Stored Procedures—Part 2

Modern relational database management systems provide advanced features allowing, for example, to include behaviour directly inside the database (stored procedures). These features raise new difficulties when a database needs to evolve (e.g. adding a new table). To get a better understanding of these difficulties, we recorded and studied the actions of a database architect during a complex evolution of the database at the core of a software system. From our analysis, problems faced by the database architect are extracted, generalized and explored through the prism of software engineering. Six problems are identified: (1) difficulty in analysing and visualising dependencies between database's entities, (2) difficulty in evaluating the impact of a modification on the database, (3) replicating the evolution of the database schema on other instances of the database, (4) difficulty in testing database's functionalities, (5) lack of synchronization between the IDE's internal model of the database and the database actual state and (6) absence of an integrated tool enabling the architect to search for dependencies between entities, generate a patch or access an up to date PostgreSQL documentation. We suggest that techniques developed by the software engineering community could be adapted to help in the development and evolution of relational databases.

The development of the interval analysis theory and its applications in solving applied problems led to the need to collect, store and extract efficiently interval-significant data in relational databases. Modern relational database management systems (DBMS) either allow to work with built-in data types which however are not friendly for use or provide the ability to create your own user-defined data types in several ways. The article describes the creation of a user-defined data type iInterval, functions and aggregates to work with interval data in MS SQL Server using the Common Language Runtime (CLR).

Consumer is the most important thing that needs to be considered by a company. Consumers will remain loyal to the company if they feel satisfied with the product and servise provided by the company. Matahari Departement Store is one of the departement store in Jember wich has a loyal customer to them. This study was to determine the effect of product quality and servise quality on customer loyalty Matahari Departement Store. The data used is primary data wich one type of data based on its source which usually obtained by field survei using all the original data collection methods. The type of data in this study are ordinal data. The sample used as many as 60 respondents. The analytical tool used is multiple linear regression with a significance level of 5% or 95% confidence internal. Regression results show that partially X1 (product quality) is significant. X2 (quality product) is significant too. Simultaneously indicates that all independent variabels (quality products and quality service) effect simultaneously on customer loyality. R square 0,785 wich means that 78,5% change of customer loyality caused by the product quality and service quality.

The current development of blockchain, technically speaking, still faces many key problems such as efficiency and scalability issues, and any distributed system faces the problem of how to balance consistency, availability, and fault tolerance need to be solved urgently. The advantage of blockchain is decentralization, and the most important thing in a decentralized system is how to make nodes reach a consensus quickly. This research mainly discusses the blockchain and K-means algorithm for edge AI computing. The natural pan-central distributed trustworthiness of blockchain provides new ideas for designing the framework and paradigm of edge AI computing. In edge AI computing, multiple devices running AI algorithms are scattered across the edge network. When it comes to decentralized management, blockchain is the underlying technology of the Bitcoin system. Due to its characteristics of immutability, traceability, and consensus mechanism of transaction data storage, it has recently received extensive attention. Blockchain technology is essentially a public ledger. This is done by recording data related to trust management to this ledger. To collaboratively complete artificial intelligence computing tasks or jointly make intelligent group decisions, frequent communication is required between these devices. By integrating idle computing resources in an area, a distributed edge computing platform is formed. Users obtain benefits by sharing their computing resources, and nodes in need complete computing tasks through the shared platform. In view of the identity security problems faced in the sharing process, this article introduces blockchain technology to realize the trust between users. All participants must register a secure identity in the blockchain network and conduct transactions in this security system. A K-means algorithm suitable for edge environments is proposed to identify different degradation stages of equipment operation reflected by multiple types of data. Based on the prediction of the fault state for a single type of data, the algorithm uses the historical data of multiple types of data together with the prediction data to predict the fault stage. During the research process, the average optimization energy consumption of K-means algorithm is 14.6% lower than that of GA. On the basis of designing a resource allocation scheme based on blockchain, the problem of how the participants can realize reliable resource use according to the recorded data on the chain is studied. The article implements the verification of the legality of the use of blockchain resources. In addition, a control node is introduced to master the global real-time information of the network to provide data support for the user's choice.

