Full Semantics Research Articles

HỌC BIỂU DIỄN CÂU SỬ DỤNG MÔ HÌNH LSTM TRONG BÀI TOÁN TÌM KIẾM CÂU HỎI

Learning sentence representation with the full semantics of a document is a challenge in natural language processing problems because if the semantic representation vector of the sentence is suitable, it will increase the performance of finding similar question problems. In this paper, we propose implementing a series of LSTM models with different ways of extracting sentence representations and applying them to question retrieval to exploit the hidden semantics of sentences. These methods give sentence representation from hidden layers of the LSTM model. The results show that the technique using a combination of both Max Pooling and Mean Pooling gives the highest results on the 2017 SemEval dataset for the problem of finding similarity questions. Keywords: LSTM; Deep Learning; NLP; QA; learning sentence representation; CQA.

Demystify the Fuzzing Methods: A Comprehensive Survey

Massive software applications possess complex data structures or parse complex data structures; in such cases, vulnerabilities in the software become inevitable. The vulnerabilities are the source of cyber-security threats, and discovering this before the software deployment is challenging. Fuzzing is a vulnerability discovery solution that resonates with random-mutation, feedback-driven, coverage-guided, constraint-guided, seed-scheduling, and target-oriented strategies. Each technique is wrapped beneath the black-, white-, and grey-box fuzzers to uncover diverse vulnerabilities. It consists of methods such as identifying structural information about the test cases to detect security vulnerabilities, symbolic and concrete program states to explore the unexplored locations, and full semantics of code coverage to create new test cases. We methodically examine each kind of fuzzers and contemporary fuzzers with a profound observation that addresses various research questions and systematically reviews and analyze the gaps and their solutions. Our survey comprised the recent related works on fuzzing techniques to demystify the fuzzing methods concerning the application domains and the target that, in turn, achieves higher code coverage and sound vulnerability detection.

Mechanized Proofs of Adversarial Complexity and Application to Universal Composability

In this paper we enhance the EasyCrypt proof assistant to reason about computational complexity of adversaries. The key technical tool is a Hoare logic for reasoning about computational complexity (execution time and oracle calls) of adversarial computations. Our Hoare logic is built on top of the module system used by EasyCrypt for modeling adversaries. We prove that our logic is sound w.r.t. the semantics of EasyCrypt programs — we also provide full semantics for the EasyCrypt module system, which was previously lacking. We showcase (for the first time in EasyCrypt and in other computer-aided cryptographic tools) how our approach can express precise relationships between the probability of adversarial success and their execution time. In particular, we can quantify existentially over adversaries in a complexity class, and express general composition statements in simulation-based frameworks. Moreover, such statements can be composed to derive standard concrete security bounds for cryptographic constructions whose security is proved in a modular way. As a main benefit of our approach, we revisit security proofs of some well-known cryptographic constructions and we present a new formalization of Universal Composability (UC).

Digital twin-enabled built environment sensing and monitoring through semantic enrichment of BIM with SensorML

Effective environmental condition monitoring provides constant surveillance of the built environment and reveals deteriorations that could impact the daily operation of facilities, especially amid COVID situations. However, the current Industry Foundation Classes (IFC) data schema for Building Information Modelling (BIM) provided limited support to represent full semantics related to environmental sensing and monitoring. How to semantically enrich the IFC schema with enhanced data description capability for informed decision-making in smart facilities management (FM) amid COVID situations remains an open question. This paper develops a semi-automatic extension and integration of IFC data schema with Sensor Model Language (SensorML) specification in order to support automated built environment sensing and monitoring. Referring to SensorML, an extended IFC model view definition for a comprehensive description of required sensor metadata and sensing entities is presented. An Internet of Things (IoT) sensor network is then established to realise continuous data collection from a variety of wireless sensing devices. The spatial-temporal data captured by the IoT sensor network are extracted by a regular expression-based data distillation algorithm and integrated with the digital twin, in which spatial interpolation algorithms further analyse, compute, and visualise the state of the environment. The proposed method is demonstrated via an experimental study which supports real-time environmental monitoring and delivers more actionable insights to facility managers to sustain the daily operation of buildings. This study contributes new methods and models to semantically enrich the digital twin from the data perspective for environmental condition monitoring during the pandemic time which fosters the development of holistic building facility management.

