Database Applications Research Articles

Data-driven methodology to predict the ICU length of stay: A multicentre study of 99,492 admissions in 109 Brazilian units

PurposeThe length of stay (LoS) is one of the most used metrics for resource use in Intensive Care Units (ICU). We propose a structured data-driven methodology to predict the ICU length of stay and the risk of prolonged stay, and its application in a large multicentre Brazilian ICU database. MethodsDemographic data, comorbidities, complications, laboratory data, and primary and secondary diagnosis were prospectively collected and retrospectively analysed by a data-driven methodology, which includes eight different machine learning models and a stacking model. The study setting included 109 mixed-type ICUs from 38 Brazilian hospitals and the external validation was performed by 93 medical-surgical ICUs of 55 hospitals in Brazil. ResultsA cohort of 99,492 adult ICU admissions were included from the 1st of January to the 31st of December 2019. The stacking model combining Random Forests and Linear Regression presented the best results to predict ICU length of stay (RMSE = 3.82; MAE = 2.52; R² = 0.36). The prediction model for the risk of long stay were accurate to early identify prolonged stay patients (Brier Score = 0.04, AUC = 0.87, PPV = 0.83, NPV = 0.95). ConclusionThe data-driven methodology to predict ICU length of stay and the risk of long-stay proved accurate in a large multicentre cohort of general ICU patients. The proposed models are helpful to predict the individual length of stay and to early identify patients with high risk of prolonged stay.

Analysis and information content of quadrupolar NMR in glasses: 25Mg NMR in vitreous MgSiO3 and CaMgSi2O6

The static wideline and high-resolution magic angle spinning (MAS) 25Mg NMR lineshapes measured for isotopically enriched enstatite and diopside glasses indicate a wide distribution of the electric-field gradient (EFG) components at the 25Mg position caused by disorder. The correct characterization of this distribution requires simulations with special attention paid to the experimental parameters. Here, both the static spectra obtained by wideband excitation and the MAS-NMR spectra obtained via rotor-synchronized Hahn spin echo acquisition were successfully simulated with the Czjzek distribution model, using one consistent set of parameters. Average nuclear electric quadrupole coupling constants near 8 MHz and a distribution width around 4 MHz were obtained for both materials, which suggests that earlier results on these glasses need to be re-examined. The results of this study outline a general strategy for characterizing the local environments of strongly coupled quadrupolar nuclei in amorphous and glassy materials. Despite the discrepancies between the interaction parameters extracted from our data and those published in earlier NMR work, the best fit to the data indicate an average isotropic chemical shift near 13 ppm (vs. aqueous MgCl2 solution) for both the enstatite and diopside glasses. Assuming the applicability of the current database relating the 25Mg chemical shifts with coordination numbers in crystalline compounds, this value suggests that the Mg2+ ions are six-coordinated. This conclusion, however, is based on the simplifying assumption that the 25Mg spectrum comprises a Czjzek distribution centered at a single isotropic chemical shift value and stands in contrast to the results of recent isotope-selective neutron diffraction studies which give an average Mg-O coordination number of 4.4–4.5 for both glasses. However, reasonable fits to the MAS-NMR spectra can also be obtained when constraining the average isotropic chemical shift to 50 ppm, a value typical of four-coordinated Mg. We conclude that multiple Mg sites with different coordination numbers may well be present and that, in the present glasses, 25Mg NMR at typically used spinning rates and magnetic field strengths (20 kHz, 14.1 T) is not capable of resolving them due to excessive broadening by quadrupolar interactions.

