Logical Schema Research Articles

The anthropological signification of the ‘Man with No Breath’ in Visayas and Mindanao epics

ABSTRACT This article argues that the enigmatic figure of the ‘Man with No Breath’ in the Visayan Labaw Donggon and the Sugidanon epics of Panay is not just a random flair in literary imagery, but works as a cultural pointer to a coherent and durable schema relating to personhood (of a self composed of ‘detachable’ or ‘partible’ parts) as it intersects with a particular ontology (of basic reality from a construal of ‘breathing’). Our ethnographic-comparative approach to this character takes it as an elaborated expression of indigenous reasoning centring on ‘breathing’ and its figurations in socio-symbolic fields. Taking relevant data coming from our Pantaron Manobo ethnography and epics to bear on Visayan epic data, we outline a logical schema – relating ‘breathing’, ‘cutting’ and ‘marking’ (‘breathing is cutting and linking’ and ‘cutting is marking with breath’) – objectified in the figure of the ‘Man with No Breath’. This breathing-cutting-marking thema has broader regional heuristic use: opening possibilities in understanding other than the usual ‘metaphorical’ or ‘animistic’ glossings of South East Asian/Austronesian ‘soul’, ‘spirit’, ‘life force’ or ‘breath’. The anthropological value of this figure is apt since ‘breath’ in this region (with its linguistic and cultural particularities) has long assumed a specific ritual/religious valence.

Logical object structure and system implementation for BIM database in civil infrastructures

ABSTRACT Building Information Modeling (BIM) has attracted much attention as a vital information method in civil engineering. BIM data research has become increasingly important with the continuous understanding of BIM. The database designed especially for storing BIM data (IFC data) is called a BIM database. To realize centralized storage and sharing of complex building information, how to design and develop a BIM database will be a hot topic. However, the BIM database designed using an existing logical model (such as a relational model) is unsuitable for storing and managing a large amount of BIM data. To this end, we propose a database logical model for BIM database development called ‘logical object structure’. Based on the database design methodology, the logical schema of the BIM database is discussed, and five relation forms are established to describe the feature of engineering information. According to the relation forms, the logical object structure is presented, and the corresponding system implementation process is discussed. Finally, four workloads are set to test the logical object structure. The results show that the logical object structure can well support interactive behaviors of BIM data and provide good performance for the BIM database.

AStar: A modeling language for document-oriented geospatial data warehouses

A Geospatial Data Warehouse (GDW) is an extension of a traditional Data Warehouse that includes geospatial data in the decision-making processes. Several studies have proposed the use of document-oriented databases in a GDW as an alternative to relational databases. This is due to the ability of non-relational databases to scale horizontally, allowing for the storage and processing of large volumes of data. In this context, modeling the manner in which facts and dimensions are structured is important in order to understand, maintain, and evolve the Document-oriented GDW (DGDW) through visual analysis. However, to the best of our knowledge, there are no modeling languages that support the design of aggregated data as facts and dimensions, that can be represented as referenced or embedded documents, partitioned into one or more collections. To overcome this lack, we propose Aggregate Star (AStar), a Domain-Specific Modeling Language for designing DGDW logical schemas. AStar is defined from a concrete syntax (graphical notation), an abstract syntax (metamodel), and static semantics (well-formedness rules). In order to describe the semantics of the concepts defined in AStar, translational semantics map the graphical notation to the metamodel and the respective code, to define the schema in MongoDB (using JSON Schema). We evaluate the graphical notation using Physics of Notations (PoN), which provides a set of principles for designing cognitively effective visual notations. This evaluation revealed that AStar is in accordance with seven of the nine PoN principles, an adequate level of cognitive effectiveness. As a proof of concept, the metamodel and well-formedness rules were implemented in a prototype of Computer-Assisted Software Engineering tool, called AStarCASE. In its current version, AStarCASE can be used to design DGDW logical schemas and to generate their corresponding code in the form of JSON Schemas.