From reversible programming languages to reversible metalanguages

During the past decade reversible programming languages have been formalized using various established semantics frameworks. However, these semantics fail to effectively specify the distinct properties of reversible languages at the metalevel, even including the central question of whether the defined language is reversible. In this paper, we build a metalanguage foundation for reversible languages from categorical principles, based on the category of sets and partial injective functions. We exemplify our approach by a step-by-step development of the full semantics of an r-Turing complete reversible while-language with recursive procedures. The use of the metalanguage leads to a formalization of the reversible semantics. A language defined in the metalanguage is guaranteed to have reversibility and inverse semantics. Also, program inverters for this language are obtained for free. We further discuss applications and directions for reversible semantics.

High-quality gene/disease embedding in a multi-relational heterogeneous graph after a joint matrix/tensor decomposition

MotivationNode embedding of biological entity network has been widely investigated for the downstream application scenarios. To embed full semantics of gene and disease, a multi-relational heterogeneous graph is considered in a scenario where uni-relation between gene/disease and other heterogeneous entities are abundant while multi-relation between gene and disease is relatively sparse. After introducing this novel graph format, it is illuminative to design a specific data integration algorithm to fully capture the graph information and bring embeddings with high quality. ResultsFirst, a typical multi-relational triple dataset was introduced, which carried significant association between gene and disease. Second, we curated all human genes and diseases in seven mainstream datasets and constructed a large-scale gene-disease network, which compromising 163,024 nodes and 25,265,607 edges, and relates to 27,165 genes, 2,665 diseases, 15,067 chemicals, 108,023 mutations, 2,363 pathways, and 7.732 phenotypes. Third, we proposed a Joint Decomposition of Heterogeneous Matrix and Tensor (JDHMT) model, which integrated all heterogeneous data resources and obtained embedding for each gene or disease. Forth, a visualized intrinsic evaluation was performed, which investigated the embeddings in terms of interpretable data clustering. Furthermore, an extrinsic evaluation was performed in the form of linking prediction. Both intrinsic and extrinsic evaluation results showed that JDHMT model outperformed other eleven state-of-the-art (SOTA) methods which are under relation-learning, proximity-preserving or message-passing paradigms. Finally, the constructed gene-disease network, embedding results and codes were made available. Data and Codes AvailabilityThe constructed massive gene-disease network is available at: https://hzaubionlp.com/heterogeneous-biological-network/. The codes are available at: https://github.com/bionlp-hzau/JDHMT.

Mock Impoliteness in Saudi Arabia: Strategies of Evil Cursing

The current paper explores evil curses in the Bani Buhair tribe, which is located in the southwestern part of Saudi Arabia. It shows that cursing in Bani Buhair is a well‐constructed speech act that follows linguistic rules and patterns. Buhairi cursers formulate their evil curse constructions by deriving verbs from the consonants of the roots of the preceding words in the discourse. These derivational strategies are of four types: (i) full morphological derivation with full semantics, (ii) full morphological derivation with different semantics, (iii) partial morphological derivation with different semantics, and (iv) full morphological derivation with no semantics. Analyzing the evaluations of these evil curses by cursers, cursees, and two witnesses from the audiences, the paper argues that evil curses are non‐impolite phrases that reinforce solidarity between Buhairi in‐groups. The paper demonstrates that Haugh and Bousfield’s (2012) model of mock impoliteness accommodates evil curses better than the other dominant politeness and impoliteness models, proposed by Brown and Levinson (1987) and Culpeper (1996) respectively.

