System for Identifying Pests and Diseases in Soybean Crop through Natural Language Processing

The presence of technologies in the agronomic field has the purpose of proposing the best solutions to the challenges found in agriculture, especially to the problems that affect cultivars. One of the obstacles found is to apply the use of your own language in applications that interact with the user in Brazilian Agribusiness. Therefore, this work uses Natural Language Processing techniques for the development of an automatic and effective computer system to interact with the user and assist in the identification of pests and diseases in soybean crop, stored in a non-relational database repository to provide accurate diagnostics to simplify the work of the farmer and the agricultural stakeholders who deal with a lot of information. In order to build dialogues and provide rich consultations, from agriculture manuals, a data structure with 108 pests and diseases with their information on the soybean cultivar and through the spaCy tool, it was possible to pre-process the texts, recognize the entities and support the requirements for the development of the conversacional system.

SOSIALISASI e-ARSIP SEBAGAI PENGOLAHAN DATA DINAS LUAR PADA KANTOR KESEHATAN PELABUHAN PEKANBARU

Kantor Kesehatan Pelabuhan (KKP) Pekanbaru merupakan Kantor pemerintahan yang bergerak di bidang kesehatan khususnya mengenai lingkungan. Dalam kegiatan dinas luar seperti surveilans kesehatan kapal, surveilans kesehatan masyarakat, bimbingan teknis, pengawasan dokumen kesehatan, surveilans faktor penyakit tidak menular pada kantor cabang kesehatan pelabuhan di provinsi riau seperti Kantor Selat Panjang, Kantor Tanjung Buton, Kantor Siak Sri Indrapura, Kantor Buatan, Kantor Sei. Duku, Kantor Kampung Dalam, kantor KKP Bangkinang dan Kantor Kuantan Singingi. Adapun pengolahan data masih belum teritegrasi dengan baik sehingga susah dalam melakukan pendataan dokumen dan informasi dari hasil kegiatan dinas luar, sementara pengadaan komputer dan sumber daya ada. Dan kegiatan ini selalu dilakukan tiap kegiatan sehingga diperlukan sebuah sistem yang dapat mengontrol data-data kegiatan dan dokumen yang dibutuhkan dalam pembuatan laporan kegiatan. Hal inilah yang menjadi ketertarikan penulis untuk membantu permasalahan yang dihadapi karyawan di Kantor Kesehatan Pelabuhan Pekanbaru supaya lebih efisien dalam menjalankan kegiatan. Relational Database management System (RDBMS) adalah kumpulan data yang disimpan secara sistematis di dalam komputer yang dapat diolah atau dimanipulasi menggunakan perangkat lunak (program aplikasi) untuk menghasilkan informasi. Dengan memanfaatkan teknologi informasi RDBMS sehingga aplikasi berbasis online dapat diakses kapan dan dimana saja dari tempat karyawan melakukan kegiatan dinas luar dapat langsung meng-input dan pengolahan data untuk penyajian informasi yang lebih cepat ke kantor pusat pelabuhan pekanbaru dan dengan pendekatan metode System development Life Cycle (SDLC) dalam penyelesaian masalah kegiatan dinas luar, sehingga diharapkan pengolahan data dapat terintegrasi dan lebih efisien dalam pendataan informasi, dengan demikian diharapkan dapat membantu pihak kantor dalam pengolahan data yang lebih efisien dan lebih aman khususnya dalam pengolahan data dinas luar pada kantor kesehatan pelabuhan pekanbaru

