosis of external vulnerability from ‘original sin’ to ‘original sin redux’: currency hierarchy and financial globalization in emerging economies

How has financial globalization changed the nature of external vulnerability of emerging economies? To answer this question, we first present an overview of the changes in international capital flows and cross-border stocks involving emerging economies from the 1970s to the COVID-19 crisis and then identify relevant recent shifts in financial globalization. We adapt the concept of currency hierarchy to the most recent features of financial globalization. We deploy a stylized balance sheet analysis to better understand the metamorphosis of these economies’ vulnerabilities. We find the occurrence of the phenomenon of ‘original sin’ during financial internationalization. In contrast, in more recent times of financial globalization, the diversification of financial flows and investors and the increase of securities denominated in domestic currency have created additional channels of vulnerability, labeled as ‘original sin redux’. We find that the private sector in Southern economies is mostly exposed to these new vulnerabilities. At first sight, it is good news because it preserves the fiscal space of Southern States in the case of capital outflows. However, it might create new contingent liabilities for the public sector. We call for capital account regulation in a broad sense to target these new complex vulnerabilities.

Contextualizing urban road network hierarchy and its role for sustainable transport futures: A systematic literature review using bibliometric analysis and content analysis tools

AbstractUrban road networks play a crucial role in transport and urban planning and have the potential to contribute to more sustainable futures if their hierarchy is properly understood. However, the concept of the urban road network hierarchy, which refers to street classification and prioritization, is not well defined within the domain of transport engineering management, leaving many questions unanswered. Is it simply a planning tool, or does it extend to defining the essence of cities? Is it a qualitative or quantitative concept? Does it emerge organically or require proactive planning? Given the lack of comprehensive answers to these questions, this research aims to provide a contextual understanding of the urban road network hierarchy through the lens of sustainable transport futures. To this purpose, we conducted a systematic literature review, which is an effective method for consolidating knowledge on a specific topic. A total of 42 articles were analyzed using both quantitative bibliometric analysis and qualitative content analysis. Our work demonstrates that the road network hierarchy consists of 16 sub-concepts. Four main research trends were identified and discussed: a) road morphology and structure, b) advanced algorithms for street classification, c) integrated street classification planning, and d) the social dimension of street classification. Recent literature indicates a shift toward alternative road network hierarchy approaches that prioritize sustainable mobility over car-centric models. In conclusion, our analysis reveals that the urban road network hierarchy is a multifaceted yet under researched “vehicle for change,” which, if utilized effectively, offers opportunities to reimagine urban road environments.

Bio-inspired gradient poly(lactic acid) nanofibers for active capturing of PM0.3 and real-time respiratory monitoring

The concept of bio-inspired gradient hierarchies, in which the well-defined MOF nanocrystals serve as active nanodielectrics to create electroactive shell at poly(lactic acid) (PLA) nanofibers, is introduced to promote the surface activity and electroactivity of PLA nanofibrous membranes (NFMs). The strategy enabled significant refinement of PLA nanofibers during coaxial electrospinning (∼40 % decline of fiber diameter), accompanied by remarkable increase of specific surface area (nearly 1.5 m2/g), porosity (approximately 85 %) and dielectric constants for the bio-inspired gradient PLA (BG-PLA) NFMs. It largely boosted initial electret properties and electrostatic adsorption capability of BG-PLA NFMs, as well as charge regeneration by TENG mechanisms even under high-humidity environment. The BG-PLA NFMs thus featured exceptionally high PM0.3 filtration efficiencies with well-controlled air resistance (94.3 %, 163.4 Pa, 85 L/min), in contrast to the relatively low efficiency of only 80.0 % for normal PLA. During the application evaluation of outdoor air purification, excellent long-term filtering performance was demonstrated for the BG-PLA for up to 4 h (nearly 98.0 %, 53 Pa), whereas normal PLA exhibited a gradually declined filtration efficiency and an increased pressure drop. Moreover, the BG-PLA NFMs of increased electroactivity were ready to generate tribo-output currents as driven by respiratory vibrations, which enabled real-time monitoring of electrophysiological signals. This bio-inspired gradient strategy opens up promising pathways to engender biodegradable nanofibers of high surface activity and electroactivity, which has significant implications for intelligent protective membranes.

