The HITRAN2016 molecular spectroscopic database

One of the most important considerations when selecting a database is how relational (SQL) and non-relational (NoSQL) data structures will interact. While all options are viable, consumers should take certain distinctions into account before choosing. Since SQL databases are vertically scalable, you can typically scale server components like CPU, RAM, or SSD. NoSQL databases, on the other hand, support horizontal scaling. As a result, you can increase the capacity of your NoSQL database by fragmenting (data partitioning), or by adding extra servers. Why, then, is it still challenging to choose the instance that is most appropriate for a given application and requires the least amount of runtime? Because data that will be conveyed via the internet uses a cloud in computer networks as a metaphor. To determine which model to utilize, it is required to conduct a comparison study of SQL-oriented database engines. SQL has a form created for another side of non-productive data and is offered in the form of ordered data, but NoSQL databases are horizontally expandable. Workload management solutions are therefore also in charge of automating organizational procedures, i.e., they carry out activities without requiring manual employee attendance. For businesses trying to implement continuous delivery methods and enhance the effectiveness of customer service delivery, they are unavoidable.

Chapter 1 - SQL Is Declarative, Not Procedural

Chapter 9 - Software engineering

The HITRAN molecular spectroscopic database: edition of 2000 including updates through 2001

Session chairs

Working with transportation networks can be tedious and confusing. Most transportation modeling packages available treat components of a transportation network independently and require coding complete networks for all alternatives. This approach has several weaknesses: it is time consuming, requires duplicate information to be stored for each alternative, and misrepresents the interactive nature of the many network attributes. A relational data base structure in conjunction with effective network management software can be used to capture the interrelationship of network characteristics, facilitate network updates, and maintain all the network scenarios in one data file. The approach, benefits, and implementation of such a system are described.

In fact, terms are a word or phrase that is the name of a concept used in science, technology, art and other areas of human activity. If the deep meanings of these terms in these areas are systematically formed and clearly marked, then only then is it considered that their goal has been achieved. The development of the terminological system undoubtedly contributes to its sustainable application in the study of a particular field, allows us to draw new conclusions. In modern science, there are significant advances in the formation of terms. Some of them have been used in everyday life for a long time, however, there are terms that need to be revised in the scope of their use. Recently, a number of scientific terms in the Kazakh language have been replenished even more. However, there is a lot of work to be done in this area. To date, it is necessary to specifically formulate terms that will more deeply reveal the meaning of scientific concepts in the Kazakh language and in themselves will be pleasant to the ear, well perceived by the majority. It is no secret that when working in this direction, questions may arise regarding the interpretation of the meanings of certain terms. In this regard, the article raises the problem of only some of those terms that are approved for use in the Kazakh language, since it is impossible to consider the entire system of terms and explain their meaning in more detail and describe them in one publication. In particular, the article describes the shortcomings in the translation of the term "archived format – RAR, ZIP", related to the field of computer science and computer technology, and several terms related to the field of record keeping and archival affairs. The main purpose of the publication is that when approving terms in the Kazakh language, it is necessary to take into account the linguistic features of both languages and pay special attention to them in further work on improving the terms.

The impact of various HITRAN molecular spectroscopic databases on infrared radiative transfer simulation

In order to enhance the semantic representation of data collected in forest inventories the paper proposes a reengineering technique consisting of Entity-Relationship modelling and a transformation process into relational database structures. The work is motivated by the fact that a huge amount of information about our most complex ecosystem on earth, the forest, is available but unfortunately currently only interpretable by the forest experts. This is due to the current structure of the data and in our opinion this is a huge disadvantage because data collected may also be of tremendous value in related disciplines, for example, for solving ecological questions. Enhancing the semantics and providing a more convenient user interface for accessing the data may make the information available in a much easier way to the ecologist, the botanist, the wildlife expert, and to all other parties that might be interested in using the inventory.

