Primitive Concepts Research Articles

Arithmetization-oriented APN permutations

AbstractRecently, many cryptographic primitives such as homomorphic encryption (HE), multi-party computation (MPC) and zero-knowledge (ZK) protocols have been proposed in the literature which operate on the prime field $${\mathbb {F}}_p$$ F p for some large prime p. Primitives that are designed using such operations are called arithmetization-oriented primitives. As the concept of arithmetization-oriented primitives is new, a rigorous cryptanalysis of such primitives is yet to be done. In this paper, we investigate arithmetization-oriented APN functions. More precisely, we investigate APN permutations in the CCZ-classes of known families of APN power functions over the prime field $${\mathbb {F}}_p$$ F p . Moreover, we present a class of binomial permutation having differential uniformity at most 5 defined via the quadratic character over finite fields of odd characteristic. Computationally it is confirmed that the latter family contains new APN permutations for some small parameters. We conjecture it to contain an infinite subfamily of APN permutations.

Methods to Enable Evolvable Digital Twins for Flexible Automated Production Systems

Changing requirements cause flexible automated Production Systems (aPS) to evolve over decades. Digital Twins (DT) of the different hierarchy levels and design steps ease this evolution, e.g., by enabling requirement analysis and compatibility checks ahead of any physical changes. To ensure up-to-date models and integrate additional knowledge, information gained during operation is included in DTs. Consequently, evolvability, decomposability, control software modularity, and learning during operation are identified as four requirements to achieve such evolvable DTs. Concepts to realize every requirement are introduced and exemplarily validated using a demonstrator machine. AutomationML (AML), the XML-based vendor neutral language for information modeling and exchange in between different disciplines and their tools and product classification systems like ECLASS that specify components attributes vendor neutral enable evolvability during the design phase. Decomposability is achieved by assembling DTs of components according to ISA 88 levels from control unit to facility. A control primitive concept that realizes control software modularity is introduced and validated. Based on data analytics and operation data the DT can be updated by using the versioning mechanism of AML. Thereby, the DT for the next machine generation is improved with knowledge from operation and represents the already existing machine more precisely.

The Sum Relation as a Primitive Concept of Mereology

The Sum Relation as a Primitive Concept of Mereology

The cum-sine pattern in German child language: An argument for antonym decomposition

ABSTRACT German-speaking children between ages 2 and 3 mostly use the preposition ohne (‘without’) in an adult-like way, to express the absence of something. In this article we present surprising results from a corpus study suggesting that in this age group, absence can also be expressed using the sequence mit ohne ‘with without’. We argue that this pattern becomes much less surprising if we assume that there is a conceptual representation independent of linguistic structure and that antonymic concepts such as that of absence (which we call sine in this article) are not represented as primitive concepts at this level—contrary to what might be suspected on the basis of monomorphemic prepositions such as German ohne. Instead, we argue that antonymic concepts like that of absence (sine) are composed of at least two units. Children’s non-adult-like patterns then result from difficulties in acquiring the morphological realization of this complex concept as the monomorphemic preposition ohne. To our knowledge, our results constitute the first evidence for antonym decomposition in the case of prepositions from child language.

New perspectives for piezoelectric material-based cochlear implants: getting to nano

Sensorineural hearing loss (SNHL) occurs when the sound transduction mechanism in the inner ear is compromised, because of impairments affecting the sensory hair cells—the actual biological transducers (90% of cases)—or the neurons. SNHL results in a broad spectrum of developmental, cognitive and psycho-social damages. To date, only cochlear implants (CIs) can offer a therapeutic solution to patients. They are multi-component electronic devices, surgically implanted, which capture, elaborate and convert the sound into electric stimuli delivered to the cochlea. Due to inherent limitations of the current electronic-based CIs, a new class of devices has been envisioned, which is based on piezoelectric materials. However, using piezoelectric membranes, the obtained sensitivity was not enough. The new frontiers for piezoelectric material-based CI aim at synergizing micro/nanofabrication aided by multiscale materials modeling with an in vivo tissue engineering approach to provide an implantable biomaterial-based system for SNHL, acting as a next-generation CI. Specifically, the envisioned device will move forward the primitive concept of bulk-structured piezoelectric CIs by designing a nanostructured material (e.g., based on nanofibers) to be precisely delivered and be intimately and efficiently integrated with the cochlear microenvironment. Piezoelectric material-based CIs are indeed hypothesized to have a much higher resolution of electrical stimulation with more than hundreds of channels, compared to maximum 22 stimulating elements present in electronic-based CIs. Moreover, the stimulation site will be closest to peripheral nerve fiber endings for maximal resolution. This would be the first sensory implant with a feedback mechanism on a micrometer scale.