I-MAD: Interpretable malware detector using Galaxy Transformer

Malware currently presents a number of serious threats to computer users. Signature-based malware detection methods are limited in detecting new malware samples that are significantly different from known ones. Therefore, machine learning-based methods have been proposed, but there are two challenges these methods face. The first is to model the full semantics behind the assembly code of malware. The second challenge is to provide interpretable results while keeping excellent detection performance. In this paper, we propose an Interpretable MAlware Detector (I-MAD) that outperforms state-of-the-art static malware detection models regarding accuracy with excellent interpretability. To improve the detection performance, I-MAD incorporates a novel network component called the Galaxy Transformer network that can understand assembly code at the basic block, function, and executable levels. It also incorporates our proposed interpretable feed-forward neural network to provide interpretations for its detection results by quantifying the impact of each feature with respect to the prediction. Experiment results show that our model significantly outperforms existing state-of-the-art static malware detection models and presents meaningful interpretations.

Constructing High-Fidelity Phenotype Knowledge Graphs for Infectious Diseases With a Fine-Grained Semantic Information Model: Development and Usability Study.

BackgroundPhenotypes characterize the clinical manifestations of diseases and provide important information for diagnosis. Therefore, the construction of phenotype knowledge graphs for diseases is valuable to the development of artificial intelligence in medicine. However, phenotype knowledge graphs in current knowledge bases such as WikiData and DBpedia are coarse-grained knowledge graphs because they only consider the core concepts of phenotypes while neglecting the details (attributes) associated with these phenotypes.ObjectiveTo characterize the details of disease phenotypes for clinical guidelines, we proposed a fine-grained semantic information model named PhenoSSU (semantic structured unit of phenotypes).MethodsPhenoSSU is an “entity-attribute-value” model by its very nature, and it aims to capture the full semantic information underlying phenotype descriptions with a series of attributes and values. A total of 193 clinical guidelines for infectious diseases from Wikipedia were selected as the study corpus, and 12 attributes from SNOMED-CT were introduced into the PhenoSSU model based on the co-occurrences of phenotype concepts and attribute values. The expressive power of the PhenoSSU model was evaluated by analyzing whether PhenoSSU instances could capture the full semantics underlying the descriptions of the corresponding phenotypes. To automatically construct fine-grained phenotype knowledge graphs, a hybrid strategy that first recognized phenotype concepts with the MetaMap tool and then predicted the attribute values of phenotypes with machine learning classifiers was developed.ResultsFine-grained phenotype knowledge graphs of 193 infectious diseases were manually constructed with the BRAT annotation tool. A total of 4020 PhenoSSU instances were annotated in these knowledge graphs, and 3757 of them (89.5%) were found to be able to capture the full semantics underlying the descriptions of the corresponding phenotypes listed in clinical guidelines. By comparison, other information models, such as the clinical element model and the HL7 fast health care interoperability resource model, could only capture the full semantics underlying 48.4% (2034/4020) and 21.8% (914/4020) of the descriptions of phenotypes listed in clinical guidelines, respectively. The hybrid strategy achieved an F1-score of 0.732 for the subtask of phenotype concept recognition and an average weighted accuracy of 0.776 for the subtask of attribute value prediction.ConclusionsPhenoSSU is an effective information model for the precise representation of phenotype knowledge for clinical guidelines, and machine learning can be used to improve the efficiency of constructing PhenoSSU-based knowledge graphs. Our work will potentially shift the focus of medical knowledge engineering from a coarse-grained level to a more fine-grained level.

