Database Support Research Articles

Insights from the Compilation and Critical Assessment of Breach and Runout Characteristics from Historical Tailings Dam Failures: Implications for Numerical Modelling

Numerical models are used for detailed and site-specific tailings dam breach analyses (TDBAs) to estimate the downstream inundation and deposition resulting from a potential breach at a tailings dam. The results of TDBAs are key inputs into risk assessments, consequence classification, and emergency planning. This paper describes the research and development of a database of 12 tailings dam breach events with a specific focus on observations that are needed for numerical modelling, in conjunction with an assessment of existing dam breach conventions to improve consistency in reporting. The characteristics relevant to modelling include outflow volumes, breach processes, breach geometries, and runout observations local to the downstream area. This study and the new database shed light on the diversity of outflow materials, facility arrangements, breach processes, and downstream environments that affect the breach development and tailings runout. Familiarity with case studies is a crucial element of expert judgement for forward-analysis TDBAs, which this database supports. The database can also be used to define model inputs for back-analysis of additional tailings dam breach events, and simultaneously provides calibration or validation constraints with the runout observations. Continued review and critical assessments are needed to reduce uncertainties and to enhance case history data availability and quality in this database.

Extending factory digital Twins through human characterisation in Asset Administration Shell

ABSTRACT This paper extends the traditional factory digital twins by incorporating human characterisation in Asset Administration Shell (AAS). The extension lays the basis for human-centred control and management, as demonstrated by employing a prototype of the extended AAS in two proposed use cases. Referred to Industry 5.0, an accurate digital representation of humans as a basis of the data-based decision support to improve operators’ well-being and resilience. The AAS is extended to include dedicated digital models accommodating a set of properties to describe the human operators and its interactions with the surrounding shop-floor resources. Two reference use cases have been designed in the context of a complete lab-scale manufacturing system: equipment and devices have been modelled according to the AAS standard, exposing information via MQTT, and have been integrated with the proposed AAS definition of human operators. Operators have been equipped with wearable sensors and a dashboard providing them with feedback from the manufacturing environment and notifications about changes. As part of the extension process, some ethical and regulation concerns are discussed, highlighting that the extended AAS is mature enough to support the inclusion of human operators, but regulations struggle to keep up with technological advances.

Global carbon uptake of cement carbonation accounts 1930–2021

Abstract. The main contributor to the greenhouse gas (GHG) footprint of the cement industry is the decomposition of alkaline carbonates during clinker production. However, systematic accounts for the reverse of this process – namely carbonation of calcium oxide and other alkaline oxides and/or hydroxides within cement materials during cements' life cycles – have only recently been undertaken. Here, adopting a comprehensive analytical model, we provide the most updated estimates of CO2 uptake by cement carbonation. The accumulated amount of global CO2 uptake by cements produced from 1930 to 2021 is estimated to be 22.9 Gt CO2 (95 % confidence interval, CI: 19.6–26.6 Gt CO2). This amount includes the CO2 uptake by concrete, mortar, construction waste and kiln dust, accounting for 30.1 %, 58.5 %, 4.0 % and 7.1 % respectively. The cumulative carbon uptake by cement materials from 1930 to 2021 offsets 55.1 % of the emissions from cement production (41.6 Gt CO2, 95 % CI: 38.7–47.2 Gt CO2) over the same period, with the greater part coming from mortar (58.5 % of the total uptake). China has the highest cement carbon uptake, with cumulative carbonation of 7.06 Gt CO2 (95 % CI: 5.22–9.44 Gt CO2) since 1930. In addition, the carbon uptake amounts of the USA, EU, India and the rest of the world took 5.0 %, 23.2 %, 5.6 % and 34.8 % separately. As a result of rapidly increased production in recent years, over three-quarters of the cement carbon uptake has occurred since 1990. Additionally, our results show little impact by the COVID-19 pandemic on cement production and use, with carbon uptake reaching about 0.92 Gt CO2 (95 % CI: 0.78–1.10 Gt CO2) in 2020 and 0.96 Gt CO2 (95 % CI: 0.81–1.15 Gt CO2) in 2021. Our uniformly formatted and most updated cement uptake inventories provide coherent data-based support for including cement carbon uptake into future carbon budgets from the local to global scale. The latest version contains the uptake data till 2021, showing the global uptake's increasing pattern and offering more usable and relevant data for evaluating cement's carbon uptake capacity. All the data described in this study are accessible at https://doi.org/10.5281/zenodo.7516373 (Bing et al., 2023).

