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Establishing a concise and accurate analytical model is the key to developing a feasible progressive collapse design for engineering practice. However, existing models either focused on an individual force mechanism or required complicated computer programming. Among existing machine learning (ML) techniques, multi-gene genetic programming (MGGP) can be trained to obtain explicit formulas for engineering problems. In this study, a comprehensive database was established by data collection, Latin hypercube sampling and structural design, and was used to train the mathematical model for quantifying progressive collapse resistance of reinforced concrete (RC) beam-column substructures under middle column removal scenarios. Further, an energy-based error index was proposed to validate the accuracy of the MGGP model among others. The research outcomes can provide references for the development of simplified analytical models for calculating the progressive collapse progress of RC frame structures, and promote the development of the practical design method.

With the rapid advancement in high-resolution confocal imaging, various forms of microscopy deliver substantial amount of valuable 3D cell biological information. Currently, image processing, modeling, visualization and analysis on confocal microscopic datasets are, however, still more or less following the traditional fashion that is 2D centric via a slice-by-slice strategy. Such image sequence based operations not only leads to lengthy processing times but also can potentially cause problems in data communication and interpretation, and knowledge discovery in a global 3D cellular level. In this paper, we describe our solution for processing, visualization and quantification of 3D confocal images with the CellStudio system we developed. CellStudio has a collaborative feature allowing 3D confocal data to be collected and retrieved across the net. CellStudio is also an integrated solution enabling 3D confocal image processing, volumetric visualization and interactive quantification performed in a network connected PC/Window platform.

We address the problem of similarity search in large multi-dimensional time sequence databases. There has been a lot of attention in similarity search in time sequence databases. However, most of the previous work on time sequences focused on one-dimensional sequences. Many applications such as multimedia databases or weather databases, however, need to handle multi-dimensional time sequences. In this paper, we extend our previous work on the similarity search by considering query types in multi-dimensional time sequence databases and more intensive experimental results that were not reported in the previous paper are illustrated. The proposed method can efficiently reduce the search space and guarantees no false dismissals.

Genome Analyzer (GenoA) with a relational database back-end, was developed to extract information from mammalian genomic sequences. This data mining and visualization tool-set enables laboratory bench scientists to identify and assemble virtual cDNA from genomic exon sequences, and provides a starting point to identify potential alternative splice variants and polymorphisms in silico. The study described in this paper demonstrates the use of GenoA to study human brain hyperpolarization-activated cation channel genes HCN1 and HCN3.

Two novel databases, GenSensor and ConSensor, have been developed. GenSensor accumulates information on the sensitivities of the prokaryotic genes to external stimuli and may facilitate designing of novel genosensors; ConSensor contains data about the structure and efficiency of the available genosensor plasmid constructs. Using these databases, candidate genes for the design of novel multiple functional genosensors were searched, and the Escherichia coli dps gene was chosen as the candidate. The genetic construct derived from its promoter was developed and tested for its sensitivity to various stress agents: hydrogen peroxide (oxidative stress), phenol (protein and membrane damaging), and mitomycin C (DNA damaging). This genosensor was found to be sensitive to all stress conditions applied confirming its ability to serve as multi-functional genosensor. The GenSensor and ConSensor databases are available at .

Recently, a number of collaborative large-scale mouse mutagenesis programs have been launched. These programs aim for a better understanding of the roles of all individual coding genes and the biological systems in which these genes participate. In international efforts to share phenotypic data among facilities/institutes, it is desirable to integrate information obtained from different phenotypic platforms reliably. Since the definitions of specific phenotypes often depend on a tacit understanding of concepts that tends to vary among different facilities, it is necessary to define phenotypes based on the explicit evidence of assay results. We have developed a website termed PhenoSITE (Phenome Semantics Information with Terminology of Experiments: ), in which we are trying to integrate phenotype-related information using an experimental-evidence–based approach. The site's features include (1) a baseline database for our phenotyping platform; (2) an ontology associating international phenotypic definitions with experimental terminologies used in our phenotyping platform; (3) a database for standardized operation procedures of the phenotyping platform; and (4) a database for mouse mutants using data produced from the large-scale mutagenesis program at RIKEN GSC. We have developed two types of integrated viewers to enhance the accessibility to mutant resource information. One viewer depicts a matrix view of the ontology-based classification and chromosomal location of each gene; the other depicts ontology-mediated integration of experimental protocols, baseline data, and mutant information. These approaches rely entirely upon experiment-based evidence, ensuring the reliability of the integrated data from different phenotyping platforms.

