Relational Tables Research Articles

Factors Affecting Maintenance of Buildings in Petroleum Training Institute, Uwvie and Delta State University Abraka, Delta State, Nigeria

Aim: The aim of this study is to assess the factors hindering effective maintenance of public buildings in Delta state with a view to establishing common defects in public buildings and significant factors affecting effective maintenance in the study area.
 Study Design: It was a survey research; the study was affected via literature review and a well-structured questionnaire. Likewise, physical observations were carried out to substantiate the findings of the questionnaire survey.
 Place and Duration of the Study: The study was conducted in Petroleum Training Institute (P.T.I), Uwvie LGA and Delta State University (DELSU), Ethiope West LGA, in Delta state, Nigeria for a period of 2 years.
 Methodology: Being survey research, the study employed the use of review of related literature, structured questionnaire, personal survey, and photographs for data collections. The study respondents were selected using purposive sampling technique. Relative Importance Index (RII), mean scores, frequency tables and descriptive statistics were employed for the data analysis. 
 Results: The study found out that the four most significant deficiencies identified include; rising dampness problem (0.8656), cracks on walls (0.8469), unstable foundation (0.8094) and defective plastering and rendering (0.7875) while the three least defects are fungi and small plant attack (0.6313), insects (termite) attack (0.6656) and timber decay (0.7031). The most four significant factors affecting building maintenance is Poor supervision (0.8875) followed by defective construction material, incompetent workforce and non-conformance with the specification with RIIs of 0.8719, 0.8531 and 0.8375 respectively.
 Conclusion: The study concludes that professionals should focus on teamwork rather than personal competitiveness in ensuring defects free design and construction. Professionals should pay more attention to the possibility of defects occurrence when planning construction projects, critical consideration of factors affecting design and construction defects when planning construction activities, engaging required professionals at every stage of the construction process, and strict monitory and supervision of construction works among others are recommended.

SISTEM INFORMASI SIMPAN PINJAM KOPERASI KARYAWAN PTPN XII KEBUN SUMBER TENGAH

The saving and loan information system of the Employees Cooperative in PTPN XII (Persero) Kebun Sumber Tengah is an enterprise dealing with saving and loan particularly for the employees of PTPN XII (Persero) Kebun Sumber Tengah giving such a service for the members especially in saving and loan. The data management is already computerized even though it is still run by using Microsoft Office that it does make the members who want to do saving and loan should wait in longer time because it usually appears data redundancy in the saving and loan data itself. The researcher raises a problem based on what is faced in the saving and loan data management. It is then expected to help the cooperative staffs increase their service to the members as well as save the data or any important documents, so the information can be presented faster and more accurately.The method of developing the information system applies system developing tools such as Flow Map Context Diagram (Contex Diagram), DFD (Data Flow Diagram) and design tools while the database proposed is ERD (Entity Relationship Diagram) relation table. The saving and loan information system that is designed aims at building a computerized information system that can enable the employees in the cooperative department manage the data of member, data of saving, data of loan, and data of installment.

Data Cleaning Model for XML Datasets using Conditional Dependencies

Data Cleaning as an essential phase to enhance the overall quality used for decades with different data models, the majority handled a relational dataset as the most dominant data model. However, the XML data model, besides the relational data model considered the most data model commonly used for storing, retrieving, and querying valuable data. In this paper, we introduce a model for detecting and repairing XML data inconsistencies using a set of conditional dependencies. Detecting inconsistencies will be done by joining the existed data source with a set of patterns tableaus as conditional dependencies and then update these values to match the proper patterns using a set of SQL statements. This research considered the final phase for a cleaning model introduced for XML datasets by firstly mapping the XML document to a set of related tables then discovering a set of conditional dependencies (Functional and Inclusions) and finally then applying the following algorithms as a closing step of quality enhancement.