Research on domain ontology construction based on the content features of online rumors

Online rumors are widespread and difficult to identify, which bring serious harm to society and individuals. To effectively detect and govern online rumors, it is necessary to conduct in-depth semantic analysis and understand the content features of rumors. This paper proposes a TFI domain ontology construction method, which aims to achieve semantic parsing and reasoning of the rumor text content. This paper starts from the term layer, the frame layer, and the instance layer, and based on the reuse of the top-level ontology, the extraction of core literature content features, and the discovery of new concepts in the real corpus, obtains the core classes (five parent classes and 88 subclasses) of the rumor domain ontology and defines their concept hierarchy. Object properties and data properties are designed to describe relationships between entities or their features, and the instance layer is created according to the real rumor datasets. OWL language is used to encode the ontology, Protégé is used to visualize it, and SWRL rules and pellet reasoner are used to mine and verify implicit knowledge of the ontology, and judge the category of rumor text. This paper constructs a rumor domain ontology with high consistency and reliability.

Knowledge-guided generative artificial intelligence for automated taxonomy learning from drug labels.

To automatically construct a drug indication taxonomy from drug labels using generative Artificial Intelligence (AI) represented by the Large Language Model (LLM) GPT-4 and real-world evidence (RWE). We extracted indication terms from 46421 free-text drug labels using GPT-4, iteratively and recursively generated indication concepts and inferred indication concept-to-concept and concept-to-term subsumption relations by integrating GPT-4 with RWE, and created a drug indication taxonomy. Quantitative and qualitative evaluations involving domain experts were performed for cardiovascular (CVD), Endocrine, and Genitourinary system diseases. 2909 drug indication terms were extracted and assigned into 24 high-level indication categories (ie, initially generated concepts), each of which was expanded into a sub-taxonomy. For example, the CVD sub-taxonomy contains 242 concepts, spanning a depth of 11, with 170 being leaf nodes. It collectively covers a total of 234 indication terms associated with 189 distinct drugs. The accuracies of GPT-4 on determining the drug indication hierarchy exceeded 0.7 with "good to very good" inter-rater reliability. However, the accuracies of the concept-to-term subsumption relation checking varied greatly, with "fair to moderate" reliability. We successfully used generative AI and RWE to create a taxonomy, with drug indications adequately consistent with domain expert expectations. We show that LLMs are good at deriving their own concept hierarchies but still fall short in determining the subsumption relations between concepts and terms in unregulated language from free-text drug labels, which is the same hard task for human experts.

Pre-school teachers' digital concept maps and instructional design practices

Concept mapping has been a useful and effective technique for representing and assessing science content knowledge. Technological advances have also allowed the creation of user-friendly digital concept map applications. However, there appears a need to examine pre-service teachers' digital concept mapping practices in relation to their instructional design practices i.e. lesson planning. Hence, this study investigated the quality of pre-service pre-school teachers' (n = 26) digital concept maps in reference to the quality of their lesson plans. The quality of the digital concept maps was assessed based on an examination of the quality of a) structure, b) content, and c) their overall quality. Furthermore, it examined teachers' preferences and reflections on digital concept maps in relation to physical (i.e. paper-and-pencil) concept maps. Mixed methods were used including qualitative analysis and statistical correlations of the quality scores of the lesson plans and concept maps. Findings revealed no significant correlation between the quality of digital concept maps and the quality of lesson plans, while the consistency of the focus between the two correlated significantly with the quality of the digital concept maps. The number of concepts, propositions and cross-links as well as conceptual hierarchy were found as indicators of the overall quality of the digital concept maps. A comparison between digital and physical concept maps revealed that teachers' views and arguments varied between the two. The findings of the study speak to the relevance and applicability of digital concept maps for teacher training programmes.

