Database Module Research Articles

Intelligent cloud manufacturing platform for efficient resource sharing in smart manufacturing networks

Modern manufacturing demands are characterized by high fluctuations with negative impact on resource efficiency. In this framework, Industry 4.0 key enabling technologies such as cloud manufacturing enable the sharing of distributed resources for effective use at industrial network level. In this work, an intelligent cloud manufacturing platform is proposed to increase resource efficiency in a manufacturing network through dynamic sharing of manufacturing services, including computational, software as well as physical manufacturing resources, that can be offered on demand according to a service-oriented paradigm. The cloud-based platform includes a database module where user input data are collected, an intelligent module for data processing, optimization and feasible solutions generation, and a decision support module for solutions evaluation and comparison. A case study demonstrates technical and economic advantages for industrial resource efficiency improvement.

Identification of key genes and pathways in chronic rhinosinusitis with nasal polyps using bioinformatics analysis.

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a prevalent inflammatory disease of yet unknown etiology. The purpose of this study was to uncover key genes and pathways related to the pathogenesis of CRSwNP via bioinformatics approaches. The gene expression profile of GSE36830 extracted from Gene Expression Omnibus database was used to screen differentially expressed genes (DEGs) between nasal polyp samples and control samples. Furthermore, functional and pathway enrichment analysis was performed using the clusterProfiler package in R language. In addition, protein-protein interaction (PPI) network was constructed by STRING database and functional modules were detected using Molecular Complex Detection algorithm. A total of 538 DEGs (326 up-regulated and 212 down-regulated) were identified. The most significantly enriched pathways for up-regulated and down-regulated genes were hematopoietic cell lineage and salivary secretion, respectively. Moreover, twenty hub genes with high connectivity degrees were selected from the PPI network, such as TYRO protein tyrosine kinase binding protein (TYROBP), G protein subunit gamma 2 (GNG2), CCR7, and CCR3. Besides, six important modules were obtained, which were highly associated with chemokine signaling pathway, Th1 and Th2 cell differentiation, complement and coagulation cascades, cell cycle, systemic lupus erythematosus, and Staphylococcus aureus infection. The results of this study may provide new insights into potential molecular mechanisms of CRSwNP. Nevertheless, further experiments are needed to confirm these findings.

Pattern Search Algorithm for Blackboard-Based Multidisciplinary Design Optimization Frameworks

Preliminary aircraft design necessitates the use of a range of analysis tools, which are often scattered among many departments in an organization and require regular tuning from skilled operators. For this reason, a distributed Multidisciplinary Design Optimisation approach that permits individual organizational domains to use their preferred analysis and optimization tools would be most suitable. This paper revisits a Blackboard framework, which uses simple heuristics to automatically guide organizational design domains to a single optimum by narrowing the bounds on the shared design variables. The authors present a newly developed rule base for this legacy framework, which has been given the title “Multidisciplinary Pattern Search.” Two examples, one of which is for conceptual transonic wing design, demonstrate the merit of the newly developed rule base, database, and visualization modules. They also serve as a means for comparisons with two established Multidisciplinary Design Optimisation architectures. The results indicate that the Blackboard performs better than the distributed Collaborative Optimisation approach, albeit worse than the monolithic simultaneous analysis and design method that tends to be organizationally disruptive to implement.

Study on the country risk rating with distributed crawling system

This paper built a system containing the Distributed Crawling Module, the Database Module and the Analysis Module to collect a large number of objective data, clean the data and realize the business intelligence representation. The distributed crawling system includes the Distributed Crawling Module building from Hadoop, the Database Module by SQL Server and the Analysis Module by the SAS system. The first two modules support a distributed way to collect and convert non-structural data into structural data for the last module processing. Then, this paper extends research fields from theory to application about BR the credit rating of Latvia, Estonia, Slovakia, Turkey, Malaysia, Russia, Thailand and other countries is very high; Afghanistan, Ukraine, Laos, Iran, Arabia, Republic of Syria, Iraq, Burma, Republic of Yemen, East Timor and other countries with poor credit ratings. The conclusion is consistent with the domestic and overseas well-known rating agencies.