PENGARUH PENGGUNAAN INTERNET TERHADAP PENYELASAIAN TUGAS (PR) MAHASISWA UNIVERSITAS QUALITY PROGRAM STUDI PGSD PADA MATA KULIAH KONSEP DASAR IPA

This study aims to determine the effect of internet use on task completion (PR) of PGSD University Quality Study Program Students in Science Concept Basic Subjects 2019/2020 Academic Year. This type of research is expostfacto with quantitative methods. The results of the average value obtained by the class 2B11 82.74 namely the class that uses the Internet for completing assignments and class 2B12 74.05 ie the class that does not use the internet for task completion. Table frequency of final grade test scores that use the internet for completing assignments and classes that do not use internet for completing assignments can be distributed in a relative frequency table then drawn into a histogram to determine the comparison of students completing assignments using the internet and students completing assignments not using Internet. Hypothesis testing using t test with a significant level of α = 0.05 and dk = (obtained 36.68 (0.975) (76) = 1.73. From the results of hypothesis testing the data can be concluded that there is an effect of task completion on task completion (PR) Quality University Students PGSD Study Program in Science Basic Concept Courses. Keywords: Task Completion, Internet Usage, Expostfacto

The basics of trauma needs-based training in asymmetric warfare.

Introduction:Trauma is the leading cause of mortality and one of the main causes of disability among the active populations in the battlefields. Therefore, trauma education is an important need for asymmetric warfare, which is met through training based on existing needs and possibilities.Methods:In this qualitative study, validated using Delphi technique in Tehran in 2019, the participants were selected from the experts and activities in the field of trauma in asymmetric warfare. Inclusion criteria included willingness to participate in the research, history of treatment activity, and trauma training in asymmetric warfare. This study is based on the two axes: (1) Investigating existing upstream documents and resources on trauma in asymmetric warfare. (2) Conducting structured interviews (based on training elements and trauma experiences in asymmetric warfare) with trauma experts and professors in asymmetric warfare.Results:The results obtained from the above resources, are defined and classified as 10 element training model (Akker). These results and related tables have also been reviewed and validated by trauma experts.Conclusion:The achievements of the present research explained the dimensions and indicators of trauma needs based training in asymmetric warfare that is an effective approach to increase the effectiveness of trauma learning and training in asymmetric warfare and increase the cost effectiveness. It is also an effective approach to organize trauma preparedness for all troops present in asymmetric warfare and can be presented as an operational protocol in terms of methodology and roadmap.

Компактное представление ограничений на основе новой интерпретации понятия «кортеж многоместного отношения»

The article discusses various points of view on the concept of "tuple of a multi-place relation" used in mathematics and information technology. Special attention is paid to an evolution of the concept “tuple” within Constraint Programming technology where the emergence of new interpretations for the concept “tuple” is related with attempts to design more “compact” table representation of qualitative relations comparing with typical relational tables. This “compact” representation can serve as a basis for accelerating qualitative constraint satisfaction procedures. In studied prototype-works, such varieties of table constraints as compressed-tables and smart-tables were proposed. In so doing, the concept of compressed- and smart- tuple substantially differs from traditional concept of tuple of a multi-place relation. However, the known table constraints types are not well suited for modeling and processing all types of quality relations, for example, there are inconveniences when modeling production rules. The article proposes a new type of table constraints – smart-tables of D-type and equivalent transformations rules allowing the initial constraint satisfaction problem to be effectively reduced. The application of the smart-tables of D-type allows in some cases to substantially reduce computer memory consumption comparing with application of the known types of table constraints. In particular, smart-tables of D-types are well suited for modeling production rules, some types of logical expirations and some types of global constraints.

Towards Cryptanalysis of a Variant Prime Numbers Algorithm

A hallmark of prime numbers (primes) that both characterizes it away from other natural numbers and makes it a challenging preoccupation, is its staunch defiance to be expressed in terms of composites or as a formula listing all its sequence of elements. A classification approach, was mapped out, that fragments a prime into two: its last digit (trailer - reduced set of residue {1, 3, 7 and 9}) and the other digits (lead) whose value is incremented by either 1, 2 or 3 thus producing a modulo-3 arithmetic equation. The algorithm tracked both Polignac’s and modified Goldbach’s coefficients in order to explore such an open and computationally hard problem. Precisely 20,064,735,430 lower primes of digits 2 to 12 were parsed through validity test with the powers of 10 primes of Sloane's A006988. Adopting at most cubic terms of predictors (as the next logical step of Euler’s quadratic formula for primes) in multiple linear regression analysis, the generated outputs were analyzed to aid in building Akaike Information Criterion (AIC) best model with forward selection strategy. The main task was fragmented into atomic units of similar instances and types (an atom is a table of length 4,493,869 integer sequences where a database contains 30 relational tables with facilities for further reprocessing). A node, that supports parallel processing, stores 30 contiguous databases, and explores 4,044,482,100 successive integers. 513,649,226,700 lower natural numbers were explored by 127 hypothetical nodes yielding primes stored in 114,300 tables spread across 3,810 databases. Veriton S6630G computer system with 7.86GB usable memory and processor Intel(R) Core(TM) i7-4790 CPU @ 3.60GHz were amongst the remarkable resources. Contrary to the apparent chaotic camouflage of primes as a bundle, the partitioned sample spaces reveal some remarkable patterns in terms of intervals of both sequence numbers and distances of separation from their immediate neighborhoods.