The Zaghawa Ethnic Group of Sudan and Chad: Clans and Traditional Nobility

The presented article highlights the issues of the history of the Zaghawa people in Sudan and Chad, as well as major social structures and various clans that make up this ethnic group. Research on Zaghawa clans and their history is still rare in Russia, while the importance and influence of this group on public and political life are becoming more and more noticeable. A significant difficulty in determining the hierarchy of major Zaghawa factions is the identification of the “original” clans, as distinct from the clans which are treated as not having a common origin with the Zaghawa. Moreover, the ethnonyms that are used by different neighbours to designate the Zaghawa are problematic, since the designation of this people by other communities in Sudan and Chad can be contradictory and vague. The Zaghawa clans have their own historical traditions and concepts of clan hierarchy. While preparing the present work, the authors scrutinized research papers and books in multiple languages (including Arabic), as well as the first-hand data obtained during interviews with with the representatives of several Zaghawa clans.

Enhancement of acousto-optic interaction using a phoxonic cavity with structural hierarchy

We propose a phoxonic cavity with structural hierarchy to enhance acousto-optic interaction in acoustically dissipative media. In a conventional phoxonic cavity, interaction between infrared light and hypersound with the same wavelength scale became weak due to large acoustic attenuation whose coefficient is proportional to the square of the frequency. To alleviate the acoustic attenuation, it is necessary to use low-frequency sound with much longer wavelength than the infrared light, but the conventional phoxonic cavity is not suitable for confining such hypersound and infrared light simultaneously. In this study, we employ the concept of structural hierarchy into the phoxonic cavity to control infrared light and hypersound with different wavelength scales. A phoxonic cavity with two different scales achieves the acousto-optic interaction approximately 1.6 times that in the conventional one. To further enhance the interaction, we adjust geometrical constitution and material properties of the two-scale phoxonic cavity using quasi-static homogenization theory, leading to the interaction about 2.1 times that in the conventional cavity.

Coupling cloud theory and concept hierarchy construction early warning thresholds for deformation safety of tailings dam

Coupling cloud theory and concept hierarchy construction early warning thresholds for deformation safety of tailings dam

MalFox: Camouflaged Adversarial Malware Example Generation Based on Conv-GANs Against Black-Box Detectors

Deep learning is a thriving field currently stuffed with many practical applications and active research topics. It allows computers to learn from experience and to understand the world in terms of a hierarchy of concepts, with each being defined through its relations to simpler concepts. Relying on the strong capabilities of deep learning, we propose a convolutional generative adversarial network-based (Conv-GAN) framework titled MalFox, targeting adversarial malware example generation against third-party black-box malware detectors. Motivated by the rival game between malware authors and malware detectors, MalFox adopts a confrontational approach to produce perturbation paths, with each formed by up to three methods (namely Obfusmal, Stealmal, and Hollowmal) to generate adversarial malware examples. To demonstrate the effectiveness of MalFox, we collect a large dataset consisting of both malware and benignware programs, and investigate the performance of MalFox in terms of accuracy, detection rate, and evasive rate of the generated adversarial malware examples. Our evaluation indicates that the accuracy can be as high as 99.01% which significantly outperforms the other 12 well-known learning models. Furthermore, the detection rate is dramatically decreased by 45.1% on average, and the average evasive rate is noticeably improved by up to 56.0%.

The Role of Trust, Respect, and Relationships in Maintaining Lived Experience and Indigenous Authority in Co-Designed Research with People Living with Disability

Co-design of research can evolve organically when the questions to be asked have their roots deep1 in the soil of partnerships based on trust, respect, and a common vision for equity and inclusion. White Questions—Black Answers, a PhD thesis research project focusing on the inclusion of Indigenous students with disability in the Australian Higher Education Sector, demonstrates this premise. Founded on Indigenous Standpoint Theory, the methodology of this research foregrounds the central role of Indigenous people with lived experience of disability—in the study design, its implementation, and in the validation of the results. This paper shares the conceptual framework and relationship hierarchy for the research, ensuring that the authority of those with lived experience was maintained and central to all research activities. It showcases a way forward for other fields of co-designed research, delivering both academic rigour and leadership by those with lived experience.