69 The Bigger Picture of Phenomics: Whole-System Support for Systems Research, Models and Databases

Abstract Phenomics started with Mendel’s elegantly simple empirical studies. Soon after, Fisher discovered purines were rich in nuclei of all cells. A century later, we have the technology to compare the actual base pair sequence of DNA and RNA with the outward expressions of phenotypes. We have sire evaluation based on genomic and phenomic measure. But, being human, it is quite common to get immersed in exciting technology and tend to forget why we developed the technology in the first place. We only refer to ensuring a stable efficient food supply of plants and animals in the reports that we expect decision makers to read and give us more money. It is, however, truly wonderful that we now have the techniques to study the questions of the ages. But the future of phenomics is built on the foundations of the past. In 1974, A. E. Freeman and others convened a meeting under the mechanism of the newly formed Regional Research Project 2 on Defining the Inefficiency of Animal Production. From that workshop came the first modern multistate genetic study in dairy cattle with the objective to compare the phenotypes (milk component production, energy and nitrogen metabolism, hormones) of dairy animals that were born from bulls of High (+795 kg PTAM) and Low (167 kg PTAM) bulls. Please remember this study was designed in the mid 1970s and the first data collected in the early 1980s, decades before efficient methods of DNA and RNA composition were available. Studies conducted at Washington State University demonstrated marked genetic and environmental differences in adipose tissues of dairy animals. Enzymes involved with catabolic reactions were highly associated with High PTAM bulls while enzymes associated with anabolic reactions in adipose tissue were more closely related to increased energy intake regardless of genetic background. With mRNA chips, we were able, after almost 40 years, to directly relate variation in mRNA expression in the adipose tissue with the genetic background of the animals. This was the first such discovery in the field, and has led to more defined and expansive phenomics studies. In the year 2023, the use of genomics, phenomics, databases, large scale, cooperative studies and team science are specific recommendations, strategies and goals of the USDA, NIFA, The National Academies, and Land-Grant Universities. The AgBioData consortium is one example of international teams working together to expand the use of genetic and genomic databases, to prepare undergraduate and graduate level educational materials on FAIR databases and to encourage and support sustainable, robustly funded public and private partnerships in the use of integrated studies and large databases, including phenomics, with the sole purpose of expanding a robust, resilient, safe and plentiful food supply.

Knowledge Base Question Answering via Semantic Analysis

Knowledge Question Answering is one of the important research directions in the field of robot intelligence. It is mainly based on background knowledge to analyze users’ questions and generate answers. It is one of the important application methods of knowledge graph technology. Compared with the traditional expert system of question and answer, it has the advantage of a large-scale background knowledge base and the traceability and interpretability of the question-answering process. Compared with the current ChatGPT (Chat Generative Pre-trained Transformer) technology, it has advantages in the proprietary segmentation field. Aiming at the problem of the accuracy of existing knowledge question-answering methods being low, this paper studies the method of semantic analysis for knowledge question-answering under the support of a knowledge database, proposes a knowledge question-answering method based on the superposition of multiple neural network models, and conducts experimental verification on the publicly available NLPCC2016KBQA(Knowledge Q&A Tasks in the 2016 Natural Language Processing and Chinese Computing Conference) data set. The experimental results show that the F1 value of this method is higher than that of the baseline model.

El doblete correcto/correcho y sus derivados en la diacronía del español

Abstract Alongside the evolutionary phenomena that arose in the transition from Latin to Romance, there were educated reactions that rescued the original voices to accommodate them, with minor adjustments, to the systems of the Romance languages, at the same time as the patrimonial words, evolved from the same etymons, managed to stay in the spoken register and from there passed to the linguistic system. Such processes gave rise to the development of doublets in the language, pairs of duplicates that, from a common etymological base, gave different results, such as the one formed by the correcto/correcho pair, whose history and geographical distribution (with the exclusive presence of the patrimonial result correcho in the provinces of León and Asturias) itself illustrates phonological processes that, on occasion, go beyond the territorial boundaries established by historical grammars. The derivative adjective escorrecho is related to these words, which enjoyed remarkable vitality in the 13th century and began to decline later until it fell into oblivion, since the Dictionary of Authorities (1929) already defines it as an outdated term whose appearance in lexicographical works does not exceed the margins of the first half of the 19th century. The processes that led to these evolutions will be explained in the present study with the support of databases on Spanish and the main tools of our lexicographical tradition.