Structural features of tundra and taiga soil humic acids according to IR EXPERT analytical system data

The purpose of this work is to identify the most probable structural fragments of the tundra and the taiga soil humic acids on the basis of computer analysis of their IR spectra. Humic acid (HA) samples were isolated from 11 northern soils of the Komi Republic, Russia. IR spectra were registered in KBr by Bruker FTIR spectrometer Vector-22. IR EXPERT information-analytical system was used for analysis of these spectra. This system is a combination of an extensive database (more than 50,000 correlation records of “IR spectrum–structure–structural fragments–accompanying information”) and software modules that allow solving various spectral-structural tasks. The procedure of working with new IR spectra of humic acid involved two stages. Comparison of the sample IR spectrum with all spectra in IR-EXPERT databases was followed by decomposition of the closest spectral analogs into the set of fragments which is individual for each HA. This unique representation makes it possible to associate a spectrum with a combination of structural fragments rather than with the exact structure. That is what we need for HA. The analysis of the obtained ten-vertex fragments shows that all HA samples contain linear, slightly branched, conjugated chains of double C–C bonds, as well as the fragments of aromatic amines and amides. Using only IR spectroscopy data and the IR EXPERT system, we were able to show that humic acids of these northern soils are predominantly aliphatic and contain a large number of oxygen-containing groups, which allows one to predict their high reactivity when interacting with ecotoxicants.

Development of an automated optimizer for sustainable urban landscape design

Abstract Current practice in selecting plants in the field of landscape design is based largely on aesthetic criteria, rather than cost and water consumption needs. This typically results in a design that neither minimizes the Life Cycle Cost (LCC) to the fullest nor optimizes the sustainability of water resources. This paper presents an Automated Optimizer for Sustainable Urban Landscape design (SEOUL) that supports landscape architects in overcoming the drawbacks of current practice. It consists of a database module that includes the list of plants from which the tool makes its selection, as well as an optimization model that uses dynamic programming to optimize the plant selection through minimizing initial cost and water needs. SEOUL is applied on selected case study projects in Egypt to demonstrate the functionality. It was validated by comparing SEOUL's results to those received from current practice through three actual projects. The results obtained shows a 44% and 33% savings in initial cost and water consumption respectively when using SEOUL versus traditional landscape design tools. In addition, the application's ergonomics was evaluated for ease of use, simplicity and efficiency for the end-users.

A Conceptual Framework to Reduce Inpatient Preventable Deaths

BackgroundEfforts to reduce preventable deaths in the in-hospital setting should target both cardiopulmonary arrest (CPA) prevention and optimal resuscitation. This requires consideration of a broad range of clinical issues and processes. A comprehensive, integrated system of care (SOC) that links data collection with a modular education program to reduce preventable deaths has not been defined. MethodsThis study was conducted in two urban university hospitals from 2005 to 2009. The Advanced Resuscitation Training (ART) program was implemented in 2007, incorporating hands-on resuscitative skills and in-hospital–specific training with an institutional resuscitation database. Linkage between the database and training modules occurs via the ART Matrix, which classifies all CPA events into the following etiologies: sepsis, hemorrhage, pulmonary embolus, heart failure, tachyarrhythmias, bradyarrhythmias, acute respiratory distress syndrome, non-intubated pulmonary disease, obstructive apnea, traumatic brain injury, ischemic brain injury, and intracranial mass lesions. This taxonomy was validated using descriptive statistics, before-and-after analysis evaluating CPA incidence, and multivariate logistic regression to predict CPA survival. ResultsA total of 336 inpatients suffered a cardiopulmonary arrest during the study period—187 in the pre-ART period and 149 in the post-ART period. The vast majority of CPA events were categorized using the ART Matrix with high inter-observer reliability. As anticipated, changes in CPA incidence and survival were observed for some Matrix categories but not others following ART implementation. In addition, multivariate logistic regression revealed strong independent associations between taxonomy classifications and outcome. ConclusionA novel SOC using a unique taxonomy for arrest classification appears to be effective at reducing inpatient CPA incidence and outcome.

DEVELOPING GIS-BASED DISASTER MANAGEMENT SYSTEM FOR LOCAL AUTHORITY – CASE STUDY IN MALAYSIA

Abstract. This paper describes the development of geospatial-based disaster management system for an agency at regional level. Important aspects of the system such as spatial data, geospatial database, interface and specific modules for the disaster management system form major discussions of this paper. The Pengerang Disaster Management System (PDMS) is being developed for a local authority in one of the Malaysian states who’s been given a task to monitor the surrounding environmental aspects. The local authority manages one of the largest oil and gas refinery plant in South East Asia region in collaboration with national oil company, PETRONAS. The PDMS, is a one-stop centre (dashboard) for managing the operations with other agencies or stakeholders such as police, marine, army, medical team, fire and rescue units. We anticipate many aspects of disaster management could trigger from this pilot project and thus provide some interesting ideas for a local authority in managing man-made disaster such as fire, other oil and gas related incidents. Some features of the developed system such as online map publishing services, data flow and other geospatial analysis during the event will be discussed in this paper. Near-future work and a big picture of the disaster management approach (with an emphasis to oil and gas incident and scenario) also will be highlighted.