<p>Availability of historical hydroclimatic data for different climate regions is necessary for hydrological change modeling and analysis. Nowadays, many global products are available that provide hydrological and meteorological datasets based on direct measurements, remote sensing observations, re-analysis outputs, and model simulations. However, differences in spatial and temporal resolutions, and inconsistencies seen between observed hydrological patterns and different model results and datasets makes it difficult to choose an appropriate combination of data products for hydrological studies. This study provides a new combined historical database of five key hydroclimatic variables at monthly and daily scales, obtained from different observational and re-analysis global datasets, including runoff (R; from GSIM), precipitation (P; from GPCC-V7 and ERA5), evapotranspiration (ET; from GLEAM 3.3 and ERA5), soil moisture (SM; from ESACCI-v04.5, GLEAM 3.3 and ERA5), and temperature (T; GHCN-CAMS, ERA5). The new database combines these variables for each of 6,400 catchments of different scales around the world. In order to select the catchments, the existing nearly 35,000 streamflow time series in the GSIM database was analyzed and 8,400 catchments were selected based on the criterion of having at least 25 years of monthly runoff data available from 1980 to 2010. After further quality controls on the accuracy of catchment polygons, and reported catchment areas and stream flows, and consistency of the range, average values, and variations of variables time series, the 6,400 catchments were selected for the final development of the new catchment-related database in this study. The other hydroclimatic variables, besides runoff, are also spatially aggregated for each individual catchment and corresponding catchment-average time series are produced from 1980 to 2019. The final database thus provides a collection of long-term multi-climate and multi-catchment time series of the five key hydroclimate variables, aggregated over each of the 6,400 hydrological catchments around the world. In choosing the data sources for each variable, first priority was given to direct observational datasets (available for all variables except for the ET), and further to re-analysis outputs that many researchers regard as being close to directly observed data. The database developed in this study can be used for different types of studies on hydrology, water resources, and their changes under shifting climate and land use conditions in different parts of the world. The standardized format of this database ensures easy applicability with possibility of expansion to include more and other types of data, e.g., on land use/cover types and their changes, and on other climatic, geomorphologic, and anthropogenic conditions.</p>

The basis of each IT system is data exchange both between individual modules of program and between program and user. The number of exchanged data and the number of operations on the data, which should be performed, require application of professional tools allowing for collecting and performing operations on multiple types of data. One of these tools are databases, which are an essential part of any IT system. With database designing are connected many decision problems which can occur both during the construction of database management system and at the stage of integration of entire user application with developed database. The article presents typical decision problems connected with designing of databases. These problems mainly concern sphere of information technology (including the programming language or recovery mechanism of database after the failure). Database architecture for typical IT system from the point of view possible paths for users were discussed, and role of catalogues played in development of database were presented. In addition, modular structure of the database, which was developed for the system SIMMAG3D for modelling and visualization of warehouse facilities in 3D was shown. This system is being developed under a project financed by the National Centre for Research and Development. We discussed in detail one of the essential elements in developed database - catalogues of means of external and internal transport, non-mechanical equipment and accessories which are essential from the point of view of the work load.

Pathologists are required to integrate data from multiple sources when making a diagnosis. Furthermore, whole slide imaging (WSI) and next generation sequencing will escalate data size and complexity. Development of well-designed databases that can allow efficient navigation between multiple data types is necessary for both clinical and research purposes. We developed and evaluated an interactive, web-based database that integrates clinical, histologic, immunohistochemical and genetic information to aid in pathologic diagnosis and interpretation with nine lung adenocarcinoma cases. To minimize sectioning artifacts, representative blocks were serially sectioned using automated tissue sectioning (Kurabo Industries, Osaka Japan) and selected slides were stained by multiple techniques, (hematoxylin and eosin [H&E], immunohistochemistry [IHC] or fluorescence in situ hybridization [FISH]). Slides were digitized by WSI scanners. An interactive relational database was designed based on a list of proposed fields covering a variety of clinical, pathologic and molecular parameters. By focusing on the three main tasks of 1.) efficient management of textual information, 2.) effective viewing of all varieties of stained whole slide images (WSI), and 3.) assistance in evaluating WSI with computer-aided diagnosis, this database prototype shows great promise for multi-modality research and diagnosis.

SystemVerilog enables modeling at a higher level of abstraction through the use of 2-state data types, enumerated types, and user-defined types. These are complemented by new specialized always procedural blocks, always_comb, always_ff and always_latch. These and other new modeling constructs have been discussed in the previous chapters of this book.

Wireless communication that provides voice only is not sufficient to support the necessity of user. In the future, the major advantage of third generation wireless communication (3G) are providing packet data communication, mobile Internet, and mobile multimedia data communication. This kind of data type requires more bandwidth to transmit data. Sometimes, the communication would be encountered the transmitting block because the new cell has no enough resource allocating to mobile station (MS or MH) in handoff. How to reduce the losing probability of data packets in wireless communication networks is important things which can raise the quality of service (QoS) and degrade the time and resource consume. In this paper, a resource reservation method is proposed to improve QoS and resource switching management to reduce data packet loss for multimedia communication at handoff operation.