Assessment and simulation of ecosystem carbon storage in rapidly urbanizing areas based on land use cover: a case study of the southern Jiangsu urban agglomeration, China

Since China’s reform and opening-up period, the southern Jiangsu urban agglomeration has been one of the fastest urbanizing regions in the country. This rapid urbanization has led to dramatic changes in land use cover that have been the primary drivers of carbon stock changes in the terrestrial ecosystem. In this study, we utilize the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and a patch-generating land use simulation (PLUS) model to analyze the land use changes and carbon stocks in the southern Jiangsu urban agglomeration over the past 30 years. We then simulate the carbon stock changes in the study area in the year 2050 under natural growth, cultivated land conservation, and ecological conservation scenarios. The results showed that 1) over the past 30 years, the urban area has increased by 2.98 times, reaching 7,408.42 km2 by 2020. In contrast, the area of cultivated and forested land has continued to decrease with rapid urbanization. 2) Between 1990 and 2020, the carbon stock of the urban agglomeration in southern Jiangsu decreased by 5.34%. The changes in the spatial distribution of carbon stocks are consistent with the changes in land use. 3) By 2050, the carbon stock loss was the largest under the natural growth scenario at 10.49 mt, while the carbon stock loss was the smallest under the cultivated land protection scenario at 0.97 mt. Under the ecological protection scenario, the carbon stock loss was 9.9 mt. The results indicate that the adoption of cultivated land and ecological protection measures can effectively control the reduction of carbon stock in rapidly urbanizing areas. 4) The conversion of cultivated land and forest land to urban land was the primary reason for the carbon stock reduction in the study area, which was primarily located in the urban outward expansion area. This study provides a reference- and data-based support for the management, decision-making, and planning in rapidly urbanizing areas.

Osteosarcoma Explorer: A Data Commons With Clinical, Genomic, Protein, and Tissue Imaging Data for Osteosarcoma Research.

Osteosarcoma research advancement requires enhanced data integration across different modalities and sources. Current osteosarcoma research, encompassing clinical, genomic, protein, and tissue imaging data, is hindered by the siloed landscape of data generation and storage. Clinical, molecular profiling, and tissue imaging data for 573 patients with pediatric osteosarcoma were collected from four public and institutional sources. A common data model incorporating standardized terminology was created to facilitate the transformation, integration, and load of source data into a relational database. On the basis of this database, a data commons accompanied by a user-friendly web portal was developed, enabling various data exploration and analytics functions. The Osteosarcoma Explorer (OSE) was released to the public in 2021. Leveraging a comprehensive and harmonized data set on the backend, the OSE offers a wide range of functions, including Cohort Discovery, Patient Dashboard, Image Visualization, and Online Analysis. Since its initial release, the OSE has experienced an increasing utilization by the osteosarcoma research community and provided solid, continuous user support. To our knowledge, the OSE is the largest (N = 573) and most comprehensive research data commons for pediatric osteosarcoma, a rare disease. This project demonstrates an effective framework for data integration and data commons development that can be readily applied to other projects sharing similar goals. The OSE offers an online exploration and analysis platform for integrated clinical, molecular profiling, and tissue imaging data of osteosarcoma. Its underlying data model, database, and web framework support continuous expansion onto new data modalities and sources.

Fully Automated Dispensing System Based on Machine Vision

To address the problems of low productivity and sizeable dispensing positioning errors in manual and semi-automatic dispensing processes in small- and medium-sized electronic enterprises, this study proposes a fully automatic dispensing method based on visual positioning with RJDNEL-type PCBs as the research object. The fully automatic dispensing system is constructed through the construction of a mechanical structure, the selection of optical equipment, and the debugging of the control system. The method is based on optical imaging technology. Firstly, the dispensing area is extracted through image preprocessing; then, the edge is detected by the Sobel operator, and the Hilditch operator optimizes the dispensing sharpness; then, the minimum outer rectangle algorithm is used to calculate the positioning information of the dispensing area by using the relationship between geometric transformations, which provides the database support for the realization of automatic dispensing; finally, the simulated annealing algorithm is adopted to optimize the dispensing path. Through the image acquisition matching experiments and positioning accuracy experimental analysis, it is concluded that the matching success rate is more than 99%, and the image positioning information repeated extraction accuracy error is less than 0.02 mm. Analysis of the total path of dispensing, as well as computing time, was performed as follows: for the complete dispensing process, 20 PCB boards were used; the path optimization of the dispensing path was reduced by 723.4 mm, and the dispensing efficiency was improved by 20% to 30%; after dispensing, the dispensing area measurement was performed on the PCB boards. PCB boards meet the quality requirements of dispensing, and the proposed method for meeting the quality of dispensing at the same time effectively improves the dispensing accuracy and efficiency.