In this paper, data mining is used to analyze the data on the differentiation of mammalian Mesenchymal Stem Cells (MSCs), aiming at discovering known and hidden rules governing MSC differentiation, following the establishment of a web-based public database containing experimental data on the MSC proliferation and differentiation. To this effect, a web-based public interactive database comprising the key parameters which influence the fate and destiny of mammalian MSCs has been constructed and analyzed using Classification Association Rule Mining (CARM) as a data-mining technique. The results show that the proposed approach is technically feasible and performs well with respect to the accuracy of (classification) prediction. Key rules mined from the constructed MSC database are consistent with experimental observations, indicating the validity of the method developed and the first step in the application of data mining to the study of MSCs.

This contribution presents a new Artificial Neural Network (ANN) tool that is able to predict the main parameters describing the wave-structure interaction processes: the mean wave overtopping discharge ($q$), the wave transmission and wave reflection coefficients ($K_t$ and $K_r$). This ANN tool is trained on an extended database (based on the CLASH database) of physical model tests, including at least one of the three output parameters, for a total number of nearly 18,000 tests. The selected 15 nondimensional ANN input parameters represent the most significant effects of the structure type (geometry, amour size and roughness) and of the wave attack (wave steepness, breaking, shoaling, wave obliquity). The model can be used for design purposes, leading to a greater accuracy than existing formulae and similar tools for complex geometries for the prediction of $K_r$ and $K_t$, and it has a similar accuracy as the CLASH ANN for predicting $q$.

Organisational creativity remains an ill-defined concept. Studies have failed to arrive at a convincing general theory of creativity and, more recently, attention has turned to the possibilities of middle-range theories in which creativity is treated as a context-specific phenomenon. A new approach for exploring the nature of creativity of organisations is reported with preliminary empirical results. The method draws on signalling theory applied to a database of companies generated from citations and executive nominations. Companies such as 3M, IBM, Sony, Disney and Proctor & Gamble were found to yield strong and frequent signals over extended time periods. Strong signals have also been detected from younger firms such as Microsoft, Virgin and Nike. The approach offers the possibility of industry-specific benchmarking for corporate creativity, and for testing the relationship between an organisation's creativity, innovativeness and other change-related features.

Binding MOAD (Mother of All Databases) is the largest collection of high-quality, protein-ligand complexes available from the Protein Data Bank. It has grown to 9837 hand-curated entries. Here, we describe our semi-annual updating procedures and BUDA (Binding Unstructured Data Analysis), a custom workflow tool that incorporates natural language processing technologies to facilitate the annotation process.

Semantic Computing is an emerging research field that has drawn much attention from both academia and industry. It addresses the derivation and matching of semantics of computational "content" where "content" may be anything including text, multimedia, hardware, network, etc. which can be mapped to many areas in Computer Science that involve analyzing and processing the intentions of humans with computational content. This paper discusses some potential applications of Semantic Computing in Computer Science.