Metarepresenting in communication

The standard cognitive explanation for the emergence of human communication is that it rests largely on the expression and attribution of communicative intentions which are, in turn, enabled by complex metarepresentations of mental states. This complexity is at odds with the limited metapsychological abilities of infants. But mentalistic metarepresentations are neither necessary nor sufficient in explaining communication. Coded ostensive signals (e.g., eye contact) and established channels (e.g., speech) allow that communicative episodes be identified through decoding rather than metarepresentational inferences. Thus, some metarepresentations may be unnecessary. However, metapsychology is also insufficient for explaining communication: the logic of instrumental actions permits interpreting their effect as following from intentions, yet the effect of communicative actions is often unavailable for inferring meaning. Moreover, current evidence for the developmental trajectory of communication and mental state attribution does not support the emergence of the former from the latter. My proposal is that our primitive concept of communication targets, instead, representational action. When we communicate, we typically convey a propositional content that is detached from our acts—a property absent in ordinary goal-directed actions. This view additionally raises the possibility that metarepresentational capacities evolved for representing external, communicative representations and were only later exapted for other purposes.

ENVIRONMENTAL REFUGE: A PERSPECTIVE OF THE ECONOMIC CONTEXT AND LEGAL RECOGNITION

Through the analysis of legal texts and official documents on the environmental refuge, it is observed that these diplomas approach the refuge only under its primitive concept, established in the Convention on the Status of Refugees, without major innovations. Moreover, the environmental refuge does not appear in legal instruments. In situations where the environment is identified as a driving factor for migration, the economic context of the affected regions is a decisive and essential element of displacement. Therefore, the research in question aims at discussing the economic context of environmental refuge, based on the cyclical phenomenon of drought in northeastern Brazil and environmental disasters in the cities of Mariana and Brumadinho. The discussion on political and social issues that enhance the damage to the environment should receive special attention in the refuge's agenda, in order to corroborate the connection between economic vulnerability and environmental refuge.

Leveraging Sub-class Discimination for Compositional Zero-Shot Learning

Compositional Zero-Shot Learning (CZSL) aims at identifying unseen compositions composed of previously seen attributes and objects during the test phase. In real images, the visual appearances of attributes and objects (primitive concepts) generally interact with each other. Namely, the visual appearances of an attribute may change when composed with different objects, and vice versa. But previous works overlook this important property. In this paper, we introduce a simple yet effective approach with leveraging sub-class discrimination. Specifically, we define the primitive concepts in different compositions as sub-classes, and then maintain the sub-class discrimination to address the above challenge. More specifically, inspired by the observation that the composed recognition models could account for the differences across sub-classes, we first propose to impose the embedding alignment between the composed and disentangled recognition to incorporate sub-class discrimination at the feature level. Then we develop the prototype modulator networks to adjust the class prototypes w.r.t. the composition information, which can enhance sub-class discrimination at the classifier level. We conduct extensive experiments on the challenging benchmark datasets, and the considerable performance improvement over state-of-the-art approaches is achieved, which indicates the effectiveness of our method. Our code is available at https://github.com/hxm97/SCD-CZSL.

A survey on geometric shape representation of objects based on medial axis transform

<div><p>Geometric shape representation algorithms are key technologies in the fields of computer graphics and geometric modeling. The Medial Axis Transform (MAT) is an important geometric model description tool that provides a simplified representation of complex geometric shapes while ensuring accurate descriptions of geometric shape and topology. Therefore, it can meet the requirements of many modern research fields, including geometric modeling, pattern recognition, model segmentation, model deformation, physical simulation, path planning, and more. This paper first introduces the basic concept of the medial axis transform, including the definition of the medial axis transform and the concept of medial axis primitives. It then describes the extraction algorithms for the medial axis transform, specific research on the medial axis transform in computer vision and computer graphics, potential applications of the medial axis transform, and medial axis transform datasets. Finally, the disadvantages and advantages of the medial axis transform are discussed, and some suggestions on possible future research directions are presented.</p></div>