NeuroCNN_GNB: an ensemble model to predict neuropeptides based on a convolution neural network and Gaussian naive Bayes.

Neuropeptides contain more chemical information than other classical neurotransmitters and have multiple receptor recognition sites. These characteristics allow neuropeptides to have a correspondingly higher selectivity for nerve receptors and fewer side effects. Traditional experimental methods, such as mass spectrometry and liquid chromatography technology, still need the support of a complete neuropeptide precursor database and the basic characteristics of neuropeptides. Incomplete neuropeptide precursor and information databases will lead to false-positives or reduce the sensitivity of recognition. In recent years, studies have proven that machine learning methods can rapidly and effectively predict neuropeptides. In this work, we have made a systematic attempt to create an ensemble tool based on four convolution neural network models. These baseline models were separately trained on one-hot encoding, AAIndex, G-gap dipeptide encoding and word2vec and integrated using Gaussian Naive Bayes (NB) to construct our predictor designated NeuroCNN_GNB. Both 5-fold cross-validation tests using benchmark datasets and independent tests showed that NeuroCNN_GNB outperformed other state-of-the-art methods. Furthermore, this novel framework provides essential interpretations that aid the understanding of model success by leveraging the powerful Shapley Additive exPlanation (SHAP) algorithm, thereby highlighting the most important features relevant for predicting neuropeptides.

Solution Space Management to Enable Data Farming in Strategic Network Design

During strategic network design, not only strategic but also operational decisions must be made long before a production network is put into operation. These include determining the location and size of inventories within the production network and setting operational parameters for production lines, such as the shift model. However, the large solution space comprising a high number of highly uncertain design parameters makes these decisions challenging without decision support. Therefore, data farming offers a potential solution, as synthetic data can be generated via the execution of multiple simulation experiments spanning the solution space and then analyzed using data mining techniques to provide data-based decision support. However, data farming has not yet been applied to strategic network design due to the lack of adequate solution space management. To address this shortcoming, this paper presents a structured solution space management approach that integrates production network-specific requirements and Design of Experiment (DoE) methods. The approach enables converting the solution space in strategic network design into individual input data sets for simulation experiments, generating a comprehensive database that can be mined for data-based decision support. The applicability and validity of the comprehensive approach are ensured via a case study in the automotive industry.

SISTEM INFORMASI PENGELOLAAN DAN ANALISA PERSEDIAAN BARANG METODE RASIO BERBASIS WEB

Financial management is an administrative activity related to budget planning, storing, using, recording and monitoring the entry and exit of money or organizational funds.
 Inventory analysis is an activity to examine an asset issue that includes goods. Turn over inventory is the ratio between the total cost of goods sold and the average value of inventory owned by the company. in the process of managing finances and inventories, it is still carried out using a recording system in a ledger, so it is less effective. Therefore the author will develop a form of information system by selecting CV. Arris AC as research object.
 Based on the problems that occur in CV. Arris AC, the authors provide a solution that can overcome weaknesses by creating an Accounting Information System for Financial Management and Inventory Analysis using the inventory turnover ratio method which can be accessed via the web.
 In other words, this ratio describes how fast inventory rotates.
 web is an application that contains multimedia documents (text, images, sound, animation, video) in it that uses the HTTP protocol with database support for MySQL, Xampp and Adobe Dreamweaver CS6..
 
 Keywords:Accounting, Financial Management,
 Inventory Analysis, Ratio, Web

An investigation on the laminar flame propagation and auto-ignition characteristics of a coal-derived rocket kerosene-Part I: Experimental study