Design of the Enrollment Information System for Foreign Students Under the Background of International Education

With the development of the internationalization of higher education, the education of foreign students has become an important part of higher education in China. How to increase enrollment publicity efforts, design in line with the actual, to show the characteristics of the effective operation of foreign students enrollment information system, to attract more students to study in China, has become an important issue for many universities in china. The article analyzes the actual needs of the parties, and the database and function modules of the enrollment information system are designed in detail. The mutual information exchange and sharing, and the accuracy and efficiency of data transmission are improved.

IEC 61850 Client Redundancy for Substation Automation System

This paper presents an overview of System level redundancy implementation in an IEC61850 based Client application and method used to reduce recovery time after failure of the station level application (IEC 61850 Client, HMI and Database). The authors have presented the implementation of a dual Server hot-standby redundancy architecture, Network Driver (NDIS-Network Driver Interface Specification) for heartbeat communication, network teaming for redundant network redundancy and database replication for substation data integrity and availability of substation data/event. This paper also discusses different redundancy modules (Redundancy Manager, IEC 61850 Client Driver, HMI, Database Module) integration like API integration between Network driver (NDIS) and IEC 61850 Client application. The implementation of data queue in IEC 61850 Client to avoid data loss during server switch over is discussed in this paper. The authors have presented the various fail-over mechanisms in this system. As the redundancy has a direct impact on the cost and complexity of the system, the proposed solution in this paper has addressed the needs of application criticality and customer requirements.

Establishment pharmacological research platform for "Concurrent treatment of the brain and heart" and its application on dissecting mechanism of Danhong injection

The Concurrent treatment of the brain and heart (CTBH) theory is proposed based on traditional Chinese medical theory and clinical practice. In this study, a framework for the pharmacological research platform was established to investigate the principles of concurrent treatment of the brain and heart. The platform for CTBH includes several key techniques for network modeling, discovery of active substances, dissecting mechanism of action and investigation of pharmacokinetic property of TCM. Taking network modeling of CTBH as an example, using database search, literature mining, network construction and module analysis, the that network modules closely associated with the pathological progress of cardiovascular and cerebrovascular diseases were identified, while further functional enrichment analysis of these modules indicated that the key biological processes included oxidative stress, metabolism and inflammation. GSK3B, NOTCH1, CDK4 were identified as key nodes in these network modules. The above-mentioned platform was applied to construct component-biomolecules network of Danhong injection for the identification of common targets and pathways. Among them, GSK3B had the highest correlation with the composition of Danhong injection in the network, and the biological function of whose cluster was related to cell oxidative stress. Based upon results of network analysis, validation experiments suggested that Danhong injection significantly improved the survival rate of oxidative injured myocardial cells and nerve cells, and the protective effect was related to the increase of phosphorylated GSK3β protein expression. Moreover, extracts of Salviae Miltiorrhizae Radix et Rhizoma and Carthami Flos exerted the synergisticcytoprotective effect. The results indicated that the mechanism of treatment of cardiovascular and cerebrovascular diseases of Danhong injection could be studied through network modeling and other methods. In summary, the proposed pharmacological platform provided a feasible way for revealing the mechanism of CTBH by using modern scientific methods.

Embedding a Standard within a Standard using Mobile Progressive Barcodes

Progressive barcodes have been proposed as a mechanism to employ Data Matrix barcodes on a package or label to enhance security services for products in a supply chain by layering additional data into color channels. While the standards-based component of the code remains readable by the same equipment, the extra (color) layer requires additional processing to extract relevant information, communicate with appropriate database modules, etc. This paper examines the problem of extending the scope of applications addressable by this technique to a wider range of designs intended for mobile consumption. This challenge involves developing a scheme that can be naturally used by a greater number of mobile devices, as well as increasing the ease of adoption. The extension of progressive barcodes to the more ubiquitous QR code via embedding a compact Data Matrix code into the design is an approach for improving functionality of print and document workflows. The two barcodes can be used simultaneously for their most familiar purposes. Mobile processing allows us to leverage many more possible object-driven workflow touchpoints.