WordNet-based Computation of Semantic Similarity Between Two Vietnamese Nouns

Abstract. This study aimed to measure the semantic distance between Vietnamese nouns to determine their similarities and differences in terms of semantics. The study utilized a dataset of 1000 randomly selected noun pairs from the Vietnamese WordNet and applied different semantic distance measurement formulas, such as Path-length, Leacock & Chodorow, Wu & Palmer, Resnik, Lin, and Jiang-Conrath measures. The results showed that the Resnik measure is suitable for evaluating noun similarity among primitive concepts of the same class and for measuring proximity between two classes of primitive concepts. On the other hand, the Leacock & Chodorow measure is appropriate for measuring the semantic distance between nouns belonging to two distant classes of primitive concepts. The methods used in this study have various potential applications in different fields of linguistics, such as determining synonyms, identifying semantically similar words, defining lexical-semantic fields, and detecting plagiarism.

An information theoretic score for learning hierarchical concepts.

How do humans learn the regularities of their complex noisy world in a robust manner? There is ample evidence that much of this learning and development occurs in an unsupervised fashion via interactions with the environment. Both the structure of the world as well as the brain appear hierarchical in a number of ways, and structured hierarchical representations offer potential benefits for efficient learning and organization of knowledge, such as concepts (patterns) sharing parts (subpatterns), and for providing a foundation for symbolic computation and language. A major question arises: what drives the processes behind acquiring such hierarchical spatiotemporal concepts? We posit that the goal of advancing one's predictions is a major driver for learning such hierarchies and introduce an information-theoretic score that shows promise in guiding the processes, and, in particular, motivating the learner to build larger concepts. We have been exploring the challenges of building an integrated learning and developing system within the framework of prediction games, wherein concepts serve as (1) predictors, (2) targets of prediction, and (3) building blocks for future higher-level concepts. Our current implementation works on raw text: it begins at a low level, such as characters, which are the hardwired or primitive concepts, and grows its vocabulary of networked hierarchical concepts over time. Concepts are strings or n-grams in our current realization, but we hope to relax this limitation, e.g., to a larger subclass of finite automata. After an overview of the current system, we focus on the score, named CORE. CORE is based on comparing the prediction performance of the system with a simple baseline system that is limited to predicting with the primitives. CORE incorporates a tradeoff between how strongly a concept is predicted (or how well it fits its context, i.e., nearby predicted concepts) vs. how well it matches the (ground) "reality," i.e., the lowest level observations (the characters in the input episode). CORE is applicable to generative models such as probabilistic finite state machines (beyond strings). We highlight a few properties of CORE with examples. The learning is scalable and open-ended. For instance, thousands of concepts are learned after hundreds of thousands of episodes. We give examples of what is learned, and we also empirically compare with transformer neural networks and n-gram language models to situate the current implementation with respect to state-of-the-art and to further illustrate the similarities and differences with existing techniques. We touch on a variety of challenges and promising future directions in advancing the approach, in particular, the challenge of learning concepts with a more sophisticated structure.

Davidson on Truth

"Truth-conditional semantics is by far the best-known philosophical contribution of Donald Davidson. The main idea of this approach is to explain the concept of meaning by appeal to the concept of truth. Accordingly, we understand a sentence s of a natural language L, if and only if, we know its truth-conditions. Challenging in its nature, this proposal immediately caught the attention of the philosophical community, being equally appreciated and criticized. The aim of this paper is to argue that Davidson’s approach is too optimistic in its goals. In my view, truth-conditional semantics is unlikely to be the best way to shed light on the concept of meaning. By appealing to Tarski’s semantic conception of truth and assuming a primitive concept of truth, this perspective leaves too many questions unanswered and thus proves its limits. Keywords: Donald Davidson, meaning, truth, Truth-Conditional Semantics. "

Hyperbolic linear canonical transforms of quaternion signals and uncertainty

This paper is concerned with Linear Canonical Transforms (LCTs) associated with two-dimensional quaternion-valued signals defined in an open rectangle of the Euclidean plane endowed with a hyperbolic measure, which we call Quaternion Hyperbolic Linear Canonical Transforms (QHLCTs). These transforms are defined by replacing the Euclidean plane wave with a corresponding hyperbolic relativistic plane wave in one dimension multiplied by quadratic modulations in both the hyperbolic spatial and frequency domains, giving the hyperbolic counterpart of the Euclidean LCTs. We prove the fundamental properties of the partial QHLCTs and the right-sided QHLCT by employing hyperbolic geometry tools and establish main results such as the Riemann–Lebesgue Lemma, the Plancherel and Parseval Theorems, and inversion formulas. The analysis is carried out in terms of novel hyperbolic derivative and hyperbolic primitive concepts, which lead to the differentiation and integration properties of the QHLCTs. The results are applied to establish two quaternionic versions of the Heisenberg uncertainty principle for the right-sided QHLCT. These uncertainty principles prescribe a lower bound on the product of the effective widths of quaternion-valued signals in the hyperbolic spatial and frequency domains. It is shown that only hyperbolic Gaussian quaternion functions minimize the uncertainty relations.