Methodology in cardiologists’ postgraduate education

Aim. To develop the methodological ware for distance cardiologists’ postgraduate education by virtual patients’ simulations. The article describes the first stage of the project to create a database of virtual patients. It includes the integration of text and multimedia clinical and diagnostic information about patients and software for its presentation. A virtual patient is considered as an informational model of the diagnostic and treatment processes.Material and methods. To create a database of virtual patients, a description of completed clinical cases in specially designed patterns was used. To provide distance access to information about virtual patients, the JavaScript was used. Results. When forming the database of virtual patients, two categories of case histories were used — the most common cases and rare disease variants. From archival case histories and examination data, information has been selected that plays a significant role in the diagnosis and treatment. It was decided to present the information in the form of separate portions-visits. Each visit includes the results of tests and specialty consultations necessary to make a decision on further treatment. In the template developed by doctors and analysts, patient information is broken down into blocks that included complaints; anamnesis; physical examination; provisional diagnosis; diagnostic and treatment plan; tests’ results; administrations; final diagnosis; clinical report. These blocks served as the basis for the development of relational database tables. To visualize information about the virtual patient, prototypes of screen forms were implemented. Information about different visits was placed on different marks, and the user is able to see previously available information.Conclusion.After testing, this software will be used in education to demonstrate complete clinical cases to students. In addition, by each virtual case, tasks that require students to make medical decisions can be formed. The technology of virtual patients can be used both for postgraduates (doctors) and medical students.

Using the whole image and restrictions in the research of properties of some signature operations in Table Algebra

The features of the whole image relative to many binary relation, and restrictions on a binary relation on the set for some of the signature operations of Table Algebra are used in the work. Constructions of the whole image and restrictions are of general interest for Mathematics, and Table Algebra is a modern analogue of Codd's well-known Relational Algebra. It forms the theoretical foundation of modern query language databases. Elements of the carrier of Table Algebra specify relational table data structures, and signature operations are based on the basic table manipulations in Relational Algebra and SQL-like languages. The following results in the research of the features of the whole image were obtained: interconnections between the whole image and restrictions were found; the monotony and distribution of the whole image and restrictions on unions, a criterion of their emptiness and interconnections with first and second projection relations were proved; the whole image of the composition of relations and composition restrictions were found; the distribution of restriction on intersection of sets was set; the estimates of the distribution of the whole image of intersection and difference of sets were given; criteria for distribution of the whole image relative to the intersection and differences of sets were found. In addition, the clues were provided with the help of the whole image and restrictions on some of the signature operations of Table Algebra: intersection, union, difference, projection and joining. These representations allowed us to obtain some features of these operations, which derive directly from the features of the whole image and restrictions. It is supposed to get similar views on other signature operations of Table Algebras and to allocate their features arising from such representation. The obtained results can be used in the theory of Table Algebra as an approach to the research of the features of their signature operations, this can be used in query optimization in relational databases.