Идея этнопоэтики в современных исследованиях

<p>In recent decades, ethnopoetics has become one of the new philological disciplines. Its idea first appeared in the treatise of Nicolas Boileau “The Art of Poetry” (1674), in which the classicist theorist formulated the requirement of local and historical color in art. His rule was followed by many poets, playwrights and novelists of Modern history. In Anglo-American criticism, the term ethnopoetics was introduced in 1968. Jerome Rotenberg, who, along with Dennis Tedlock and Dell Himes, founded the principles and methods of studying American Indian poetry. In the 2000s. this concept has entered encyclopedic dictionaries in English and other European languages, but this word is still not in Russian terminological dictionaries. So far, the concept of poetics, which restricts the semantics of words forming a term, has received recognition. Already in the process of formation of ethnopoetics, its subject was expanded at the expense of middle Eastern and Jewish folklore, and later the oral creativity of other peoples. The word formation model (ἔθνος/ ethnos + ποιητική/poetics) cancels limited interpretations of the term. In modern usage, the term ethnopoetics is used in a wide range of meanings that have not yet been marked by lexicographers, but convey the full semantics of the words forming the term. The idea of ethnopoetics gave rise to not one, but several of its concepts. The author of the article develops his earlier understanding of ethnopoetics as a discipline that should study the national identity of the oral and written text, describe in the categories of poetics the specific things that make national literature national. It is characterized by concepts and conceptospheres, they form the mentality, reveal the cultural code of national literatures. The analysis of ethnopoetics opens up great opportunities in the comparative analysis of thesauri of different authors and their works.</p>

Planning for Hybrid Systems via Satisfiability Modulo Theories

Planning for hybrid systems is important for dealing with real-world applications, and PDDL+ supports this representation of domains with mixed discrete and continuous dynamics. In this paper we present a new approach for planning for hybrid systems, based on encoding the planning problem as a Satisfiability Modulo Theories (SMT) formula. This is the first SMT encoding that can handle the whole set of PDDL+ features (including processes and events), and is implemented in the planner SMTPlan. SMTPlan not only covers the full semantics of PDDL+, but can also deal with non-linear polynomial continuous change without discretization. This allows it to generate plans with non-linear dynamics that are correct-by-construction. The encoding is based on the notion of happenings, and can be applied on domains with nonlinear continuous change. We describe the encoding in detail and provide in-depth examples. We apply this encoding in an iterative deepening planning algorithm. Experimental results show that the approach dramatically outperforms existing work in finding plans for PDDL+ problems. We also present experiments which explore the performance of the proposed approach on temporal planning problems, showing that the scalability of the approach is limited by the size of the discrete search space. We further extend the encoding to include planning with control parameters. The extended encoding allows the definition of actions to include infinite domain parameters, called control parameters. We present experiments on a set of problems with control parameters to demonstrate the positive effect they provide to the approach of planning via SMT.

A Proof of Syntactic Incompleteness of the Second-Order Categorical Arithmetic

Actually, Arithmetic is considered as syntactically incomplete. However, there are different types of arithmetical theories. One of the most important is the second-order Categorical Arithmetic (AR), which interprets the principle of induction with the so-called full semantics. Now, whoever concluded that AR is sintactically (or semantically, since categoricity implies equivalence of the two types of completeness) incomplete? Since this theory is not effectively axiomatizable, the incompleteness Theorems cannot be applied to it. Nor is it legitimate to assert that the undecidability of the statements is generally kept in passing from a certain theory (such as PA) to another that includes it (such as AR). Of course, although the language of AR is semantically incomplete, this fact does not imply that the same AR is semantically/sintactically incomplete. Pending a response to the previous question, this paper aims to present a proof of the syntactic/semantical incompleteness of AR, by examples based on the different modes of representation (i.e. codes) of the natural numbers in computation.

Refinement through restraint: bringing down the cost of verification

We present a framework aimed at significantly reducing the cost of verifying certain classes of systems software, such as file systems. Our framework allows for equational reasoning about systems code written in our new language, Cogent. Cogent is a restricted, polymorphic, higher-order, and purely functional language with linear types and without the need for a trusted runtime or garbage collector. Linear types allow us to assign two semantics to the language: one imperative, suitable for efficient C code generation; and one functional, suitable for equational reasoning and verification. As Cogent is a restricted language, it is designed to easily interoperate with existing C functions and to connect to existing C verification frameworks. Our framework is based on certifying compilation: For a well-typed Cogent program, our compiler produces C code, a high-level shallow embedding of its semantics in Isabelle/HOL, and a proof that the C code correctly refines this embedding. Thus one can reason about the full semantics of real-world systems code productively and equationally, while retaining the interoperability and leanness of C. The compiler certificate is a series of language-level proofs and per-program translation validation phases, combined into one coherent top-level theorem in Isabelle/HOL.