3 - Introduction to interMedia Storage

The application, development and key matters of applying spatio-temporal GIS to traffic information management system are discussed in this paper by introducing the development of spatio-temporal database, current models of spatio-temporal data, traits of traffic information management system. This paper proposes a method of organizing spatio-temporal data taking road object changes into consideration, and describes its data structure in 3 aspects, including structure of spatio-temporal object, organizing method spatio-temporal data and storage means of spatio-temporal data. Trying to manage types of spatio-temporal data involved in traffic system, such as road information, river information, railway information, social and economical data, and etc, uniformly, efficiently and with low redundancy.

Business intelligence today covers the elements of information technology, accounting management, business analysis and marketing. It enables collection, analysis, distribution and acting based on the business information and for the purpose of easier solving of management problems and making of best business decisions. So, business intelligence system originally intended for the decision makers even though in todaypsilas modern conditions of new economies decisions are made by majority of the managers in the company. SQL server 2008 and Visual Studio 2005 together offer deeper integration between the data base in the application development then ever before. Programmers now have the possibility to create a CLR stored procedure, function and user defined types directly from Visual Studio development environment. Other then that, Visual Studio 2005 supports all new SQL Server data types. Business Intelligence with Office Share Point Server 2007 system facilitate to people who make decisions to access information and analyze them at any time, anywhere. Managers in the trading company can use updated information wherever people are working, cooperate and make decisions regardless whether this is on desktop or via Web.

Despite its decade long history, object database technology has never entered mainstream system development. In this work, I look at the background of the slow adoption, and the possible future outlook of this technology based on my personal experience and the published literature. Object databases represent a revolutionary new technology and provide superior storage facility for complex data structures and types. They also enable close language binding and a unified development process. It is a mature technology with advanced database management and development features and has several proven and robust deployment examples. Besides its current technical excellence, this technology is also demonstrating future potential through such emerging technologies as Java, Application servers, and XML. The past failure of object databases to proliferate the market was mainly due to unawareness, lack of skills, and the overwhelming existing investment in relational systems. As these factors are changing by the end of this century and new technology adoption is accelerating, object databases are looking forward to a slow but sure take off.

There is an urgent need for large‐scale botanical data to improve our understanding of community assembly, coexistence, biogeography, evolution, and many other fundamental biological processes. Understanding these processes is critical for predicting and handling human‐biodiversity interactions and global change dynamics such as food and energy security, ecosystem services, climate change, and species invasions. The Botanical Information and Ecology Network (BIEN) database comprises an unprecedented wealth of cleaned and standardised botanical data, containing roughly 81 million occurrence records from c. 375,000 species, c. 915,000 trait observations across 28 traits from c. 93,000 species, and co‐occurrence records from 110,000 ecological plots globally, as well as 100,000 range maps and 100 replicated phylogenies (each containing 81,274 species) for New World species. Here, we describe an r package that provides easy access to these data. The bien r package allows users to access the multiple types of data in the BIEN database. Functions in this package query the BIEN database by turning user inputs into optimised PostgreSQL functions. Function names follow a convention designed to make it easy to understand what each function does. We have also developed a protocol for providing customised citations and herbarium acknowledgements for data downloaded through the bien r package. The development of the BIEN database represents a significant achievement in biological data integration, cleaning and standardization. Likewise, the bien r package represents an important tool for open science that makes the BIEN database freely and easily accessible to everyone.

Recent publications have highlighted the benefits to policing of an integrated intelligence environment, and the current move in both British policing and beyond is towards a level of information gathering and analysis that is focused at the local area command level. Local intelligence gathering is seen as both effective and economical, though much of the literature concerning the integration of local intelligence concentrates on the use of surveillance, informant handling and the development of intelligence databases. These documents concentrate on the gaining of information about criminal activity that is not known to the police and little is said about maximising the analysis of information already in the possession of the police. Digitalisation of both recorded crime records and calls for service provides a wealth of information about local crime activity that is readily retrievable from modern computer systems. The possibilities and potential benefits of mapping and analysing these types of data have been known for some time, though technical and other difficulties have often hindered the implementation of crime mapping systems. This paper acts as an introduction to crime mapping, presents a model of the required inputs and potential outputs of two types of crime mapping systems, and sets a framework for the integration and control of crime mapping in an intelligence environment. The result of a survey of every police force in the UK indicates that although some successes exist, many forces still have technical and human implementation hurdles to overcome.