Fitting Relative Permeability’s Curves Based on Laboratory Production Data for A Thermal Composite Core Flooding Experiment

Numerical simulators are effective tools for an adequate understanding of models geological and dynamic properties under which enhanced oil recovery techniques are investigated. Core flooding experiments are usually conducted for calibrating simulated rock and fluid properties against actual test results at micro-scales, and for further scaling up processes to the reservoir scale. In this paper, laboratory experiments data were used as input for a numerical simulator to study the effect of relative permeability end points on production data. The laboratory experiments were completed to evaluate steam core flooding test performance and study the effect of steam on rock relative permeability’s. The test was performed utilizing a composite stack from a sandstone reservoir and super-heated steam at reservoir pressure. Test results provided numerous properties of rock and fluid properties, steam flooding data and relative permeability’s calculations. 3D core model was created with 28.89 cm length and 3.08 cm diameter. The skeleton was divided into 45×3×9 in x, y, z directions respectively, with 1215 total number of grid cells. Simulation model was initialized at the same condition of the actual laboratory experiment, and the resulted production data were utilized to match the relative permeability curves . The results confirmed that the production history is strongly affected by changes in relative permeability tables, particularly; the residual oil saturation (Sor) and the curve exponents values, by which they could effectively be utilized for fitting and optimizing relative permeability curves. Care should be taken when using the relative permeability data as input for reservoir simulation studies.

Comparative Study of LASSO, Ridge Regression, Preliminary Test and Stein-type Estimators for the Sparse Gaussian Regression Model

This paper compares the performance characteristics of penalty estimators, namely, LASSO and ridge regression (RR), with the least squares estimator (LSE), restricted estimator (RE), preliminary test estimator (PTE) and the Stein-type estimators. Under the assumption of orthonormal design matrix of a given regression model, we find that the RR estimator dominates the LSE, RE, PTE, Stein-type estimators and LASSO estimator uniformly, while, similar to Hansen (2013), neither LASSO nor LSE, PTE and Stein-Type estimators dominates the other. Our conclusions are based on the analysis of L_2-risks and relative risk efficiencies (RRE) together with the RRE related tables and graphs.

A Novel Approach to Data Extraction on Hyperlinked Webpages

The World Wide Web has an enormous amount of useful data presented as HTML tables. These tables are often linked to other web pages, providing further detailed information to certain attribute values. Extracting schema of such relational tables is a challenge due to the non-existence of a standard format and a lack of published algorithms. We downloaded 15,000 web pages using our in-house developed web-crawler, from various web sites. Tables from the HTML code were extracted and table rows were labeled with appropriate class labels. Conditional random fields (CRF) were used for the classification of table rows, and a nondeterministic finite automaton (NFA) algorithm was designed to identify simple, complex, hyperlinked, or non-linked tables. A simple schema for non-linked tables was extracted and for the linked-tables, relational schema in the form of primary and foreign-keys (PK and FK) were developed. Child tables were concatenated with the parent table’s attribute value (PK), serving as foreign keys (FKs). Resultantly, these tables could assist with performing better and stronger queries using the join operation. A manual checking of the linked web table results revealed a 99% precision and 68% recall values. Our 15,000-strong downloadable corpus and a novel algorithm will provide the basis for further research in this field.

Impact of macroeconomic indicators on housing prices

PurposeThis paper uses statistical analyses to quantify the effects of five major macroeconomic indicators, namely crude oil price, 30-year mortgage interest rate (IR), Consumer Price Index (CPI), Dow Jones Industrial Average (DJIA), and unemployment rate (UR), on housing prices over time.Design/methodology/approachHousing price is measured as housing price index (HPI) and is treated as a variable affecting itself. Actual housing sale prices in the Town of Amherst, New York State, USA, 1999-2008, and time-series data of the macroeconomic indicators, 2000-2017, were used in a vector autoregression statistical model to examine the data that show the greatest statistical significance and exert maximum quantitative effects of macroeconomic indicators on housing prices.FindingsThe analyses concluded that the 30-year IR and HPI have statistically significant effects on housing prices. IR has the highest effect, contributing 5.0 per cent of variance in the first month to 8.5 per cent in the twelfth. The UR has the next greatest influence followed by DJIA and CPI. The disturbance from HPI itself causes the greatest variability in future prices: up to 92.7 per cent in variance 1 month ahead and approximately 74.5 per cent 12 months ahead. This result indicates that current changes in house prices heavily influence people’s expectation of future prices. The total effect of the error variance of the macroeconomic indicators ranged from 7.3 per cent in the first month to 25.5 per cent in the twelfth.Originality/valueThe conclusions in this paper, along with related tables and figures, will be useful to the housing and real estate communities in planning their business for the next years.