Implementation of BIM-based model checking technology for managing maintenance planning in green building ecosystem

PurposeThe green building (GB) maintenance industry has been under increasing pressure by designers to demonstrate its evaluation and information management of building information modelling based model checking (BMC) to the competency's performance and design knowledge of building control instrument. This main problem has been termed as maintenance planning level. Although maintenance planning has been explored in GB maintenance environments, less is known about what maintenance planning problems currently exist and what their causes are, such as the recent fire in the Grenfell Tower (14 June 2017, about 80 fatalities) in North Kensington, West London. The aim of this paper is to identify how GB maintenance environments could integrate BMC within their processes. The purpose of this study is to assess the BMC technology management of GB maintenance ecosystem and that of a soft skills level to establish the impact of innovation policy features on database and safety risk function mechanism.Design/methodology/approachTo achieve this aim, a comprehensive literature review of the existing conceptualisation of BMC practices is reviewed and the main features of Information and Communication Technology tools and techniques currently being employed on such GB maintenance ecosystem is carried out to evaluate the strengths and weaknesses of the previous studies. The conceptual framework explores the importance of integration of BMC in the construction phase to identify alternative methods in the automation system (AS) process to co-generate, monitor and optimise BMC.FindingsThe results confirm that BMC tool positively influences database application and risk mechanism of construction project safety while agreeableness negatively does. Besides, database application has a negative influence on innovation policy of company towards BMC implementation. Propositions derived not only shed light on guidance for future research on the soft skills of construction organisations, but also provide decision-making support through a better understanding of the factors affecting soft skills level amongst biggest construction companies.Originality/valueThus far, this study advances the knowledge about how GB maintenance environments can ensure BMC delivery. This paper highlights the need for further research to integrate BMC in GB maintenance environments validates the framework across the construction phase with different GB project managers and engineers.

IsoBugView

Database applications frequently use weaker isolation levels, such as Read Committed, for better performance, which may lead to bugs that do not happen under Serializable. Although a number of works have proposed methods to identify such isolation-related bugs, the difficulty of analyzing reported bugs is often underestimated, since these bugs often involve multiple complicated transactions interleaved in a specific order and they often require users' feedback to improve the accuracy of bug analysis. This paper presents IsoBugView, a tool to visualize isolation bugs and incorporate users' feedback: to address the challenge that a complicated bug may include much information and thus is hard to present, IsoBugView displays a high-level overview of the bug first and displays further information of individual pieces if the developer needs further investigation. To incorporate users' feedback, IsoBugView embeds hook functions into the backend analysis tool to preprocess a dependency graph and postprocess a found cycle and further allows a user to apply predefined hook functions in its graphic user interface. Our experience shows that IsoBugView has greatly improved our productivity of analyzing isolation bugs.

SMARTBELL SEBAGAI APLIKASI IoT PADA SISTEM KEAMANAN RUMAH

In this paper, a smart bell system is designed and realized. The system uses a passive-infrared sensor to detect motion and activate the system to logged detection time to database, sent notification, and commanda webcam to take pictures and record video. An Arduino microcontroller is used to process datathat will be presented on web pages which are then converted into Progressive Web Applications. Node.js is used as the platform to creare a server, and MongoDB is employed as database for time detection. For communication system protocol between the database and web application pages the REST-API method isused. During the detection process, the system will send a notification using webpush with the Firebase Cloud Messanging framework. The system was tested to detect, record videos, create GIFs, write to databases, and send notifications into web applications. The experiments shows a success of 81.25% for displaying videosand of 93.75% for displaying GIFs.

A Qualitative Study of Data Management Development for Hybrid Organisation Application

A revolution of information technology through big data for data processing is greatly affecting organisations around the globe, specifically the education providers. Subsequently, there are increasing needs and demands for software, digitalisation, and processing power development for unlimited database development and applications. The study aims to determine how well-prepared UTMSPACE is in meeting the new data management planning requirement for developing the big data management application. This study is supplementary to the development of strategic management planning in digitalisation and data management. The study employs qualitative method for its exploratory and data processing application research. The findings will help to identify the weaknesses and strengths in preparing data management applications to achieve strategic management plan outcomes. The study suggests that the company must increase awareness on the importance of big-data management through data processing engines that provide a more organised and centralised data and information management. In addition, the results also share the type of data and information needed for prioritising the organisational strategies in implementing the lifelong learning programmes across different environments and sectors.