UMineAR: Mobile-Tablet-Based Abandoned Mine Hazard Site Investigation Support System Using Augmented Reality

Conventional mine site investigation has difficulties in fostering location awareness and understanding the subsurface environment; moreover, it produces a large amount of hardcopy data. To overcome these limitations, the UMineAR mobile tablet application was developed. It enables users to rapidly identify underground mine objects (drifts, entrances, boreholes, hazards) and intuitively visualize them in 3D using a mobile augmented reality (AR) technique. To design UMineAR, South Korean georeferenced standard-mine geographic information system (GIS) databases were employed. A web database system was designed to access via a tablet groundwater-level data measured every hour by sensors installed in boreholes. UMineAR consists of search, AR, map, and database modules. The search module provides data retrieval and visualization options/functions. The AR module provides 3D interactive visualization of mine GIS data and camera imagery on the tablet screen. The map module shows the locations of corresponding borehole data on a 2D map. The database module provides mine GIS database management functions. A case study showed that the proposed application is suitable for onsite visualization of high-volume mine GIS data based on geolocations; no specialized equipment or skills are required to understand the underground mine environment. UMineAR can be used to support abandoned-mine hazard site investigations.

Automatic Tool Selection System based on STEP_NC and ISO13399 Standards

Computer Aided Process Planning (CAPP) is considered as an essential component of Computer Integrated manufacturing (CIM) environment and it is an important interface between Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM). The purpose of the CAPP is to determine automatically the use of available resources, including machines, cutting inserts, holders, appropriate machining parameters such as cutting speed, feed rate, depth of cut, and generates automatic sequences of operations and instructions to convert a raw material into a required product,with good surface finish.The contribution of this work in CAPP field is the development of an automatic tool selection system based on STEP_NC and ISO 13399 standards for turning and milling processes. The paper presentsthe result of study and analysis of principal system functionalities to be considered. The system consist of four principal modules: a Tool database, feature recognition module, cutting tool selection module and a process optimization module.Finally, based on functional analysis results, the paper present the development of tool database and data tool extraction module from ISO 13399 File using oriented object programing.

IP027. A Preoperative Risk Score for Transfusion in Infrarenal Endovascular Aneurysm Repair to Avoid Type and Cross

Preoperative type and crossmatch is often routinely ordered before elective endovascular aneurysm repair (EVAR), but the cost of this practice is high, and transfusion is rare. We therefore aimed to stratify patients by their risk of transfusion to identify a cohort in whom a type and screen would be sufficient. We queried the targeted vascular module of the National Surgical Quality Improvement Program database for all elective EVARs from 2011 to 2015. We included only infrarenal aneurysms and excluded ruptured aneurysms and patients who received a transfusion within 72 hours preoperatively. Two-thirds of the cases were randomly assigned to a prediction cohort and one-third to a validation cohort. We created and subsequently validated a risk model for transfusion within the first 24 hours of surgery (including intraoperatively), using logistic regression. Between 2011 and 2015, 4875 patients underwent elective infrarenal EVAR, of which only 221 (4.5%) received a transfusion within 24 hours of surgery. The frequency of transfusion over the study period declined monotonously from 6.5% in 2011 to 3.2% in 2015. The factors independently associated with transfusion were preoperative hematocrit <36% (odds ratio [OR], 3.4; 95% confidence interval [CI], 2.1-5.4; P < .001), aortic diameter (per cm increase: OR, 1.2; 95% CI, 1.03-1.4; P = .02), preoperative dependent functional status (OR, 2.5; 95% CI, 1.1-5.5; P = .03), and chronic obstructive pulmonary disease (OR, 1.7; 95% CI, 1.04-2.9; P = .04). A risk-prediction model based on these criteria (Table) produced a C statistic of 0.69 in the prediction cohort and 0.76 in the validation cohort and a Hosmer-Lemeshow goodness of fit of 0.62 and 0.14, respectively. A score of <3 of 9, corresponding to a <5% probability of transfusion, would avoid preoperative type and crossmatch in 86% of patients. Of the 4203 patients (86%) with a hematocrit >36, only six (0.1%) had a risk score >3. Perioperative transfusion for EVAR is becoming increasingly uncommon and is predicted well by a transfusion risk score, or simply a hematocrit of <36. Application of this risk score would avoid unnecessary type and crossmatch in the majority of patients, leading to significant savings in both time and cost.TablePreoperative risk scoreCriteriaPointsTotal pointsRisk of transfusion (%)Cumulative frequency (%)Hematocrit01.9741.54 <30513.0278.91 30-36324.6286.15 ≥36036.9991.02410.4596.12Diameter515.3497.99 >5.51621.9699.36 ≤5.50730.4099.75840.4199.88COPD951.29100 Yes1 No0Dependent functional status Yes2 No0COPD, Chronic obstructive pulmonary disease. Open table in a new tab