Declarative interfaces for HEP data analysis: FuncADL and ADL/CutLang

Analysis description languages are declarative interfaces for HEP data analysis that allow users to avoid writing event loops, simplify code, and enable performance improvements to be decoupled from analysis development. One example is FuncADL, inspired by functional programming and developed using Python as a host language. FuncADL borrows concepts from database query languages to isolate the interface from the underlying physical and logical schemas. The same query can be used to select data from different sources and formats and with different execution mechanisms. FuncADL is one of the tools being developed by IRIS-HEP for highly scalable physics analysis for the LHC and HL-LHC. FuncADL is demonstrated by implementing example analysis tasks designed by HSF and IRIS-HEP. Another language example is ADL, which expresses the physics content of an analysis in a standard and unambiguous way, independent of computing frameworks. In ADL, analyses are described in human-readable text files composed of blocks with a keyword-expression structure. Two infrastructures are available to render ADL executable: CutLang, a runtime interpreter written in C++; and adl2tnm, a transpiler converting ADL into C++ or Python code. ADL/CutLang are already used in several physics studies and educational projects, and are adapted for use with LHC Open Data.

«Неисследованные девяностые»: систематизация источников и концептуальное проектирование базы данных (на примере системы СМИ Томска и Томской области 1990-х годов)

The paper presents the conceptual structure of the factual database “Tomsk media anomaly” covering all the media in Tomsk and the Tomsk Oblast of the 1990s. The authors analyze the state of the research field for understanding the processes of transformation of journalism in the 1990s. A consistent description is given of the stages of conceptual design. The first stage involved planning a system of tasks to be solved using the information resource developed. The second stage was to analyze the subject area and develop its infological scheme by defining the main objects to be described and identifying their relationships within the framework of the subject area. The third stage was focused on generating a data logical schema of the database, representing the structure of the table fields, displaying the attributes of the described objects. The paper explains the structures of the central table and supplementary tables. Also, the examples of how to solve research problems by means of the tables are provided. The authors suggest that the database concept will provide a full-fledged information resource for recording and quantitatively processing the data on Tomsk and Tomsk Oblast media. The development of a database based on conceptual design is part of the general methodology for studying the transformation of Tomsk and the Tomsk Oblast media system.

A novel approach for handling semantic trajectories on data warehouses

A trajectory is a set of traces left by a moving object. It contains spatio-temporal information about where and when that object was, as well as other semantical relevant information. It is described by a continuation of movement. Data concerning moving objects and their trajectories can be stored in a Trajectory Data Warehouses for organization, managing, and analysis purposes. This work is dedicated to semantic trajectory data warehouses. A logical schema is proposed, called S-TrODW, where an object relational framework is used. The main novelty of the S-TrODW model is the integration of trajectories and their segments in the fact table by means of a nested relation. An algorithm is presented for transforming the flat star schema (with non-nested trajectory segments) to the S-TrODW schema. The proposal is validated through a case study dealing with freight transportation. A more natural modelling and queries formulation, as well as the improvement of query execution time are among the contributions of this paper compared to other works.

Meteorological Data Warehousing and Analysis for Supporting Air Navigation

Data analysis of weather phenomena to either predict or control human imprint on the environment requires the collection of various forms of observational data ranging from historical and longitudinal to forecast. The objective of this research paper is the development of a data warehouse (DW) based on a new hybrid logical schema, concerning the assimilation and maintenance of historical meteorological data from all operating airports in Greece, along with data in the Greek Flight Information Region related to flight delays and cancellations. SQL is used for querying these data and makes them easily accessible and manageable. The data from the DW are collected and used as training data for the induction of predictive models. In this study, the prediction problem is cast as a classification task, and different decision tree induction techniques are applied to build accurate models that allow flexible scheduling and planning for the minimization of waiting time and inconvenience of passengers.

Bio-Strings: A Relational Database Data-Type for Dealing with Large Biosequences.

DNA sequencers output a large set of very long biological data strings that we should persist in databases rather than basic text file systems. Many different data models and database management systems (DBMS) may deal with both storage and efficiency issues regarding genomic datasets. Specifically, there is a need for handling strings with variable sizes while keeping their biological meaning. Relational database management systems (RDBMS) provide several data types that could be further explored for the genomics context. Besides, they enforce integrity, consistency, and enable good abstractions for more conventional data. We propose the relational text data type to represent and manipulate biological sequences and their derivatives. We present a logical schema for representing the core biological information, which may be inferred from a given biological conceptual data schema and the corresponding function manipulations. We implement and evaluate these stored functions into an actual RDBMS for both efficacy and efficiency. We show that it is possible to enforce basic and complex requirements for the genomic domain. We claim that the well-established relational text data type in RDBMS may appropriately handle the representation and persistency of biological sequences. We base our approach on the idea of domain-specific abstract data types that can store data with semantically defined functions while hiding those details from non-technical end-users.

