Relational Database Applications Research Articles

Picture Fuzzy Relations over Picture Fuzzy Sets

Nowadays, picture fuzzy set theory is a flourishing field in mathematics with uncertainty by incorporating the concept of positive, negative and neutral membership degrees of an object. A traditional crisp relation represents the satisfaction or the dissatisfaction of relationship, connection or correspondence between the objects of two or more sets. However, there are some problems that can’t be solved through classical relationships, such as the relationship between two objects being vague. In those situations, picture fuzzy relation over picture fuzzy sets is an important and powerful concept which is suitable for describing correspondences between two vague objects. It represents the strength of association of the elements of picture fuzzy sets. It plays an important role in picture fuzzy modeling, inference and control system and also has important applications in relational databases, approximate reasoning, preference modeling, medical diagnosis, etc. In this article, we define picture fuzzy relations over picture fuzzy sets, including some other fundamental definitions with illustrations. The max-min and min-max compositions of picture fuzzy relations are defined in the light of picture fuzzy sets and discussed some properties related to them. The reflexivity, symmetry and transitivity of a picture fuzzy relation are described over a picture fuzzy set. Finally, various properties are explored related to the picture fuzzy relations over a picture fuzzy set.

Serving deep learning models with deduplication from relational databases

Serving deep learning models from relational databases brings significant benefits. First, features extracted from databases do not need to be transferred to any decoupled deep learning systems for inferences, and thus the system management overhead can be significantly reduced. Second, in a relational database, data management along the storage hierarchy is fully integrated with query processing, and thus it can continue model serving even if the working set size exceeds the available memory. Applying model deduplication can greatly reduce the storage space, memory footprint, cache misses, and inference latency. However, existing data deduplication techniques are not applicable to the deep learning model serving applications in relational databases. They do not consider the impacts on model inference accuracy as well as the inconsistency between tensor blocks and database pages. This work proposed synergistic storage optimization techniques for duplication detection, page packing, and caching, to enhance database systems for model serving. Evaluation results show that our proposed techniques significantly improved the storage efficiency and the model inference latency, and outperformed existing deep learning frameworks in targeting scenarios.

Upaya Peningkatan Kemampuan Penggunaan Microsoft Access Programming Bagi Pegawai Unit Usaha Bank Sumut Syariah

This training aims to improve the ability to use microsoft access programming for employees of the Bank Sumut Syariah business unit. This training was attended by all employees because this training is considered very important to support the performance of the employees. Currently, the Bank Sumut Syariah business unit has implemented technology based on Microsoft Access Programming in the context of carrying out all office activities. This training is carried out by means of socialization to employees, discussions, training and also direct practice of its use. The service activities for the Microsoft Access Programming Training have been carried out well. The service activity for the Microsoft Access Programming Training received an enthusiastic response from the participants of the Bank Sumut Syariah unit employees. Microsoft Access Programming training is carried out in stages and distributed in 14 meetings with a student center learning system and project based learning model so that employees can solve work problems with the skills that have been taught. Microsoft Access is a relational computer database application program that is used to design, create and process various types of data with large capacities. Database is a collection of related tables. Between tables with one another are related to each other, so it is often called a relational database. The relations between tables are connected by a key, namely the primary key and foreign key

Унифицированное применение методов онтологического инжиниринга в задачах обработки текстовых данных

Unified application issues of ontological engineering methods and tools for text data processing automation in 2 problems classes solving are considered. The first class is the relational database applications construction automation based on the necessary facts extracting directly from unstructured text documents collections in natural language. The second class is the text data processing automation in artificial languages in the program code verifying process for database applications. The information systems designing and developing problems, same as program code verifying problems, are complex for non-professional programmers. The text data processing problem solving automation is also relevant for professional programmers, because it significantly reduces the database applications development time. The ontologically controlled solution concept is proposed for these problems. An unified approach for problems solution and the tools demos implementation are described.

CLOTHO: directed test generation for weakly consistent database systems

Relational database applications are notoriously difficult to test and debug. Concurrent execution of database transactions may violate complex structural invariants that constraint how changes to the contents of one (shared) table affect the contents of another. Simplifying the underlying concurrency model is one way to ameliorate the difficulty of understanding how concurrent accesses and updates can affect database state with respect to these sophisticated properties. Enforcing serializable execution of all transactions achieves this simplification, but it comes at a significant price in performance, especially at scale, where database state is often replicated to improve latency and availability. To address these challenges, this paper presents a novel testing framework for detecting serializability violations in (SQL) database-backed Java applications executing on weakly-consistent storage systems. We manifest our approach in a tool, CLOTHO, that combines a static analyzer and model checker to generate abstract executions, discover serializability violations in these executions, and translate them back into concrete test inputs suitable for deployment in a test environment. To the best of our knowledge, CLOTHO, is the first automated test generation facility for identifying serializability anomalies of Java applications intended to operate in geo-replicated distributed environments. An experimental evaluation on a set of industry-standard benchmarks demonstrates the utility of our approach.