Uniform strategies, rational relations and jumping automata

A general concept of uniform strategies has recently been proposed as a relevant notion in game theory for computer science, which subsumes various notions from the literature. It relies on properties involving sets of plays in two-player turn-based arenas equipped with arbitrary binary relations between plays; these properties are expressed in a language based on CTL⁎ with a quantifier over related plays. There are two semantics for our quantifier, a strict one and a full one, that we study separately. Regarding the strict semantics, the existence of a uniform strategy is undecidable for rational binary relations, but introducing jumping tree automata and restricting attention to recognizable relations allows us to establish a 2-Exptime-complete complexity – and still capture a class of two-player imperfect-information games with epistemic temporal objectives. Regarding the full semantics, relying on information set automata we establish that the existence of a uniform strategy is decidable for rational relations and we provide a nonelementary synthesis procedure. We also exhibit an essentially optimal subclass of rational relations for which the problem becomes 2-Exptime-complete. Considering rich classes of relations makes the theory of uniform strategies powerful: it directly entails various results in logics of knowledge and time, some of them already known, and others new.

EXACT2: the semantics of biomedical protocols.

BackgroundThe reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility.MethodsWe have developed the ontology EXACT2 (EXperimental ACTions) that is designed to capture the full semantics of biomedical protocols required for their reproducibility.To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously 'unseen' (not used for the construction of EXACT2) protocols.ResultsThe paper reports on a fundamentally new version EXACT2 that supports the semantically-defined representation of biomedical protocols. The ability of EXACT2 to capture the semantics of biomedical procedures was verified through a text mining use case. In this EXACT2 is used as a reference model for text mining tools to identify terms pertinent to experimental actions, and their properties, in biomedical protocols expressed in natural language. An EXACT2-based framework for the translation of biomedical protocols to a machine amenable format is proposed.ConclusionsThe EXACT2 ontology is sufficient to record, in a machine processable form, the essential information about biomedical protocols. EXACT2 defines explicit semantics of experimental actions, and can be used by various computer applications. It can serve as a reference model for for the translation of biomedical protocols in natural language into a semantically-defined format.

Standardization of Questions in Rare Disease Registries: The PRISM Library Project

BackgroundPatient registries are often a helpful first step in estimating the impact and understanding the etiology of rare diseases - both requisites for the development of new diagnostics and therapeutics. The value and utility of patient registries rely on the use of both well-constructed structured research questions and relevant answer sets accompanying them. There are currently no clear standards or specifications for developing registry questions, and there are no banks of existing questions to support registry developers.ObjectiveThis paper introduces the [Rare Disease] PRISM (Patient Registry Item Specifications and Metadata for Rare Disease) project, a library of standardized questions covering a broad spectrum of rare diseases that can be used to support the development of new registries, including Internet-based registries.MethodsA convenience sample of questions was identified from well-established (>5 years) natural history studies in various diseases and from several existing registries. Face validity of the questions was determined by review by many experts (both terminology experts at the College of American Pathologists (CAP) and research and informatics experts at the University of South Florida (USF)) for commonality, clarity, and organization. Questions were re-worded slightly, as needed, to make the full semantics of the question clear and to make the questions generalizable to multiple diseases where possible. Questions were indexed with metadata (structured and descriptive information) using a standard metadata framework to record such information as context, format, question asker and responder, and data standards information.ResultsAt present, PRISM contains over 2,200 questions, with content of PRISM relevant to virtually all rare diseases. While the inclusion of disease-specific questions for thousands of rare disease organizations seeking to develop registries would present a challenge for traditional standards development organizations, the PRISM library could serve as a platform to liaison between rare disease communities and existing standardized controlled terminologies, item banks, and coding systems.ConclusionsIf widely used, PRISM will enable the re-use of questions across registries, reduce variation in registry data collection, and facilitate a bottom-up standardization of patient registries. Although it was initially developed to fulfill an urgent need in the rare disease community for shared resources, the PRISM library of patient-directed registry questions can be a valuable resource for registries in any disease – whether common or rare.Trial RegistrationN/A