This paper develops a web database application to make space-time 4D visual delivery (4DVD) of big climate data. The delivery system shows climate data in a 4D space-time box and allows users to visualize the data. Users can zoom in or out to help identify desired information for particular locations. Data can then be downloaded for the spatial maps and historical climate time series of a given location after the maps and time series are identified to be useful. These functions enable a user to quickly reach the core interested features without downloading the entire dataset in advance, which saves both time and storage space. The 4DVD system has many graphical display options such as displaying data on a round globe or on a 2D map with detailed background topographic images. It can animate maps and show time series. The combination of these features makes the system a convenient and attractive multimedia tool for classrooms, museums, and households, in addition to climate research scientists, industrial applicants, and policy makers. To demonstrate the 4DVD’s usage, several application examples are included in this paper, such as the La Nina’s influence on land temperature.

Buruli ulcer (BU), a severe skin disease is caused by Mycobacterium ulcerans. There are concerns of therapeutic inefficacy of existing drugs coupled with chemoresistance. Databases have been shown to augment data mining and integrative systems pharmacology approaches towards the search for novel therapeutic moieties. So far, there is no known integrated database solely dedicated to BU drug discovery. In this work, Buruli ulcer database (BuDb) is a “one-stop-shop” knowledgebase for supporting BU drug discovery. It contains both manually verified literature and database-curated data on BU. The BuDb provides comprehensive information on the various drug targets, tested compounds, existing drugs, ethnopharmacological plants and information on the genome of M. ulcerans. It also contains cross-referenced links to databases including PubMed, PubChem, DrugBank, NCBI, Gene Ontology (GO), UniProt, Prota4u, String database, KEGG Pathway and KEGG genome database. The BuDb has been implemented with accessibility features such as keyword and specific searches as well as browsing. BuDb is the first useful online repository of its kind integrated with enriched datasets that can aid in the discovery of new biotherapeutic entities for BU. BuDb can be freely accessed at http://197.255.126.13:3000/.

Lysosomal storage diseases (LSDs) consist of about 60 different monogenic disorders. Most of them occur due to protein misfolding. Only a few of those have been treated with molecular chaperones; the remaining either have limited treatment options or only management therapies. About 1860 single amino-acid substitutions (SAS) have been identified under LSDs. Merely, a handful of mutations have been studied experimentally. Availability of computational tools has made researchers turn toward genetic disorders to focus light on unexplored disorders and their mutations. Since all the LSDs are rare genetic disorders, not much research is carried out in this area. However, a mutational effect on protein function could be predicted, through bioinformatics tools. On that note, out of 1860 SAS, 58 predictions were neutral and 778 were predicted to be disease associated by all programs included in this study. The result of the prediction analysis of all mutations in each of the LSDs is curated into a database. This would make researchers know the deleterious nature of a mutation causing LSD. The database is available at http://lsddb.vit.ac.in:3000/.

The ADB COVID-19 Policy Database displays the measures taken and monetary amounts announced or estimated by the 68 members of the Asian Development Bank, two institutions, and nine other economies (i.e., a total of 79 entries) until May 2020, to fight the coronavirus disease (COVID-19) pandemic. Measures are classified according to (i) the path a given measure takes to affect the financial system, spending, production, and so forth, i.e., provide liquidity, encourage credit creation by the financial sector, or directly fund households; and (ii) the effects on the financial statements of households, businesses, government, i.e., whether the measures create more debt or more income. This gives a total of nine categories. When the information is available, we report the amounts that governments have announced (intentions) they will allocate to each measure (in many cases, no amount is provided because the measure does not entail spending, e.g., interest rate reductions). These are a mix of actual amounts and estimates, today and in the future (without specifying when). The database will be updated, revised, and expanded as information is released. It is available at https://covid19policy.adb.org/.

Efficient execution of data-intensive workflows has been playing an important role in bioinformatics as the amount of data has been rapidly increasing. The execution of such workflows must take into account the volume and pattern of communication. When orchestrating data-centric workflows, a centralized workflow engine can become a bottleneck to performance. To cope with the bottleneck, a hybrid approach with choreography for data management of workflows is proposed. However, when a workflow includes many repetitive operations, the approach might not gain good performance because of the overheads of its additional mechanism. This paper presents and evaluates an improvement of the hybrid approach for managing a large amount of data. The performance of the proposed method is demonstrated by measuring execution times of example workflows.