Black Universals and Alain Locke's Notion of Value

Black Universals and Alain Locke's Notion of Value

Design of quaternary MIN and MAX circuits using graphene nanoribbon field effect transistors

This paper presents the design of digital logic schematics in quaternary logic. The quaternary logic is considered as best choice over the conventional two-valued logic due to its advantages such as faster computations, large memory storage, reduced interconnect length, ability to transmitting and receiving the large information, and simplification in testing. These advantages allow designing high performance circuit’s in the future integrated circuits. The new method is projected to develop the quaternary logic circuits utilizing graphene nanoribbon field effect transistors (GNRFETs). The quaternary logic circuits are developed based on GNRFETs wonderful properties, such as controlling the threshold voltage by changing the GNR width. This property makes them compatible to develop the multi-threshold digital circuits. To ensure the functionality of the digital circuits, the GNRFET based quaternary minimum (MIN) and maximum (MAX) circuits are developed. The proposed designs are simulated extensively in HSPICE tool for performance analysis. In comparison with the quaternary CNTFET based circuits, the proposed circuits optimized by 67.13%, 18.7%, 73.16% and 25.88%, in power consumption, delay, power delay product (PDP) and circuit area, respectively.

Implicitness, Logical Form and Arguments

In the paper I suggest that a loose notion of logical form can be a useful tool for the understanding or evaluation of everyday language and the explicit and implicit content of communication. Reconciling ordinary language and logic provides formal guidelines for rational communication, giving strength and order to ordinary communication and content to logical schemas. The starting point of the paper is the idea that the bearers of logical form are not natural language sentences, but what we communicate with them, that is, their content in a particular context. On the basis of that idea, I propose that we can ascribe logical proprieties to what is communicated using ordinary language and suggest a continuum between semantic phenomena such as explicatures and pragmatic communicational strategies such as (particularized) conversational implicatures, which challenges the idea that an implicatum is completely separate from what is said. I believe that this continuum can be best explained by the notion of logical form, taken as a propriety of sentences relative to particular interpretations.

A unified metamodel for NoSQL and relational databases

The Database field is undergoing significant changes. Although relational systems are still predominant, the interest in NoSQL systems is continuously increasing. In this scenario, polyglot persistence is envisioned as the database architecture to be prevalent in the future. Therefore, database tools and systems are evolving to support several data models.Multi-model database tools normally use a generic or unified metamodel to represent schemas of the data model that they support. Such metamodels facilitate developing database utilities, as they can be built on a common representation. Also, the number of mappings required to migrate databases from a data model to another is reduced, and integrability is favored.In this paper, we present the U-Schema unified metamodel able to represent logical schemas for the four most popular NoSQL paradigms (columnar, document, key–value, and graph) as well as relational schemas. We will formally define the mappings between U-Schema and the data model defined for each database paradigm. How these mappings have been implemented and validated will be discussed, and some applications of U-Schema will be shown.To achieve flexibility to respond to data changes, most of NoSQL systems are “schema-on-read,” and the declaration of schemas is not required. Such an absence of schema declaration makes structural variability possible, i.e., stored data of the same entity type can have different structure. Moreover, data relationships supported by each data model are different; For example, document stores have aggregate objects but not relationship types, whereas graph stores offer the opposite. Through the paper, we will show how all these issues have been tackled in our approach.As far as we know, no proposal exists in the literature of a unified metamodel for relational and the NoSQL paradigms which describes how each individual data model is integrated and mapped. Our metamodel goes beyond the existing proposals by distinguishing entity types and relationship types, representing aggregation and reference relationships, and including the notion of structural variability. Our contributions also include developing schema extraction strategies for schemaless systems of each NoSQL data model, and tackling performance and scalability in the implementation for each store.