A laboratory information management system for the analysis of tritium (3H) in environmental waters

Accurate and precise measurements of low levels of tritium (3H) in environmental waters are difficult to attain due to complex steps of sample preparation, electrolytic enrichment, liquid scintillation decay counting, and extensive data processing. We present a Microsoft Access™ relational database application, TRIMS (Tritium Information Management System) to assist with sample and data processing of tritium analysis by managing the processes from sample registration and analysis to reporting and archiving. A complete uncertainty propagation algorithm ensures tritium results are reported with robust uncertainty metrics. TRIMS will help to increase laboratory productivity and improve the accuracy and precision of 3H assays. The software supports several enrichment protocols and LSC counter types. TRIMS is available for download at no cost from the IAEA at www.iaea.org/water.

Multikernel Data Partitioning With Channel on OpenCL-Based FPGAs

Recently, field-programmable gate array (FPGA) vendors (such as Altera) have started to address the programmability issues of FPGAs via OpenCL SDKs. In this paper, we analyze the performance of relational database applications on FPGAs using OpenCL. In particular, we study how to improve the performance of data partitioning, which is a very important building block in relational database. Since the data partitioning causes random memory accesses, it is time-consuming, and then, it has been the major bottleneck for database operators, such as partitioned hash join. In particular, we import the state-of-the-art OpenCL implementation of data partitioning from OmniDB, which was originally designed and optimized for CPUs/GPUs, and we find that this implementation suffers from both lock overhead and memory bandwidth overhead. Accordingly, we present a multikernel approach to address the lock overhead by leveraging two emerging features ( task kernel and channel ) from Altera OpenCL software development kit. In order to reduce the memory bandwidth overhead, on-chip buckets are used to reduce the number of random global memory transactions. We further develop an FPGA-specific cost model to guide the parameter configuration. We evaluate the proposed design on a recent OpenCL-based FPGA. We have applied our optimized partitioning method to a number of data processing tasks, including hash join, histogram, and hash search. Our experimental results demonstrate that our cost model can accurately guide the user to determine the optimal parameter combination for data partitioning and the optimal parameter combination can achieve $16.6\times$ speedup over the default multithreaded implementation.

An object triple mapping system supporting detached objects: A performance and memory usage empirical comparison

The development and use of ontologies in creating more intelligent and effective applications have increased in recent years. This rise in popularity is due to the potential of ontologies in providing semantics for the data consumed by machines, allowing them to reason on these data. Providing sophisticated tools that improve the development of applications based on RDF and OWL can further accelerate the adoption of the Semantic Web. In this context, some types of ontology tools have been proposed, for instance, ontology editors, ontology reasoners, triple store tools, RDF frameworks and object triple mapping (OTM) systems. In particular, OTM systems (e.g., AliBaba, KOMMA, JOINT and so on) are of utmost importance for developing ontology-based applications through the object-oriented paradigm. They map RDF triples into data objects, enabling developers to handle RDF triples as objects in object-oriented applications. In a similar way, developers of relational database applications have been using object-relational mapping (ORM) systems, for example Hibernate, to map relational databases into objects as well as to manage the object states. The main object state that Hibernate provides is the detached one; however, except for Empire, current OTM systems do not provide detached objects. The great difference between these two types of objects is that the former one has its life cycle independent of the underlying database connection, while the latter one is bound to the connection. In this way, this paper presents an object triple mapping system that supports detached objects, named JOINT-Detached (JOINT-DE). By using JOINT-DE, developers of ontology-based applications can (i) use the objects coming from the triple store as objects of the business model, (ii) use such objects as data transfer objects (DTOs) between subsystems, and (iii) use of less resources (triple store connections) to load object properties. To evaluate the proposed tool, we first describe how we conducted an experiment to empirically compare our tool with another OTM widely used by the community. We measure performance and memory usage regarding create, retrieve and update operations. Our results indicate that: (1) JOINT-DE has better performance results in all three operations; (2) JOINT-DE has an advantage over AliBaba with respect to the memory usage in the retrieve operation; (3) AliBaba uses less memory than JOINT-DE in the update operation; and (4) we could not find statistically significant differences between the tools regarding memory usage in the create operation. Finally, to illustrate the benefits of the proposed system, a case study of a real application is presented, outlining the architectural limitations of the application using an existing OTM in the literature, as well as showing positive results to the use of JOINT-DE.