Relational Database for Horizontal-to-Vertical Spectral Ratios

Frequency-dependent horizontal-to-vertical spectral ratios (HVSRs) of Fourier amplitudes from three-component recordings can provide useful information for site response modeling. However, such information is not incorporated into most ground-motion models, including those from Next-Generation Attenuation projects, which instead use the time-averaged shear-wave velocity (VS) in the upper 30 m of the site and sediment depth terms. To facilitate utilization of HVSR, we developed a publicly accessible relational database. This database is adapted from a similar repository for VS data and provides microtremor-based HVSR data (mHVSR) and supporting metadata, but not parameters derived from the data. Users can interact with the data directly within a web portal that contains a graphical user interface (GUI) or through external tools that perform cloud-based computations. Within the database GUI, the median horizontal-component mHVSR can be plotted against frequency, with the mean and mean ± one standard deviation (representing variability across time windows) provided. Using external interactive tools (provided as a Jupyter Notebook and an R script), users can replot mHVSR (as in the database) or create polar plots. These tools can also derive parameters of potential interest for modeling purposes, including a binary variable indicating whether an mHVSR plot contains peaks, as well as the fitted properties of those peaks (frequencies, amplitudes, and widths). Metadata are also accessible, which includes site location, details about the instruments used to make the measurements, and data processing information related to windowing, antitrigger routines, and filtering.

Storage organization for "open" sets of entity attributes in relational databases

Relations are practically implemented by database management systems in the form of two-dimensional tables. In this regard, certain difficulties arise in the development of relational database schemas, in which it is necessary to represent objects with an alterable (open) set of attributes. The article proposes a solution to this problem by including special relations in the scheme - relations of properties directory. Properties directory allow replenishing the sets of object attributes without changing the structure of the database. Examples of the practical use of properties directory in the development of database schemas of two information systems are presented.

Relational database used for ground-motion model development in the NGA-sub project

The Next-Generation Attenuation for subduction zone regions project (NGA-Sub) has developed data resources and ground motion models for global subduction zone regions. Here we describe the NGA-Sub database. To optimize the efficiency of data storage, access, and updating, data resources for the NGA-Sub project are organized into a relational database consisting of 20 tables containing data, metadata, and computed quantities (e.g. intensity measures, distances). A database schema relates fields in tables to each other through a series of primary and foreign keys. Model developers and other users mostly interact with the data through a flatfile generated as a time-stamped output of the database. We describe the structure of the relational database, the ground motions compiled for the project, and the means by which the data can be accessed. The database contains 71,340 three-component records from 1880 earthquakes from seven global subduction zone regions: Alaska, Central America and Mexico, Cascadia, Japan, New Zealand, South America, and Taiwan. These data were processed on a component-specific basis to minimize noise effects in the data and remove baseline drifts. Provided ground motion intensity measures include peak acceleration, peak velocity, and 5%-damped pseudo-spectral accelerations for a range of oscillator periods.

Empowering Natural Language Interfaces to Databases with Aggregations

A Natural Language Interface to Database (NLIDB) refers to a database interface that translates a question asked in natural language into a structured query. Aggregation questions express aggregation functions, such as count, sum, average, minimum and maximum, and optionally a group by clause and a having clause. NLIDBs deliver good results for standard questions but usually do not deal with aggregation questions. The main contribution of this article is a generic module, called GLAMORISE (GeneraL Aggregation MOdule using a RelatIonal databaSE), that extends NLIDBs to cope with aggregation questions. GLAMORISE covers aggregations with ambiguities, timescale differences, aggregations in multiple attributes, the use of superlative adjectives, basic recognition of measurement units, and aggregations in attributes with compound names.

LRW-CRDB: Lossless Robust Watermarking Scheme for Categorical Relational Databases

In 2002, Agrawal and Kiernan defined six basic requirements, including preventing illegal watermark embedding and authentication, reversibility, robustness, and others, which must be satisfied when a reversible watermark is designed for relational databases. To meet these requirements, in this paper, a lossless watermarking scheme for a categorical relational database called LRW-CRDB (lossless robust watermarking for categorical relational databases) is proposed. In our LRW-CRDB scheme, the database owner needs to generate two secret embedding keys, K1 and K2, in advance. Then, two reference sets are generated based on two different secret embedding keys and a symmetry-based data hiding strategy, and then these are used for the watermark embedding phases. Experimental results confirmed that our LRW-CRDB scheme successfully detects 100% of hidden watermarks, even when more than 95% of the watermarked relational database has been deleted. In other words, the robustness of our proposed LRW-CRDB scheme outperforms other existing schemes under a variety of possible attacks, such as alteration, sorting, deletion, and mix-match attacks.