Outcome following valve surgery in Australia: development of an enhanced database module

BackgroundValvular heart disease, including rheumatic heart disease (RHD), is an important cause of heart disease globally. Management of advanced disease can include surgery and other interventions to repair or replace affected valves. This article summarises the methodology of a study that will incorporate enhanced data collection systems to provide additional insights into treatment choice and outcome for advanced valvular disease including that due to RHD.MethodsAn enhanced data collection system will be developed linking an existing Australian cardiac surgery registry to more detailed baseline co-morbidity, medication, echocardiographic and hospital separation data to identify predictors of morbidity and mortality outcome following valve surgery.DiscussionThis project aims to collect and incorporate more detailed information regarding pre and postoperative factors and subsequent morbidity. We will use this to provide additional insights into treatment choice and outcome.

Robust local L2,1tracker via red-green-blue color channel fusion

We propose a robust local L 2,1 tracker based on red-green-blue (RGB) color channel fusion. In this tracker, the object is first divided into some patches with overlap region, and then the local sparse optimization from RGB color channels in each patch is solved via the L 2,1 mixed-norm regularization, which can realize the fusion of multicolor channel information. In the calculation of candidate object confidence, the confidences from RGB color channels are fused to obtain the total confidence of candidate object, this can accurately select the best candidate object. In the update module of template set and dictionary database, we design an adaptive update mechanism. The template and dictionary to delete are determined by sorting the cosine similarities between the tracking result and templates while the update of dictionary database is completed by replacing the old dictionaries with the reconstruction results of all the patches corresponding to the tracking result. This update method can effectively adapt to the appearance change of the object, and it can alleviate the tracking drift. Both qualitative and quantitative evaluations on challenging video sequences demonstrate that the tracker proposed is reliable and effective. It performs favorably against several state-of-the-art methods.

Digital Management Mechanism of Sudden Geological Disaster Emergency Plan

Digital emergency plan is an important part of the emergency platform. This paper proceeds as follow. Firstly, it presents the key technologies of digital emergency plan, emphasizing feature extraction, multi-source information fusion and GIS technology. And then the processes of the geological disaster emergency plan are discussed based on the “The national sudden geological disaster emergency plan” for guideline, including regional geological disaster warning information response process and single geological disaster emergency response information flow, . Moreover, the digital prototype system is designed, including the framework of geological disaster emergency plan of the overall structure, database and function modules. Finally, based on MapGIS platform, B/S mode, using Flex, Flash Builder technology, it developed the prototype system for experiment.

Designing Multi-Agent Simulation with Big Time Series Data for a Global Supply Chain System

Multinational corporations produce products at relatively few factories and then sell those products in all areas of the world. Longer lead times increase the risk of fluctuations in product demand. To reduce this risk, the entire business chain, from production to sale, must be optimized. In this study, we propose, implement, and verify a total optimization system. This system uses multi-agent simulation on big time series data. It consists of management, integrated database, and operation modules.

A planning support system to optimize approval of private housing development projects

Out of 182 million population of Pakistan, 38% reside in urban areas having an average growth rate of 1.6%, raising the urban housing demand significantly. Poor state response to fulfil the housing needs has resulted in a mushroom growth of private housing schemes (PHS) over the years. Consequently, only in five major cities of Punjab, there are 383 legal and 150 illegal private housing development projects against 120 public sector housing schemes. A major factor behind the cancerous growth of unapproved PHS is the prolonged and delayed approval process in concerned approval authorities requiring 13 months on average. Currently, manual and paper-based approaches are used for vetting and for granting the permission which is highly subjective and non-transparent. This study aims to design a flexible planning support system (PSS) to optimize the vetting process of PHS projects under any development authority in Pakistan by reducing time and cost required for site and documents investigations. Relying on the review of regulatory documents and interviews with professional planners and land developers, this study describes the structure of a PSS developed using open- source geo-spatial tools such as OpenGeo Suite, PHP, and PostgreSQL. It highlights the development of a Knowledge Module (based on regulatory documents) containing equations related to scheme type, size (area), location, access road, components of layout plan, planning standards and other related approval checks. Furthermore, it presents the architecture of the database module and system data requirements categorized as base datasets (built-in part of PSS) and input datasets (related to the housing project under approval). It is practically demonstrated that developing a customized PSS to optimize PHS approval process in Pakistan is achievable with geospatial technology. With the provision of such a system, the approval process for private housing schemes not only becomes quicker and user-friendly but also transparent.