While the importance of modulatory proteolysis in research has steadily increased, knowledge on this process has remained largely disorganized, with the nature and role of entities composing modulatory proteolysis still uncertain. We built CaMPDB, a resource on modulatory proteolysis, with a focus on calpain, a well-studied intracellular protease which regulates substrate functions by proteolytic processing. CaMPDB contains sequences of calpains, substrates and inhibitors as well as substrate cleavage sites, collected from the literature. Some cleavage efficiencies were evaluated by biochemical experiments and a cleavage site prediction tool is provided to assist biologists in understanding calpain-mediated cellular processes. CaMPDB is freely accessible at http://calpain.org.

Progressive die has been widely used to mass produce metal stamping for electrical, electronic and mechanical applications. Of all the components within a progressive die set, standard parts account for a big portion of design work, which requires a lot of interactions for designer to do part selections and parameter specifications. Thus, the performance of data retrieving from the standard part database is an important factor in shortening tooling design lifecycle. Excel-based worksheets are now very popular in storing standard part parameters. However, the existing tool to retrieve Excel-based data is not sufficient due to its low speed for interactive operation in die design system. Besides, the content in a table cell still needs to be evaluated before it can be used for design. This paper reports a method to expedite the data retrieving efficiency by use of a set of predefined keyword-format files that can be easily accessed. A converting tool has been developed to convert the original Excel file into keyword-format files. Retrieving functions like searching and matching are available for these files. The proposed database is made up of the original excel files, the intermediate keyword files and tools for file conversion and data searching. The practical examples have proven the efficiency of the proposed database in our Knowledge-based Die design system.

In this chapter, information about a large and diverse database of license plates from countries around the world is presented. CENPARMI’s growing database contains images of isolated plates, including a small percentage of vanity plates, as well as landscapes, where the vehicle is included in the image. Many images contain multiple license plates, have complex scenery, have motion blur, and contain high light and shadow contrast. Photos were taken during different seasons, many are occluded by foreground objects, and some were taken through mist, fog, snow, and/or glass. In many cases, the license plate, camera, or both were in motion. In order to make training more robust, different cameras, lenses, focal lengths, shutter speeds, and ISOs (sensor sensitivity) were used. A summary of proposed guidelines used for license plate design is outlined, details about the database of license plates are presented, followed by information about ongoing work and efforts for labelling/ground truth.

It is no secret that the e-commerce industry is changing every year. Earlier, before the invention of the internet, the “brick-and-mortar” business model was used where customers needed to visit a physical outlet to purchase goods, but this is not the scenario nowadays. People now have the luxury of buying items from the convenience of their own homes online, and they are now taking advantage of it. In this 21st century with the ever-increasing number of people participating in electronic commerce, it is necessary to have advanced information technology to handle this e-commerce ecosystem. In 2018 alone, mobile conversions have increased by 55% and are expected to reach $175.4 billion in USD sales. Any business, store, or person who actively sells products online is considered part of this e-commerce system. To serve the customer with a better experience and streamline their various processes, e-commerce retailers often implement a database to strategically capture vital information. A database is a collection of data that stores organized information.

The retail business completely depends on databases 24 × 7 for order processing, transactions, inventory, order shipping, etc. With the existence of a database management system, each organization can attempt to be a lot competitive to skyrocket the decision-making process, increasing organizational performance in achieving targeted goals.

In an e-commerce application, the main purpose of a database is to store information for retrieving the product details, customer information, track transactions, and further, maintain the inventory. One of the biggest benefits of using a database for e-commerce is structuring vast amounts of shop data. When the data is organized in a proper format, it can be accessed more efficiently by e-commerce applications.

Database plays a very critical and important role in the e-commerce industry, in today’s scenario the reason behind the success of an e-commerce firm is how much it has optimized its database. Because today’s consumers rely heavily on technology, e-commerce firms must use it to their advantage.