Deep unsupervised cardinality estimation

Cardinality estimation has long been grounded in statistical tools for density estimation. To capture the rich multivariate distributions of relational tables, we propose the use of a new type of high-capacity statistical model: deep autoregressive models. However, direct application of these models leads to a limited estimator that is prohibitively expensive to evaluate for range or wildcard predicates. To produce a truly usable estimator, we develop a Monte Carlo integration scheme on top of autoregressive models that can efficiently handle range queries with dozens of dimensions or more.Like classical synopses, our estimator summarizes the data without supervision. Unlike previous solutions, we approximate the joint data distribution without any independence assumptions. Evaluated on real-world datasets and compared against real systems and dominant families of techniques, our estimator achieves single-digit multiplicative error at tail, an up to 90x accuracy improvement over the second best method, and is space- and runtime-efficient.

General axisymmetric active earth pressure obtained by the characteristics method based on circumferential geometric condition

Existing solutions for axisymmetric active earth pressure are based on certain hypotheses of the circumferential stress, lacking of strict basis. This article presents a technique for deriving the actual circumferential stress according to the circumferential geometric condition, the Drucker-Prager criterion and incremental theory. Based on the actual circumferential stress, a new characteristics method for determining the axisymmetric active earth pressure in plastic flow is developed in this article. In this new method, the inclined angle of boundaries, interface friction of contact interface, dilatation effect and flow velocity of soil are considered at the same time. The validity of the new method is confirmed using several sets of experimental data from the literature. The pressure coefficients are investigated individually in detail, and some different conclusions are found. Finally, a practical formula for calculating axisymmetric active earth pressure is presented based on the linear superposition principle, and related tables of coefficients are also provided for engineering application.

Fusion OLAP: Fusing the Pros of MOLAP and ROLAP Together for In-Memory OLAP

OLAP models can be categorized with two types: MOLAP (multidimensional OLAP) and ROLAP (relational OLAP). In particular, MOLAP is efficient in multidimensional computing at the cost of cube maintenance, while ROLAP reduces the data storage size at the cost of expensive multidimensional join operations. In this paper, we propose a novel Fusion OLAP model to fuse the multidimensional computing model and relational storage model together to make the best aspects of both MOLAP and ROLAP worlds. This is achieved by mapping the relation tables into virtual multidimensional model and binding the multidimensional operations into a set of vector indexes to enable multidimensional computing on relation tables. The Fusion OLAP model can be integrated into the state-of-the-art in-memory databases with additional surrogate key indexes and vector indexes. We compared the Fusion OLAP implementations with three leading analytical in-memory databases. Our comprehensive experimental results show that Fusion OLAP implementation can achieve up to 35, 365, and 169 percent performance improvements based on the Hyper, Vectorwise, and MonetDB databases, respectively, for the Star Schema Benchmark (SSB) with scale factor 100.

Ten years of knowledge representation for health care (2009-2018): Topics, trends, and challenges.

In the last ten years, the international workshop on knowledge representation for health care (KR4HC) has hosted outstanding contributions of the artificial intelligence in medicine community pertaining to the formalization and representation of medical knowledge for supporting clinical care. Contributions regarding modeling languages, technologies and methodologies to produce these models, their incorporation into medical decision support systems, and practical applications in concrete medical settings have been the main contributions and the basis to define the evolution of this field across Europe and worldwide. Carry out a review of the papers accepted in KR4HC in the 2009-2018 decade, analyze and characterize the topics and trends within this field, and identify challenges for the evolution of the area in the near future. We reviewed the title, the abstract, and the keywords of the 112 papers that were accepted to the workshop, identified the medical and technological topics involved in these works, provided a classification of these papers in medical and technological perspectives and obtained the timeline of these topics in order to determine interest growths and declines. The experience of the authors in the field and the evidences after the review were the basis to propose a list of challenges of knowledge representation in health care for the future. The most generic knowledge representation methods are ontologies (31%), semantic web related formalisms (26%), decision tables and rules (19%), logic (14%), and probabilistic models (10%). From a medical informatics perspective, knowledge is mainly represented as computer interpretable clinical guidelines (43%), medical domain ontologies (26%), and electronic health care records (22%). Within the knowledge lifecycle, contributions are found in knowledge generation (38%), knowledge specification (24%), exception detection and management (12%), knowledge enactment (8%), temporal knowledge and reasoning (7%), and knowledge sharing and maintenance (7%). The clinical emphasis of knowledge is mainly related to clinical treatments (27%), diagnosis (13%), clinical quality indicators (13%), and guideline integration for multimorbid patients (12%). According to the level of development of the works presented, we distinguished four maturity levels: formal (22%), implementation (52%), testing (13%), and deployment (2%) levels. Some papers described technologies for specific clinical issues or diseases, mainly cancer (22%) and diseases of the circulatory system (20%). Chronicity and comorbidity were present in 10% and 8% of the papers, respectively. KR4HC is a stable community, still active after ten years. A persistent focus has been knowledge representation, with an emphasis on semantic-web ontologies and on clinical-guideline based decision-support. Among others, two topics receive growing attention: integration of computer-interpretable guideline knowledge for the management of multimorbidity patients, and patient empowerment and patient-centric care.

Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels

This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standard language that allows defining customized mappings from relational databases to RDF datasets. In this work, data are spatiotemporal in nature; therefore, R2RML must be adapted to allow producing spatiotemporal Linked Open Data.Data generated in this way are used to populate a SPARQL endpoint, where queries are submitted and the result can be displayed on a map. This endpoint is implemented using Strabon, a spatiotemporal RDF triple store built by extending the RDF store Sesame. The first part of the paper describes how R2RML is adapted to allow producing spatial RDF data and to support XML data sources. These techniques are then used to map data about cultural events and public transport in Brussels into RDF. Spatial data are stored in the form of stRDF triples, the format required by Strabon. In addition, the endpoint is enriched with external data obtained from the Linked Open Data Cloud, from sites like DBpedia, Geonames, and LinkedGeoData, to provide context for analysis. The second part of the paper shows, through a comprehensive set of the spatial extension to SPARQL (stSPARQL) queries, how the endpoint can be exploited.

Synergistic graph and SQL analytics inside IBM Db2

To meet the challenge of analyzing rapidly growing graph and network data created by modern applications, a large number of specialized graph databases have emerged, such as Neo4j, JanusGraph, and Sqlg. At the same time, RDBMSs and SQL continue to support mission-critical business analytics. However, real-life analytical applications seldom contain only one type of analytics. They are often made of heterogeneous workloads, including SQL, machine learning, graph, and other analytics. In particular, SQL and graph analytics are usually accompanied together in one analytical workload. This means that graph and SQL analytics need to be synergistic with each other. Unfortunately, most existing graph databases are standalone and cannot easily integrate with relational databases. In addition, as a matter of fact, many graph data (data about relationships between objects or people) are already prevalent in relational databases, although they are not explicitly stored as graphs. Performing graph analytics on these relational graph data today requires exporting large amount of data to the specialized graph databases. A natural question arises: can SQL and graph analytics be performed synergistically in a same system? In this demo, we present such a working system called IBM Db2 Graph. Db2 Graph is an in-DBMS graph query approach. It is implemented as a layer inside an experimental IBM Db2™, and thus can support synergistic graph and SQL analytics efficiently. Db2 Graph employs a graph overlay approach to expose a graph view of the relational data. This approach flexibly retrofits graph queries to existing graph data stored in relational tables. We use an example scenario on health insurance claim analysis to demonstrate how Db2 Graph is used to support synergistic graph and SQL analytics inside Db2.

Assessment of drip lateral design methods based on uniformity coefficient

In this paper, six drip lateral design methods were selected and a comparative assessment was done to find its practical applicability for finding accurate uniformity coefficient. Step-By-Step (SBS) method, Differential method (DM), Constant Discharge method (CDM), Variable discharge method (VDM), Outlet variation method (OVM) and Statistical method (STM) were the different methods assessed. The percentage relative error in calculating the uniformity coefficient by different methods were obtained as the difference between step-by-step method (true) value and alternate method (observed) value. These errors were tabulated. VDM and OVM method performed well with equal accuracy to SBS method at different slopes. For L=250m, DM method performed well. The STM performed good for down slope and lateral length of 250m with 6 per cent relative error. The method having lesser relative percentage error can be selected by the design engineers for designing the laterals from the relative percentage error tables.