Active Inference and Abduction

The background target of the research going into the present article is to forge an intellectual alliance between, on the one hand, active inference and the free-energy principle (FEP), and on the other, Charles S. Peirce’s theory of semiotics and pragmatism. In the present paper, the focus is on the allegiance between the nomenclatures of active and abductive inferences as the proper place to begin reaching at that wider target. The paper outlines the key conceptual elements involved in a naturalistic rendering of Peirce’s late semiotic and logical notion of abductive reasoning. The target is a cognitive-biological model of abduction which preserves the functional integrity of an organism and fulfils the existential imperative for living beings’ evidence of existence. Such a model is an adaptation of Peirce’s late logical schema of abduction proposed in his largely unpublished works during the early 20th century. The proposed model is argued to be a feasible sketch also of recent breakthroughs in computational (sensu Bayesian) cognitive science.

Automatic Generation of Scripts for Database Creation from Scenario Descriptions

Aims: Database creation is the most critical component of the design and implementation of any software application. Generally, the process of creating the database from the requirement specification of a software application is believed to be extremely hard. This study presents a method to automatically generate database scripts from a given scenario description of the requirement specification.
 Study Design: The method is developed based on a set of natural language processing (NLP) techniques and a few algorithms. Standard database scenario descriptions presented in popular textbooks on Database Design are used for the validation of the method.
 Place and Duration of Study: Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya, Sri Lanka, Between December 2019 to December 2020.
 Methodology: The description of the problem scenario is processed using NLP operations such as tokenization, complex word handling, basic group handling, complex phrase handling, structure merging, and template construction to extract the necessary information required for the entity relational model. New algorithms are proposed to automatically convert the entity relational model to the logical schema and finally to the database script. The system can generate scripts for relational databases (RDB), object relational databases (ORDB) and Not Only SQL (NoSQL) databases. The proposed method is integrated into a web application where the users can type the scenario in natural or free text. The user can select the type of database (i.e., one of RDB, ORDB, NoSQL) considered in their system and accordingly the application generates the SQL scripts.
 Results: The proposed method was evaluated using 10 scenario descriptions connected to 10 different domains such as company, university, airport, etc. for all three types of databases. The method performed with impressive accuracies of 82.5%, 84.0% and 83.5% for RDB, ORDB and NoSQL scripts, respectively.
 Conclusion: This study is mainly focused on the automatic generation of SQL scripts from scenario descriptions of the requirement specification of a software system. Overall, the developed method helps to speed up the database development process. Further, the developed web application provides a learning environment for people who are novices in database technology.

Modified Data Storage and Replication Mechanism with Frequent Use-Case Based Indexing

The real time applications demands high speed and reliable data access from the remote database. An effective logical data management strategy that handles simultaneous connections with better performance negotiation is inevitable. This work considers an e-health care application that proposes MongoDB based modified indexing and performance tuning methods. To cope with certain high frequency use case and its performance mandates, a flexible and efficient logical data management may be preferred. By analysing the data dependency, data decomposition concerns and the performance requirements of the specific use case of the medical application, a logical schema may be customized on an ala-carte basis. This work focused on the flexible logical data modeling schemes and its performance factors of the NoSql DB. The efficiency of unstructured data base management in storing and retrieving the e-health care data was analysed with a web based tool. To enable faster data retrieval and query processing over the distributed nodes, a Spark based storage engine was built on top of the MongoDB based data storage management. With Spark tool, the database has been made distributed as master–slave structures with suitable data replication mechanisms. In such distributed database the fail-over also implemented with the suitable replication mechanism. This work considered MongoDB based flexible schema modeling and Spark based distributed computation with multiple chunks of data. The flexible data modeling scheme with MongoDB with the on-demand Spark based computation framework was proposed. To facilitate the eventual consistency, scalability aspects of the e-health care applications, use case based indexing was proposed. With the effective data management, faster query processing the horizontal scalability has been increased. The overall efficiency and scalability of the proposed logical data management approach was analysed. Through the simulation studies, the proposed approach has been claimed to boost the performance of the bigdata based application to a considerable extent.

Formal inferences and their relationships to knowledge acquisition: mental models and semantic links

The mental model theory is an approach with clear psychological, linguistic, and cognitive consequences. This paper delves into some of the epistemological conclusions that can be drawn from it. In particular, it addresses the process why knowledge acquisition can modify the inferences people tend to make. That process is described by means of an example based on a well-known logical schema related to the conditional: Modus Tollendo Tollens.

The Ontological Innocence of Schematic Logic

This paper gives a semantics for schematic logic, proving soundness and completeness. The argument for soundness is carried out in ontologically innocent fashion, relying only on the existence of formulae which are actually written down in the course of a derivation in the logic. This makes the logic available to a nominalist, even a nominalist who does not wish to rely on modal notions, and who accepts the possibility that the universe may in fact be finite.