The energy structure of coal-rich and oil-poor in China, makes the conversion of coal to liquid fuels an attractive option to reduce petroleum dependence. In this study, the combustion characteristics of a newly developed coal-derived rocket kerosene were investigated to provide fundamental parameters for evaluating the feasibility and compatibility of the new fuel in potential applications. The laminar flame propagation properties of the fuel were studied at pressures of 1, 2 and 5 bar over a temperature range of 423–483 K for equivalence ratio of 0.7–1.8 in a constant volume combustion bomb, and the auto-ignition characteristics of the target fuel were then experimentally studied in a heated shock tube. Flame propagation process was studied based on the recorded flame morphology firstly. The unsteady transition from spark assisted ignition kernel propagation to normal flame was analyzed and was found to become less conspicuous in flames with stronger reaction intensity (higher initial pressure or temperature) and smaller Lewis number (higher equivalence ratio). The Markstein length was extracted by extrapolating the flame trajectories and used to investigate the flame instability. The results shows that the increase of pressure, equivalence ratio enhance the flame instability, but the impact of initial temperature shows no prominent pattern. The laminar burning velocity and ignition delay times were reported over a wide range to strengthen the understanding of combustion characteristics of the new fuel. A kinetic model was proposed to simulate the combustion chemistry of the fuel and kinetic analysis was performed to identify the key reactions driving the flame propagation and auto-ignition. The present study is hoped to provide insights into the evaluation of fuel application in the future and database support for further combustion reaction kinetic mechanism development.

PENGARUH MANAJEMEN RANTAI PASOK BERBASIS SISTEM ERP TERHADAP KINERJA KARYAWAN PT INFINEON TECHNOLOGIES BATAM

A company needs good business continuity to maximize all aspects of businessactivities, therefore a structured management governance is needed. A goodenterprise resource planning system will produce a clear flow of supply chainmanagement and create good human resource performance within the company.The existence of ERP system assistance makes it easy to obtain existing informationon a company in each division with the support of a large database so that companyoperations run smoothly, such as at PT Infineon Technologies Batam which hassurvived until now. This study uses qualitative analysis methods and is in the formof descriptive information, the data obtained will be related to the theory andanalysis of the company. The results of the study show that implementing an ERPsystem at PT Infineon Technologies Batam is very beneficial for companiesbecause it can reduce costs due to continuous integration and monitoring, as wellas another factor of implementing an ERP system at PT Infineon TechnologiesBatam is being able to adjust customer interests to obtain a more efficient level inmaximizing revenue results.Keywords: Customer, Enterprise, Enterprise resource planning, Human Resources,Management, Product, Supply Chain, Technology

Sistem Informasi Reservasi Tamu pada SEI Hotel Banda Aceh

The Guest Reservation Information System is an important aspect of data management at SEI Hotel. The aim is to simplify and direct the acquisition of information related to guest reservation reports. In this research, the author discusses the design of a Guest Reservation Information System at SEI Hotel using the CodeIgniter framework. Programming is carried out using HTML, PHP, CSS, JSON, AJAX, and MySQL as database support. This research aims to design a Guest Reservation Information System at SEI Hotel using the CodeIgniter framework and using the programming languages HTML, PHP, CSS, JSON, AJAX, and MySQL as database support. Data collection was carried out through two methods, namely library studies which included library book literature and related scientific works, as well as field studies by conducting interviews and direct observation of research objects. The guest reservation process at SEI Hotel is carried out by an administrative staff in the financial sector, who is tasked with recording and inputting guest reservation report data. The research results show that the Guest Reservation Information System at SEI Hotel has followed procedures using the CodeIgniter framework and the programming languages HTML, PHP, CSS, JSON, AJAX, and MySQL as database support

Research on the Influencing Factors of Precision Marketing in Commercial Banks from The Perspective of Data Mining

With the rapid development of financial technology, modern data mining techniques are becoming increasingly widespread in the banking industry. Telephone marketing, which offers interactivity, measurability, extensive spatial coverage, and database support, is an effective way for banks to promote their financial products. This study focuses on how to use existing customer data to explore the potential promotion value of bank financial products while meeting customer needs and to develop a telephone marketing model that is suitable for the era of big data. We begin by analyzing the data of a Portuguese bank to predict whether customers will sign a long-term deposit agreement and identify which features have a significant impact on the response variable. Univariate analysis is used to identify these features, and then the logistic regression model is employed to confirm them. Finally, the random forest model is used to identify the variables that have the greatest impact on customer response. After identifying these key variables, we analyze the reasons and provide improvement measures and optimization strategies for the telephone marketing promotion of bank financial products.