Hypermodelling: an integrated approach to dynamic system modelling

Models used in simulation tend to be disconnected from reality and from related models. Ideally, we should like to interact with models as if they were web assets containing extensive hyperlinking and cross-connections. In practice, these inter-connections with respect to the human-model interface are lacking and need to be improved. For example, interacting with a term within a mathematical model is rarely possible. Without such interaction, the full semantics of the term, including its real-world meaning, appearance, and source code implementation, are difficult to identify. The same model may appear in several separate locations: electronic documentation, formula-oriented software, slides, source code. Without the proper connections, model semantics can drift. Also, multiple models are generally required to view different aspects of reality, and to ensure that the right model medium is used for the people that need to understand that model. We introduce the term, hypermodel, to include interaction within models, among models, and between human and model. The discussion of hypermodelling is presented with a special focus on research performed at the University of Florida over the past 20 years.

De la pulsión a la solicitud por el otro: Bases antropológicas para la “pequeña ética” de Ricœur

L’intention de ce travail consiste à suivre jusqu’au niveau le plus archaïque de la condition humaine, les racines anthropologiques que justifient la fondation d’une éthique, comme celle que propose Paul Ricœur, dans son livre Soi-même-comme-un-autre. D’abord, j’essayerai d’exposer le parcours que fait l’image créatrice, depuis sa genèse pulsionnelle jusqu’à sa plénitude sémantique dans le symbole, selon le dialogue que l’auteur engage avec Freud, dans son œuvre De l’interprétation. Essai sur Freud, à partir de sa préoccupation herméneutique. En suite, tenant compte d’une réflexion critique que Ricœur fait à Freud, j’explorerai l’orientation intentionnelle de “la vie bonne”, dont “l’estime de soi”, son sentiment réflexif, intègre la dimension symbolique de l’action et prépare l’épanouissement de la personne humaine.

Crime is in the Eye of the Beholder: Petr Petrovich Luzhin as a Distorting “Puddle-Mirror” in Dostoevsky's Crime and Punishment

AbstractThis study demonstrates how conceptualizations ingrained in our linguistic consciousness help us realize the full semantics that an author com municates to his reader through a “speaking name”; this kind of name, together with the character's behavioral profile create a multidimensional psychological portrait.The examples are taken from Dostoevsky's Crime and Punishment, specifically the “puddle-name” Luzhin. The speaking name of Petr Petrovich Luzhin evokes a number of cognitive conceptualizations that are rooted in human experience, as well as in the history, mythology, and culture of the Russian people and that are in dialogical relationships with the other characters in the novel through their speaking names. The analysis, based on cognitive stylistics and, more specifically, cognitive metaphor theory in the Lakoff tradition, underscores the significance of the cultural water metaphor when applied to the human domain. It also confirms that the “speaking name” is a major device in Dostoevsky's poetics.

A certified framework for compiling and executing garbage-collected languages

We describe the design, implementation, and use of a machine-certified framework for correct compilation and execution of programs in garbage-collected languages. Our framework extends Leroy's Coq-certified Compcert compiler and Cminor intermediate language. We add: (i) a new intermediate language, GCminor, that includes primitives for allocating memory in a garbage-collected heap and for specifying GC roots; (ii) a precise, low-level specification for a Cminor library for garbage collection; and (iii) a proven semantics-preserving translation from GCminor to Cminor plus the GC library. GCminor neatly encapsulates the interface between mutator and collector code, while remaining simple and flexible enough to be used with a wide variety of source languages and collector styles. Front ends targeting GCminor can be implemented using any compiler technology and any desired degree of verification, including full semantics preservation, type preservation, or informal trust. As an example application of our framework, we describe a compiler for Haskell that translates the Glasgow Haskell Compiler's Core intermediate language to GCminor. To support a simple but useful memory safety argument for this compiler, the front end uses a novel combination of type preservation and runtime checks, which is of independent interest.