Evaluasi Kinerja Website Pelayanan Publik Pemerintah Daerah Pada Provinsi Kalimantan Timur

This research aims to evaluate the performance of websites managed by the regional government of East Kalimantan province and also to provide input on improving the performance of websites that are considered less good. There are 9 public service websites managed by the Government of East Kalimantan including the website of the flying pesut, SIPPD, website, si website, tepra website, foreign service travel website, cooperation database application website, grant website and bansos online, regional financial transparency website, performance report website. In this research the method used is an evaluation research method that is carried out by collecting data so that it can be compared with existing standards and will then be drawn conclusions. The data collection is done by observing and reviewinglibraries, and analyzing databy using web.dev to measure performance levels, accessibility, best practices and SEO. The results of this study showed that the performance of the website had a good assessment with the average overall website assessment of 73%. With the regular evaluation and improvements and improvements to public service websites owned by the East Kalimantan provincial government, more people are expected to be able to do so. You can use public service websites to get the information you need. The government needs to hold trainings to website managers so that they can support website management in order to be better and more qualified.

QoS-Aware Cost Minimization Strategy for AMI Applications in Smart Grid Using Cloud Computing.

Cloud computing coupled with Internet of Things technology provides a wide range of cloud services such as memory, storage, computational processing, network bandwidth, and database application to the end users on demand over the Internet. More specifically, cloud computing provides efficient services such as “pay as per usage”. However, Utility providers in Smart Grid are facing challenges in the design and implementation of such architecture in order to minimize the cost of underlying hardware, software, and network services. In Smart Grid, smart meters generate a large volume of different traffics, due to which efficient utilization of available resources such as buffer, storage, limited processing, and bandwidth is required in a cost-effective manner in the underlying network infrastructure. In such context, this article introduces a QoS-aware Hybrid Queue Scheduling (HQS) model that can be seen over the IoT-based network integrated with cloud environment for different advanced metering infrastructure (AMI) application traffic, which have different QoS levels in the Smart Grid network. The proposed optimization model supports, classifies, and prioritizes the AMI application traffic. The main objective is to reduce the cost of buffer, processing power, and network bandwidth utilized by AMI applications in the cloud environment. For this, we developed a simulation model in the CloudSim simulator that uses a simple mathematical model in order to achieve the objective function. During the simulations, the effects of various numbers of cloudlets on the cost of virtual machine resources such as RAM, CPU processing, and available bandwidth have been investigated in cloud computing. The obtained simulation results exhibited that our proposed model successfully competes with the previous schemes in terms of minimizing the processing, memory, and bandwidth cost by a significant margin. Moreover, the simulation results confirmed that the proposed optimization model behaves as expected and is realistic for AMI application traffic in the Smart Grid network using cloud computing.

Cluster Computing

A computer cluster is a collection of loosely linked computers that operate together so closely that they appear to be one computer in many ways. Clusters are frequently connected via fast local area networks. Clusters are frequently used to increase the performance and/or dependability of a single computer while also being significantly less expensive than single machines of equivalent speed and reliability. Cluster computing arose from the convergence of numerous developments, including the affordable availability of high- performance microprocessors and high-speed networks, as well as the creation of standard software tools for high-performance distributed calculate. Clusters have grown to accommodate a wide range of applications, including ecommerce and high-performance database applications. The fundamental goal of a cluster computer is to perform a task in a shorter amount of time by employing processing node groups. This is accomplished by moving loads from busy to idle nodes. Transferring excess loads from active nodes to idle nodes is one approach for achieving this goal.