Technical framework of energy-saving construction management of intelligent building based on computer vision algorithm

At present, China's urbanization transformation is accelerating, the construction industry is developing rapidly, and people's requirements for buildings are also increasing, which leads to the increasing energy consumption. Therefore, energy-saving construction in the construction industry is imminent. During the actual life cycle of a building project, including planning, design, construction and later operation and maintenance, energy consumption will be generated in the above processes. Based on this background, this research realized the design of intelligent building management and information system for energy conservation projects by introducing computer vision algorithm. The system is integrated with laws and regulations, economic benefits, technical steps, quality management, cost management, schedule management and other modules. The design process is relatively complex. Therefore, this work adopts modern computer vision algorithm technology and uses relevant tools to collect, store, and analyze a large amount of information in each stage of energy-saving project management process and realize information management from project approval, design, drawing review, and construction to acceptance. Finally, this paper builds system interface layer, system function layer, and database support layer. The system measurement shows that the building energy consumption can be predicted easily, accurately and stably by inputting the energy consumption data collected by each part of the target building. The system realizes the combination of qualitative and quantitative research on energy conservation regulation and improves the informatization level of China's energy conservation research and construction. This paper designs a kind of intelligent building energy-saving management system by studying computer vision algorithm.

Comprehensive multi-omics analysis reveals m7G-related signature for evaluating prognosis and immunotherapy efficacy in osteosarcoma

BackgroundOsteosarcoma is one of the most prevalent bone malignancies with a poor prognosis. The N7-methylguanosine (m7G) modification facilitates the modification of RNA structure and function tightly associated with cancer. Nonetheless, there is a lack of joint exploration of the relationship between m7G methylation and immune status in osteosarcoma. MethodsWith the support of TARGET and GEO databases, we performed consensus clustering to characterize molecular subtypes based on m7G regulators in all osteosarcoma patients. The least absolute shrinkage and selection operator (LASSO) method, Cox regression, and receiver operating characteristic (ROC) curves were employed to construct and validate m7G-related prognostic features and derived risk scores. In addition, GSVA, ssGSEA, CIBERSORT, ESTIMATE, and gene set enrichment analysis were conducted to characterize biological pathways and immune landscapes. We explored the relationship between risk scores and drug sensitivity, immune checkpoints, and human leukocyte antigens by correlation analysis. Finally, the roles of EIF4E3 in cell function were verified through external experiments. ResultsTwo molecular isoforms based on regulator genes were identified, which presented significant discrepancies in terms of survival and activated pathways. Moreover, the six m7G regulators most associated with prognosis in osteosarcoma patients were identified as independent predictors for the construction of prognostic signature. The model was well stabilized and outperformed traditional clinicopathological features to reliably predict 3-year (AUC = 0.787) and 5-year (AUC = 0.790) survival in osteosarcoma cohorts. Patients with increased risk scores had a poorer prognosis, higher tumor purity, lower checkpoint gene expression, and were in an immunosuppressive microenvironment. Furthermore, enhanced expression of EIF4E3 indicated a favorable prognosis and affected the biological behavior of osteosarcoma cells. ConclusionsWe identified six prognostic relevant m7G modulators that may provide valuable indicators for the estimation of overall survival and the corresponding immune landscape in patients with osteosarcoma.

Analysis of research hotspots and trends on Chinese brands and service quality under the new development pattern of “Dual Circulation”

Brand building has achieved rapid development under the new development pattern of “Dual Circulation”, and service quality plays an important role in promoting brand efficient construction. Based on the support of China National Knowledge Network database and CiteSpace analysis software, this paper makes a quantitative analysis. Through the research of hot spots and evolution trend, it is found that the main extendable space of this topic is: The research direction of China will conform to the new development pattern of “Dual Circulation”, shift the main body of research to omni-channel integrated physical retail services, focus on the mode innovation of omni-channel integrated retail brand supply chain, explore its realization mechanism, and drive the construction and improvement of the new development pattern of dual circulation.

Design and implementation of a decision support system for flood management

This work deals with the design and implementation of a decision support system for flood management. In the society today emergency issues arises due to terrorist attack, flood disaster, epidemics, widespread massive riot etc. In other to handle this situation government has established a number of agents supported by Non-governmental organization (NGO). Due to non-existence of integrated database and communication support system for managing flood emergency has resulted to poor handling, huge losses and reoccurrences. This work involves managing the inter operations/ interlinks of flood incidents sources by the handling agents, design of database report format and communication media for the system automation. In other to solve this problem waterfall methodology was adopted in this study. The programming tool adopted was adobe dreamer. Its host has front end and back end. The front end is the user interface and serves as a channel through which users communicates to the system. Adobe dreamer being the tools used for building such web-based application supports many mark-up languages like HTML, CSS and Java script. The most common available tools for the development of this system is the Adobe Dream waver which is IDE (integrated Development Environment. It is a creation management tool and requires no programming language and good enough for experienced website developers.