Modelling Test Views for Graph Database Applications

Since NoSQL databases use data models, access modes and query languages that differ from the relational databases, the testing NoSQL database applications raises new challenges. There has been much attention to testing relational database applications, however testing NoSQL database applications is an area that has been hardly explored. This paper describes a model-based approach that allows the tester to model the important features of a graph database application to be tested, called test views. These test views are used to derive the test requirements that guide the generation of test cases. The approach is illustrated with an application that represents a real-world problem related with access control. The results show that using this model-based approach leads to test cases that are able to reveal faults and failures in both system specification and implementation.

TO WARDS DATA PERSIST ENCY IN REAL-TIME ONLINE INTERACTIVE APPLIC ATIONS

The class of distributed Real-time O nline Interactive Applications (ROIA) includes such important applications as Massively Multiplayer Online Games (MMOGs), as well as interactive e-Learning a nd simulation systems. These applications usually work in a persistent environment (also called world) which continues to exist and evolve also while the user is offline and away from the application. The challenge is how to efficiently make the world and the player characters persistent in the system over time. In this paper, we deal with storing persistent data of real-time interactive applications in modern relational databases. We analyze the major requirements to a system for persistency and we describe a preliminary design of the Entity Persistence Module (EPM) middleware which liberates the application developer from writing and maintaining complex a nd error-prone code for persistent data management. EPM automatically performs the mapping operations to store/ retrieve the complex data to/from different types of relational databases, supports the management of persistent data in memory, and integrates it into the main loop of the ROIA client-server architecture.

Facilitating the interaction with data warehouse schemas through a visual web-based approach

In most respects, there are implicit drawbacks concerning representation and interaction with data in relational-database applications. On the one hand, there is a lack of expressiveness and ease of use in the user interfaces that handle such data. On the other hand, there is an implicit need for interactive end-user visual tools to query data and avoid dependency on programming languages. The main aim of this work is to study the problem of database interaction and usability, comparing existing solutions and providing a new approach that overcomes existing problems. We propose a web-based tool that manipulates Data Warehouse schemas by using a visual language to represent the database structure and providing several visualization techniques that facilitate the interaction and creation of queries involving different levels of complexity. We based our research on an End-User Development approach that has been evaluated to obtain some initial usability indicators.

Reusable Business Tier Components

Call Level Interfaces (CLI) are software API used for building business tiers of relational database applications whenever performance is a key requirement. Nevertheless, their use is cumbersome, mainly in large database applications with many and complex Create, Read, Update and Delete (CRUD) expressions. CLI are low level API conveying several difficulties during the development process of relational business tiers. Four of them are herein emphasized: 1) Programmers need to master the schemas of the underlying databases; 2) the same CRUD expression is frequently re-written to address different business needs; 3) CLI are not suited to cope with evolving business tiers and, finally, 4) CLI do not provide any feature to decouple development process of relational business tiers from the development process of application tiers. To tackle these difficulties, this paper proposes an architecture for building reusable relational business tier components based on CLI herein referred to as the Reusable Business Tier Architecture (RBTA). It relies on a customizable wide typed service to address a business area, such as accountability. The typed service is able to manage CRUD expressions, deployed at runtime, on behalf of application tiers and in accordance with users' needs. The only constraint is that the required service to manage each CRUD expression must be a sub-set of the implemented wide typed service. A proof of concept is also presented.

Optimizing the Intelligent Generic Query Mode and its Interface for Relational Database Applications

This research presents an optimization for generic query mode for any database application. It is an enhancement for a previously research Improving the Query Mode and its Interface for Relational Database Applications. The research improved its intelligence more than expected. In the previous research the algorithm was intelligent in the sense that it answers most of the possible queries or questions that may arise in the user’s mind without the need or support of the application developer but there was a restriction for that which is the user can't query about any computed field. This research added this feature to the algorithm regardless the depth of the computed field. The meaning of the depth of the computed field is how many times of the computed field in an equation needs to be transformed so that it contains no computed fields. It has been implemented using PowerBuilder (release 11.5) as a front end tool and Adaptive Server Anywhere (one of Sybase products) as a database engine. This research describes the design of the optimized intelligent generic query mode and its interface.

Prioritized fuzzy logic based information processing in relational databases

Many years of research related to fuzzy logic and fuzzy set theory extensions to relational databases have not lead to stable implementations, standardized languages or fuzzy relational database application development tools and methods. The main goal of this paper is the modelling and the implementation of a set of tools that allow usage of fuzzy logic enriched with priorities in relational database applications. In order to achieve that goal, at first, the relational data model is extended with the elements of fuzzy set theory. After that, a fuzzy extension of the SQL query language, called the PFSQL, is defined. An interpreter for that language is integrated inside an implementation of the fuzzy JDBC driver. An implementation of the CASE tool for modelling of fuzzy relational database schemas rounds up a set of tools for the implementation of Java fuzzy database applications. In this sense, this paper presents a step towards a methodology for the fuzzy relational database application development.