Issues concerning effective retrieval of pertinent data have been tackled by developing an intelligence-based system interfacing with a relational database structure. The artificial neural network dynamically modifies the variables based on the "Relative Strength of Effect", a model parameter which can be computed from the field data. A prototype has been established for the prediction of sediment characteristics within a harbour having low tidal range.

the massive volume of data in databases, web pages, and document files usually causes information to be disorganized and unclear for the user. Therefore, information in such an environment can be classified into three forms: structured, semistructured, or unstructured. Structured information is the best form of information because it facilitates the acquisition and comprehension of knowledge. Relational Database Management System (RDBMS) has a robust structure that manages, organizes and retrieves data. There are many attempts have been made in order to deal with such data. These attempts can be categorized into three groups: within a database schema, by a developed data model within the database, or by query-based techniques in database. Nonetheless, RDBMS contain massive amount of unstructured data such as textual data.. This paper proposed Textual Virtual Schema Model (TVSM). TVSM is conducted to perform semantic textual data linking and clustering and is embedded in the relational database structure (schema). In addition, linking and converting the unstructured information to structured data. Quality improvement of textual data clusters. Achievement of high query processing efficiency in retrieving data clusters. TVSM initially developed to assist researchers, developers, and database administrators who are concerned on unstructured information management, information extraction, multi-document clustering, information retrieval, query processing efficiency, personal information management, question answering, information integration, news tracking, and news summarization

PARIS (personal archiving and retrieving image system) is an experiment personal photograph library, which includes more than 80,000 of consumer photographs accumulated within a duration of approximately five years, metadata based on our proposed MPEG-7 annotation architecture, dozen dimensional digital content (DDDC), and a relational database structure. The DDDC architecture is specially designed for facilitating the managing, browsing and retrieving of personal digital photograph collections. In annotating process, we also utilize a proposed spatial and temporal ontology (STO) designed based on the general characteristic of personal photograph collections. This paper explains PRAIS system

The paper describes the design of a simulator capable of investigating a number of ATM flow-control algorithms. The event driven simulator contains a minimum number of component types-queues, connections and routes. The first two are the only participants generating events. The major data elements are packets which logically can contain any number of cells but the simulator provides for packet transport which is statistically similar to that occurring in individual cell transport through a network. The simulator code is written in C++. Two of its mechanisms, overloaded data structures and dynamic assignment of code using pointers to functions allow the simulator to contain any number of flow control algorithms and to select the algorithm to be used. Because of the unique character of the basic simulator components, relational database structures are used for case input and run output. Run output post processing is necessary because network flow-control problems are usually related to particular components when selecting the flow control algorithm and/or parameters to best meet a system's needs. Simulator run time is excellent, with a 7 queue, 5 connection network taking 2-3 second clock time for a 0.5 second run time. Scaling to a component count by an order of magnitude should be very feasible. To demonstrate the simulator's versatility, we provide a comparison of three very different flow control schemes. The first uses fair-share assignment for individual connections at each queue. The second, a threshold queue algorithm does not control individual connections, only the bulk queue load. The third scheme is an adaptive rate-based algorithm. It uses no control at the queue-only measure transport delay at the receiver.

Data management is part of information resource management which includes all activities that ensure that company data resources are accurate, up-to-date, and safe from tampering, and are also available to users and the company. This study aims to find out about the role of concept database management in managing large volumes of company data. The result showed that data management activities include data collection, integrity, and testing, storage, maintenance, security, organization, retrieval. Meanwhile, the database structure includes hierarchical database structure, network database structure, and relational database structure.

Quality inspection and defect management in industrial building construction is one of the major factors that general contractors have to consider for improving customer satisfaction and gain competitive advantage. This paper describes a web-based system for quality inspection and defect management (SIDEM). The system is derived from the elements of ISO 9001 standard, and assist management in tracking of inspection/test results, defects management, non-conformities analysis, preventive and corrective measures, etc. A Quality Inspection database and a relational database structure were devised to effectively interconnect the essential information such as facility, trades, trade contractors, materials, and defect types required for a computerized quality inspection and defect management for industrial building construction. In SIDEM, all collected and analyzed information is stored into the database of the central server system allowing general contractors to effectively monitor and statistically analyze the statuses and results of the quality inspection and defect management in real time.