Interactive Visual Task Learning for Robots

We present a framework for robots to learn novel visual concepts and tasks via in-situ linguistic interactions with human users. Previous approaches have either used large pre-trained visual models to infer novel objects zero-shot, or added novel concepts along with their attributes and representations to a concept hierarchy. We extend the approaches that focus on learning visual concept hierarchies by enabling them to learn novel concepts and solve unseen robotics tasks with them. To enable a visual concept learner to solve robotics tasks one-shot, we developed two distinct techniques. Firstly, we propose a novel approach, Hi-Viscont(HIerarchical VISual CONcept learner for Task), which augments information of a novel concept to its parent nodes within a concept hierarchy. This information propagation allows all concepts in a hierarchy to update as novel concepts are taught in a continual learning setting. Secondly, we represent a visual task as a scene graph with language annotations, allowing us to create novel permutations of a demonstrated task zero-shot in-situ. We present two sets of results. Firstly, we compare Hi-Viscont with the baseline model (FALCON) on visual question answering(VQA) in three domains. While being comparable to the baseline model on leaf level concepts, Hi-Viscont achieves an improvement of over 9% on non-leaf concepts on average. Secondly, we conduct a human-subjects experiment where users teach our robot visual tasks in-situ. We compare our model’s performance against the baseline FALCON model. Our framework achieves 33% improvements in success rate metric, and 19% improvements in the object level accuracy compared to the baseline model. With both of these results we demonstrate the ability of our model to learn tasks and concepts in a continual learning setting on the robot.

Interactive Visual Task Learning for Robots

We present a demonstrable framework for robots to learn novel visual concepts and visual tasks via in-situ linguistic interactions with human users. Previous approaches in computer vision have either used large pre-trained visual models to infer novel objects zero-shot, or added novel concepts along with their attributes and representations to a concept hierarchy. We extend the approaches that focus on learning visual concept hierarchies and take this ability one step further to demonstrate novel task solving on robots along with the learned visual concepts. To enable a visual concept learner to solve robotics tasks one-shot, we developed two distinct techniques. Firstly, we propose a novel approach, Hi-Viscont(HIerarchical VISual CONcept learner for Task), which augments information of a novel concept, that is being taught, to its parent nodes within a concept hierarchy. This information propagation allows all concepts in a hierarchy to update as novel concepts are taught in a continual learning setting. Secondly, we represent a visual task as a scene graph with language annotations, allowing us to create novel permutations of a demonstrated task zero-shot in-situ. Combining the two techniques, we present a demonstration on a real robot that learns visual task and concepts in one-shot from in-situ interactions with human users, and generalize to perform a novel visual task of the same type in zero-shot. As shown by the studies in the main conference paper, our system achieves a success rate of 50% on solving the whole task correctly with generalization where the baseline performs at 14% without any ability to generalize to novel tasks and concepts. We will demonstrate our working interactive learning pipeline at AAAI 2024 in person with our robot and other required hardware.

Problematising Hierarchy and Dualism for Ecological Concern: Johnsen’s Decolonial Methodology in Defence of Non-Hierarchical Worldmaking

The climate crisis presents an urgent problem for World Christianity. Since Lynn White, Jr., argued that ‘Christianity is the most anthropocentric religion the world has seen’ (White 1967), theologians have debated to what extent Christianity is responsible for ecological crisis. In this article, I will focus on two related problems for Christian thought that Majority World theologians have highlighted – hierarchy and dualism – in order to postulate what a non-hierarchical Christian worldview might entail, drawing on the work of Sámi Norwegian Lutheran theologian Tore Johnsen, primarily his recently published book Sámi Nature-Centered Christianity in the European Arctic (2022). This article utilises a multidisciplinary, World Christianity approach to theology that draws upon Johnsen’s work to examine the two themes of hierarchy and dualism, critically questioning these concepts and examining theological implications for the climate crisis. Johnsen’s research amongst the Sámi demonstrates their expression of ‘nature-centred’ Christianity that exhibits a non-hierarchical cosmology. He contrasts this with Western Christian expressions, in particular that of the Church of Norway. Johnsen’s decolonial approach questions aspects of the Western worldview critically and helpfully with reference to the climate crisis. This article therefore problematises two related concepts of hierarchy and dualism, notions which have become embedded within Christian tradition. In questioning these underlying concepts, it draws upon Johnsen’s work to consider whether and to what extent a non-hierarchical expression of Christianity might serve as a viable alternative.