A Relational Database Complexity Computing Model

In this paper we have proposed a model to compute the complexity of small relational database application developed in MS Access. The model was built using different database objects. These objects were categorized based upon the basis of weights assigned to their complexity determining factors. We have implemented our model in a tool called SMARtS. We used our model to compute complexity of eight database projects. To evaluate our model, we analyzed the calculated complexity and actual effort. We found that our model successfully captured the complexity of different database projects. Correlation analysis has shown that complexities computed by SMARtS and the actual efforts are strongly correlated.

Towards the methodology for development of fuzzy relational database applications

In this paper we examine the possibilities to extend the relational data model with the mechanisms that can handle imprecise, uncertain and inconsistent attribute values using fuzzy logic and fuzzy sets. We present a fuzzy relational data model which we use for fuzzy knowledge representation in relational databases that guarantees the model in 3rd normal form. We also describe the CASE tool for the fuzzy database model development which is apparently the first implementation of such a CASE tool. In this sense, this paper presents a leap forward towards the specification of a methodology for fuzzy relational database applications development.

The Surgical Intensive Care-infection Registry: a research registry with daily clinical support capabilities.

Infections in the surgical and trauma intensive care unit (STICU) are responsible for significant patient morbidity and mortality. Research into these infectious complications often uses administrative databases or clinical information systems designed for documenting and billing daily patient care. Neither of these sources is intended for research, and many investigators have questioned their accuracy. The Surgical Intensive Care-Infection Registry (SIC-IR) was developed as a research data repository to use to monitor STICU infections. SIC-IR is a relational database application designed to collect quality data and to integrate with daily patient care. SIC-IR prospectively collects and archives more than 100 clinical variables daily on each STICU patient to ensure completeness and correctness of the registry. Furthermore, SIC-IR aids in clinical activities by providing patient summaries and medical record documentation. SIC-IR provides accurate data for STICU infection research and enables the users to easily undertake quality-of-care improvement initiatives.

Reverse engineering relational databases to identify and specify basic Web services with respect to service oriented computing

Service-oriented computing (SOC) is the computing paradigm that utilizes services as a fundamental building block. Services are self-describing, open components intended to support composition of distributed applications. Currently, Web services provide a standard-based realization of SOC due to: (1) the machine-readable format (XML) of their functional and nonfunctional specifications, and (2) their messaging protocols built on top of the Internet. However, how to methodologically identify, specify, design, deploy and manage a sound and complete set of Web services to move to a service-oriented architecture (SOA) is still an issue. This paper describes a process for reverse engineering relational database applications architecture into SOA architecture, where SQL statements are insulated from the applications, factored, implemented, and registered as Web services to be discovered, selected, and reused in composing e-business solutions. The process is based on two types of design patterns: schema transformation pattern and CRUD operations pattern. First, the schema transformation pattern allows an identification of the services. Then the CRUD operations pattern allows a specification of the abstract part of the identified services, namely their port types. This process is implemented as a CASE tool, which assists analysts specifying services that implement common, reusable, basic business logic and data manipulation.

New systematic data utilization for monitoring surveys in Lake Biwa

Lake monitoring surveys data are vital and have been being accumulated for every lake. However data itself, without effective data management and interpretation, cannot be used to tell the story or history of the lake. Therefore, this project aims to develop a new water quality database system for a lake with systematical functions to utilize such data effectively and to satisfy both general public users and specialists. Lake Biwa was chosen as the target lake, where long-term monitoring data were available for almost one hundred years. A relational database application, Access 2002, with the help of Macro functions and VBA (Visual Basic for Applications) was introduced to organize all of the data. With the systematical storing of data, valuable data could be easily accessed, filtered and powerfully utilized for researchers own interests. The filtered data can be written into basic documents (spreadsheet or text files), provided for outside requests, and again used for further basic and advanced analysis by a reading back process. The system supports multiple users, especially public users by providing user interface system and visualized result displays. The final outcomes from this systematic data utilization can be fruitfully used as the guideline for effective monitoring management program of lake water quality.

Management and Visualization of Whole Genome Shotgun Assemblies Using SAM

We have designed and implemented a system to manage whole genome shotgun sequences and whole genome sequence assembly data flow. The Sequence Assembly Manager (SAM) consists primarily of a MySQL relational database and Perl applications designed to easily manipulate and coordinate the analysis of sequence information and to view and report genome assembly progress through its Common Gateway Interface (CGI) web interface. The application includes a tool to compare sequence assemblies to fingerprint maps that has been used successfully to improve and validate both maps and sequence assemblies of the Rhodococcus sp.RHAI and Cryptococcus neoformans WM276 genomes.