Simulation study of memristor aided logic (MAGIC) based on CMOS NOR gate

Memristor is a non-volatile new technology memory where the data stored as a resistance which the performance is influenced by the stateful logic design. Therefore, this study is an attempt to investigate the performance of the MAGIC NOR Gate stateful logic design using LTSPICE and targeted to 2 bits memory application. The objective is to investigate the performance of memristor based stateful logic logic design and schematics for memory application. Furthermore, the study been carried out by implementing the MAGIC NOR gate stateful logic schematic, then simulate the design in order to see the effects of performance including the electrical parameters compared to the others. Evidently, the improvement of MAGIC NOR gate contributes in reducing the number of NOR gate and CMOS count. Besides, the MAGIC NOR gates takes parallel inputs topology and eliminate the threshold voltage compared to IMPLY logic. Nevertheless, larger numbers of memristor required to stable the output consistency in MAGIC NOR gate schematic.

INFORMATION TECHNOLOGY OF SUPPORTING ARCHITECTURAL SOLUTIONS USING POLYGLOT PERSISTENCE CONCEPT IN LEARNING MANAGEMENT SYSTEMS

This paper shows that performance of the learning management systems heavily depends on the choice, made during designing, of architectural solution for storage and processing of data. Based on analysis of evolution of the various architectural solutions dur-ing the information system design, beginning with monolith platform and ending with decentralized microservices, it has been de-termined that architecture based on microservices for a server side with code-level isolation and database-level decentralization for components is proved to be effective solution for high-performance system complexes for learning management system. However, for implementation of polyglot persistence concept based on multiple database managementsystems with various logical schemas, there is also a need for developing an information technology to support such architectural solutions. It has been shown that the de-velopment of databases for such learning management system, that operate with a large amount of various information, consists of the stages of conceptual, logical and physical modeling, and, precisely during the creation of logical models the requirements for the storage and processing of data, that are used by the selected entities for the implementation of business functions, are determined. The peculiar properties of using relational and non-relational database management systems such as: document, key-value, graph and column storages have been examined and analyzed in detail. A method for automated selection of logical data models based on initial information about a limited context has been developed, then used to develop a classifier. The efficiency of the classifier was tested on a dataset for two hundred thirty entities. As a result of the experiment, the reliability of the classification was ninety-three percent. The advantages of the developed information technology are shown on the example of designing JustStart learning management system. Analysis of the stress testing results of the developed system shows that due to the distribution of the load between the three databases, its average response time with simultaneous operation of one hundred fifty users was one point two seconds. At thesame time, simulation of the same number of users with only one database management system, the response time increased and the aver-age was approximately two point six seconds. Thus, the use of the developed information technology of supporting architectural solutions for organizing storage of large volumes of diverse data according to the polyglot persistence concept, that allowed to design and implement learning management system, the performance of which, if it is used simultaneously by a large audience, is on aver-age twice as fast as the average educational resource on the market.

Оцінювання збалансованості розвитку національної економіки: структурно-динамічний аспект

The work is devoted to the grounding of the scientific and methodological aspects and forming the practical recommendations for evaluation of national economy’s development balance. Assessment’s results are aimed at strict explanation of real economic dynamics to find relevant instruments and impact mechanisms to target national economic development to the mainstream. Structural and dynamic approach to the estimation gives an opportunity to neutralize the complexity of national economy as an object for the evaluation by means of building the phase portraits of national economic sectors’ movements in two-dimensional phase space structured with the balanced lines. Practicability of the “balanced growth concept” implementation as a part of the national economy’s balance development evaluating is scientifically proved. Using of the concept’s mechanisms and principles at the macro level of national economic systems’ evolution is proposed. The structural and logical schema of balanced indicators is formed. Empirical research of Ukrainian national economy’s balance development is done during 2008-2012’ period. Matrix of growth quality assessment is built for the main sectors of national economy. The conclusions about security, sustainability and expediency of national economic growth rates, its structural components are made. The national economy’s sectors characterized with the most sustainable and regular behavior according to assessment based on indicators of a Balanced Growth Rate and Sustainable Development Index are picked out. General results of balance and prospects of national economy’s development are formed.