TERMINOLOGIA ESPECIALIZADA DE ENFERMAGEM PARA O CUIDADO DE PESSOAS COM LEISHMANIOSE VISCERAL

ABSTRACT Objective: to create specialized Nursing terminology for the care of people with Visceral Leishmaniasis. Method: a methodological study carried out in two stages: identification of the relevant concepts in medical records of patients with chosen health priority admitted between 2017 and 2019 to a public and teaching hospital in the north of Minas Gerais, BR; cross-mapping of the concepts identified with the ICNP®. Results: a total of 57,797 simple and compound (with repetitions) concepts, were extracted, of which 624 were useful single concepts for the Nursing care to be provided to people with Visceral Leishmaniasis. 281 (45%) primitive concepts were identified as included in ICNP® 2019-2020, as well as 343 (55%) not included in the classification. The concepts related to Focus and Location stood out in the axes. Conclusions: a specialized ICNP® terminology was created for the care of people with Visceral Leishmaniasis, with potential impacts on the standardization of actions and on generation of indicators sensitive to the Nursing practice.

Core issues, case studies, and the need for expanded Legacy African American genomics.

Introduction: Genomic studies of Legacy African Americans have a tangled and convoluted history in western science. In this review paper, core issues affecting African American genomic studies are addressed and two case studies, the New York African Burial Ground and the Gullah Geechee peoples, are presented to highlight the current status of genomic research among Africa Americans. Methods: To investigate our target population's core issues, a metadatabase derived from 22 publicly accessible databases were reviewed, evaluated, and synthesized to identify the core bioethical issues prevalent during the centuries of the African American presence in North America. The sequence of metadatabase development included 5 steps: identification of information, record screening and retention of topic relevant information, identification of eligibility via synthesis for concept identifications, and inclusion of studies used for conceptual summaries and studies used for genetic and genomic summaries. To these data we added our emic perspectives and specific insights from our case studies. Results: Overall, there is a paucity of existing research on underrepresent African American genomic diversity. In every category of genomic testing (i.e., diagnostic, clinical predictive, pharmacogenomic, direct-to-consumer, and tumor testing), African Americans are disproportionately underrepresented compared to European Americans. The first of our case studies is from the New York African Burial Ground Project where genomic studies of grave soil derived aDNA yields insights into the causes of death of 17th and 18th Century African Americans. In the second of our case studies, research among the Gullah Geechee people of the Carolina Lowcountry reveals a connection between genomic studies and health disparities. Discussion: African Americans have historically borne the brunt of the earliest biomedical studies used to generate and refine primitive concepts in genetics. As exploited victims these investigations, African American men, women, and children were subjected to an ethics-free western science. Now that bioethical safeguards have been added, underrepresented and marginalized people who were once the convenient targets of western science, are now excluded from its health-related benefits. Recommendations to enhance the inclusion of African Americans in global genomic databases and clinical trials should include the following: emphasis on the connection of inclusion to advances in precision medicine, emphasis on the relevance of inclusion to fundamental questions in human evolutionary biology, emphasis on the historical relevance of inclusion for Legacy African Americans, emphasis on the ability of inclusion to foster expanded scientific expertise in the target population, ethical engagement with their descendants, and increase the number of science researchers from these communities.

On the geometry of physical measurements: Topological and algebraic aspects

We study the mathematical structure of the notion of measurement space, which extends aspects of noncommutative topology that are based on quantale theory. This yields a geometric model of physical measurements that provides a realist picture, yet also operational, such that measurements and classical information arise interdependently as primitive concepts. A derived notion of classical observer caters for a mathematical formulation of Bohr's classical/quantum divide. Two important classes of measurement spaces are obtained, respectively from C*-algebras and from second-countable locally compact open sober topological groupoids. The latter yield measurements of classical type and relate to Schwinger's notion of selective measurement. We show that the measurement space associated to the reduced C*-algebra of any second-countable locally compact Hausdorff étale groupoid is canonically equipped with a classical observer, and we establish a correspondence between properties of the observer and properties of the groupoid.