Remote Sensing of Surface and Subsurface Soil Organic Carbon in Tidal Wetlands: A Review and Ideas for Future Research

Tidal wetlands, widely considered the most extensive reservoir of soil organic carbon (SOC), can benefit from remote sensing studies enabling spatiotemporal estimation and mapping of SOC stock. We found that a majority of the remote-sensing-based SOC mapping efforts have been focused on upland ecosystems, not on tidal wetlands. We present a comprehensive review detailing the types of remote sensing models and methods used, standard input variables, results, and limitations for the handful of studies on tidal wetland SOC. Based on that synthesis, we pose several unexplored research questions and methods that are critical for moving tidal wetland SOC science forward. Among these, the applicability of machine learning and deep learning models for predicting surface SOC and the modeling requirements for SOC in subsurface soils (soils without a remote sensing signal, i.e., a soil depth greater than 5 cm) are the most important. We did not find any remote sensing study aimed at modeling subsurface SOC in tidal wetlands. Since tidal wetlands store a significant amount of SOC at greater depths, we hypothesized that surface SOC could be an important covariable along with other biophysical and climate variables for predicting subsurface SOC. Preliminary results using field data from tidal wetlands in the southeastern United States and machine learning model output from mangrove ecosystems in India revealed a strong nonlinear but significant relationship (r2 = 0.68 and 0.20, respectively, p < 2.2 × 10−16 for both) between surface and subsurface SOC at different depths. We investigated the applicability of the Soil Survey Geographic Database (SSURGO) for tidal wetlands by comparing the data with SOC data from the Smithsonian’s Coastal Blue Carbon Network collected during the same decade and found that the SSURGO data consistently over-reported SOC stock in tidal wetlands. We concluded that a novel machine learning framework that utilizes remote sensing data and derived products, the standard covariables reported in the limited literature, and more importantly, other new and potentially informative covariables specific to tidal wetlands such as tidal inundation frequency and height, vegetation species, and soil algal biomass could improve remote-sensing-based tidal wetland SOC studies.

A Study of Modern Trends in Database and Data Repository Technologies as the Technological and Architectural Basis for the Creation of Software and Intelligent Systems by Means of Modern Programming Languages. Part 2

The article contains an analytical review of developments in database technologies, made on the basis of reports prepared by the results of eight meetings of database specialists held throughout 1988–2013. Objects of the analysis are most interesting predictions given in the reports: their realism, accuracy, pragmatism or, vice versa, utopianism or opportunism. 
 The article consists of two parts.
 Part 1 is devoted to analysis and evaluation of predictions made in the reports of the four earlier meetings held in 1988, 1990, 1995, and 1996. These predictions are about creation, development and uses of decision support systems, database appliances, graphic processing units, operating systems, interface for structured query language, database applications, information distribution, universal database management systems, query optimization criteria, intellectual analysis of database within database management systems. A detailed description of research themes in the field of databases, which got the priority status in that time, is given: recording and computation of data, security and confidentiality of data, replication and harmonization of data, structuring of data, intellectual analysis of data, data warehouses. 
 Part 2 is devoted to an analytical review of the predictions contained in the reports on the meetings held in 1998, 2003, 2008, and 2013. The predictions are about self-adjustment of database systems, rethinking of the traditional database architecture as a result of new hardware capabilities. They make special emphasis on the feasibility of manipulations with structured and unstructured data within DSS architecture, support of Big Data technology, with outlining the themes of research aimed at implementation of its potential.

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.

Ultra-high performance liquid chromatography-orbitrap high-resolution mass spectrometry for rapid screening and identification of 32 illegally added drugs in slimming and anti-impotence health foods