Schrödinger's Cat Meets Occam's Razor.

We discuss V.P. Belavkin's approach to the Schrödinger cat problem and show its close relation to ideas based on superselection and interaction with the environment developed by N.P. Landsman. The purpose of the paper is to explain these ideas in the most simple possible context, namely: discrete time and separable Hilbert spaces, in order to make them accessible to those coming from the philosophy of science and not too happy with idiosyncratic notation and terminology and sophisticated mathematical tools. Conventional elementary mathematical descriptions of quantum mechanics take "measurement" to be a primitive concept. Paradoxes arise when we choose to consider smaller or larger systems as measurement devices in their own right, by making different and apparently arbitrary choices of location of the "Heisenberg cut". Various quantum interpretations have different resolutions of the paradox. In Belavkin's approach, the classical world around us does really exist, and it evolves stochastically and dynamically in time according to probability laws following from successive applications of the Born law. It is a collapse theory. The quantum/classical distinction is determined by the arrow of time. The underlying unitary evolution of the wave-function of the universe enables the designation of a collection of beables which grows as time evolves, and which therefore can be assigned random, classical trajectories. In a slogan: the past is particles, the future is a wave. We, living in the now, are located on the cutting edge between past and future.

Architectural modelling for robotics: RoboArch and the CorteX example.

The need for robotic systems to be verified grows as robots are increasingly used in complex applications with safety implications. Model-driven engineering and domain-specific languages (DSLs) have proven useful in the development of complex systems. RoboChart is a DSL for modelling robot software controllers using state machines and a simple component model. It is distinctive in that it has a formal semantics and support for automated verification. Our work enriches RoboChart with support for modelling architectures and architectural patterns used in the robotics domain. Support is in the shape of an additional DSL, RoboArch, whose primitive concepts encapsulate the notion of a layered architecture and architectural patterns for use in the design of the layers that are only informally described in the literature. A RoboArch model can be used to generate automatically a sketch of a RoboChart model, and the rules for automatic generation define a semantics for RoboArch. Additional patterns can be formalised by extending RoboArch. In this paper, we present RoboArch, and give a perspective of how it can be used in conjunction with CorteX, a software framework developed for the nuclear industry.

Alternatives to QUD

Abstract The paper critically examines some central principles of the Question Under Discussion (QUD) framework and ultimately explores the concept of ‘question’, central to QUD-models. It demonstrates how fine-grained, interactionally informed analyses of language-specific categories can reveal building blocks of interaction and explain the sources of the observed information- and discourse-structuring interpretations (such as update, contrast and more). Employing data from Anal Naga (Trans-Himalayan, India), it proceeds to a fine-grained analysis of the notion of ‘question’. The decomposition of ‘questions’ into smaller building blocks similarly reveals how diverse categories and discourse processes can trigger the interpretation of an information request. These findings and additional theoretical arguments suggest that QUD-models are problematic for various reasons: such models are non-parsimonious as they add superfluous extra layers to explain the observations; the explanatory apparatus is circular, as the extra layers are derived from within the explananda but regarded as underlying explanatory factors; and the models gloss over the actual factors by channelling them into cover terms prematurely regarded as primitive. Finally, since ‘question’ does not constitute a primitive concept but is a product of diverse discourse processes, discourse cannot be modelled on this foundation.

Relation-Aware Compositional Zero-Shot Learning for Attribute-Object Pair Recognition

This paper proposes a novel model for recognizing images with composite attribute-object concepts, notably for composite concepts that are unseen during model training. We aim to explore the three key properties required by the task --- relation-aware, consistent, and decoupled --- to learn rich and robust features for primitive concepts that compose attribute-object pairs. To this end, we propose the Blocked Message Passing Network (BMP-Net). The model consists of two modules. The concept module generates semantically meaningful features for primitive concepts, whereas the visual module extracts visual features for attributes and objects from input images. A message passing mechanism is used in the concept module to capture the relations between primitive concepts. Furthermore, to prevent the model from being biased towards seen composite concepts and reduce the entanglement between attributes and objects, we propose a blocking mechanism that equalizes the information available to the model for both seen and unseen concepts. Extensive experiments and ablation studies on two benchmarks show the efficacy of the proposed model.