建立了基于超高效液相色谱-Orbitrap高分辨质谱的快速筛查及确证减肥和壮阳类保健食品中32种非法添加药物的分析方法,并总结了数据库建立和应用的相关要点。研究对象聚焦于非法添加药物的衍生物,在对比正负离子模式下各化合物响应强度的基础上建立了高分辨质谱信息库,对提取溶剂、色谱柱温度等实验条件进行了详细探究,尽可能给出了较宽的标准曲线线性范围。使用Hypersil gold vanquish色谱柱(100 mm×2.1 mm, 1.9 μm),梯度洗脱,流量0.3 mL/min,正、负离子全扫描/数据依赖的二级扫描模式,在17 min内完成32种目标化合物的数据采集,通过TraceFinder软件进行快速定性筛查和定量。结果显示在17 min内32种化合物能得到较好分离;2种基质加标溶液中32种化合物的一级质谱离子精确质量数的实测值与理论值均在5×10-6误差之内,二级碎片离子质量数的实测值与理论值均在1×10-5误差之内;方法学验证结果表明,所有化合物均显示出优异的线性关系,相关系数(r2)均大于0.99;固体基质中除达泊西汀、羟基硫代豪莫西地那非、硫代豪莫西地那非、硫代西地那非、去甲基硫代西地那非的回收率较低外,其余27种化合物的回收率为50.5%~84.5%,相对标准偏差(RSD)为1.2%~13%,液体基质中32种化合物的回收率范围为60.4%~109.3%, RSD为0.77%~8.2%;在48份减肥及壮阳类保健食品中检出1份阳性样品,检出率2.08%。该方法操作简单,结果定性准确,可用于减肥及壮阳类保健食品中32种非法添加药物的快速筛查及确证。

A design in system architecture based on mobile cloud computing for a virtual try-on solution

Cloud computing is an emerging technology in this digital century. It provides an excellent but low-cost source for database storage, computing power, applications, and services through an internet-delivered cloud platform. Thanks to the cost savings in investing and maintaining physical data centers, as well as the stability of Quality of Service (QoS), it has no restrictions on company size or sector for enterprises to shift their operations to a cloud platform. The fashion industry, particularly the fashion e-commerce sector, is a case study in leveraging the cloud platform via a technology called “Virtual try-on” (VTO). VTO solution allows fashion brands to increase the shopping experience, however, requires installing and maintaining a bulky system for implementation. There are different methods and approaches to design architectures using cloud computing, however, there have not been many studies addressing tasks related to machine learning that uses the high Graphics Processing Unit (GPU) encountered in VTO solutions. To design a scheduler that could optimize the system performance while lowering operational expenses in VTO solutions, this research proposes a system to (1) handle synchronous model and asynchronous model separately and clearly, (2) perform multi-layered task processing architecture by hashing task ID and implementing a queue management system. This method would satisfy three major requirements: (1) Avoid complex hardware requirements for users, (2) Ensure the system stability and the ease of horizontal and vertical extension, and (3) Protect user information privacy.

Modern challenges of property market analysis- homogeneous areas determination

Effective comprehension of highly complex and spatially heterogenous property market requires its’ appropriate recognition. One of the most critical steps in property analyses and valuation procedures is the identification of the sub-markets as the fundamental comparable units. The biggest challenge in this case is to define the criteria of the basis indicating the similarity (homogeneity) of property markets area. The objective of the study was to propose methodology (called “HO-MAR”) that enables objective identification of the homogenous (similar/comparable) areas (zones) that could indicate location of similar groups of property transactions (representative properties) used either in individual valuations or AVMs. The authors propose utilization of automated solutions based on robust geo-estimation that enables high efficacy of property submarkets identification. Robust geo-estimation is guaranteed by merging semi-automated data mining methods (e.g. entropy theory, rough set theory, fuzzy logic) and geoprocessing activities (Gauss filter, geocoding and reverse geocoding, tessellation model with mutual spatial overlapping) concerning spatial relation database application.

IOT IMPLEMENTATION FOR CALCULATING POWER CONSUMPTION BASED ON ANDROID

Electrical power consumption monitoring, mainly at business properties in urban areas that have one line power supply distribution at many area rent, had the problem of the bill electric consumption on the tenant. The places like dormitories, food court, futsal field, pets day care etc. had problems, where the node had more electrical consumption operationally, so we implemented IoT monitoring and control at electrical device and electrical consumption report. The method to implement this system is using IoT protocol communication and firebase cloud data as a third party database application that is accessed by an android mobile phone. The systems of our research is infrastructure IoT mobile communication that can be controlled and adjusted by firebase cloud and can activate the device by MCU microcontroller ESP wifi that Based to monitor and record activity that had controlled by mobile phone. All data activity has to be processed and saved to the firebase data cloud, so the system depends on internet communication and an active firebase server. So the result of our research is to report activity and bill of electrical consumption every node that had rented.

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

A living tool for the continued exploration of microplastic toxicity

Throughout the past decade, many studies have reported adverse effects in biota following microplastic exposure. Yet, the field is still emerging as the current understanding of microplastic toxicity is limited. At the same time, recent legislative mandates have required environmental regulators to devise strategies to mitigate microplastic pollution and develop health-based thresholds for the protection of human and ecosystem health. The current publication rate also presents a unique challenge as scientists, environmental managers, and other communities may find it difficult to keep up with microplastic research as it rapidly evolves. At present, there is no tool that compiles and synthesizes the data from these studies to allow for visualization, interpretation, or analysis. Here, we present the Toxicity of Microplastics Explorer (ToMEx), an open access database and open source accompanying R Shiny web application that enables users to upload, search, visualize, and analyze microplastic toxicity data. Though ToMEx was originally created to facilitate the development of health-based thresholds to support California legislations, maintaining the database by the greater scientific community will be invaluable to furthering research and informing policies globally. The database and web applications may be accessed at https://microplastics.sccwrp.org/.Graphical

VenomMaps: Updated species distribution maps and models for New World pitvipers (Viperidae: Crotalinae)

Beyond providing critical information to biologists, species distributions are useful for naturalists, curious citizens, and applied disciplines including conservation planning and medical intervention. Venomous snakes are one group that highlight the importance of having accurate information given their cosmopolitan distribution and medical significance. Envenomation by snakebite is considered a neglected tropical disease by the World Health Organization and venomous snake distributions are used to assess vulnerability to snakebite based on species occurrence and antivenom/healthcare accessibility. However, recent studies highlighted the need for updated fine-scale distributions of venomous snakes. Pitvipers (Viperidae: Crotalinae) are responsible for >98% of snakebites in the New World. Therefore, to begin to address the need for updated fine-scale distributions, we created VenomMaps, a database and web application containing updated distribution maps and species distribution models for all species of New World pitvipers. With these distributions, biologists can better understand the biogeography and conservation status of this group, researchers can better assess vulnerability to snakebite, and medical professionals can easily discern species found in their area.

Information soil database of Republic of Khakassia

Relevance. Currently, a number of soil information systems of various levels and directions have been created, the studies on the creation and application of soil databases are represented insufficiently in the Republic of Khakassia today.Methods. Were carried out by common methods: at-ground soil and geobotanical studies, cartographic method, physical and agrophysical, agrochemical methods of soil researches. For the database creation the Microsoft Access software package was used, which systematized and unified a large amount of experimental data.Results. Based on the long-term soil research, the database “Agricultural Soils of the foothills of the Western Sayan of Khakassia” with a wide range of soil characteristics for various purposes and uses was formed and registered. The database contains attribute information about the current state of arable and postagrogenic soils in the foothills of the Western Sayan of the Republic of Khakassia. The set of independent materials is presented in the form of tables, queries, forms, reports and catalogues of text files (.docx), photos (.jpeg), which contain information about soil forming factors, soil classification and distribution by natural and climatic zones on the research territory. Currently, the database includes a description of 17 representative soil profiles with an optimal set of indicators, a detailed description of each pedologic horizon, an accurate geographical reference and a digital photography of each reference soil profile. It contains the taxonomic attribute of the dominant and codominant soils in various classification systems (SC RF; WRB, 2006; FAO, 1988). The main information object is the type (subtype) of soil, which includes systematized factors of soil criteria (a list of 18 sets): morphological description of the soil profile, indicators of pedological property, chemical, physico-chemical, agrophysical, hydrophysical and other indicators. The contemporary database with a variety of pedologic properties will serve as a basis for the rational use and protection of soils. Geographical coordinates of soil profiles in the database will allow to display them on the maps of Russia and to put them in the Unified state register of soil resources of Russia.