DB2 Database Research Articles

Effectiveness of Digital Transformation in Data Warehouse Technology

Banking performance must always be maintained in providing fast and accurate services based on data processing results. PT Bank ABC has several data warehouse from various sources. The technology used makes the reporting process more complex, and maintenance costs are high. This research presents the data warehouse system transformation process using a single source of truth approach and the use of Extract, Transform, and Load (ETL) tools from IBM InfoSphere DataStage version 11.5. ETL testing is carried out on the Performance Measurement System (PMS) process by business units to monitor, identify, and analyze performance in each business unit. The results obtained proved to be faster than DB2 and Oracle database queries. Using the DataStage platform provides advantages in time efficiency, which is a crucial factor in overall data processing. In addition, DataStage Integration can have a positive impact on overall system performance, support smooth operations, and minimize the potential for database server overload.

Making existing software quantum safe: A case study on IBM Db2

The software engineering community is facing challenges from quantum computers (QCs). In the era of quantum computing, Shor's algorithm running on QCs can break asymmetric encryption algorithms that classical computers practically cannot. Though the exact date when QCs will become "dangerous" for practical problems is unknown, the consensus is that this future is near. Thus, the software engineering community needs to start making software ready for quantum attacks and ensure quantum safety proactively. We argue that the problem of evolving existing software to quantum-safe software is very similar to the Y2K bug. Thus, we leverage some best practices from the Y2K bug and propose our roadmap, called 7E, which gives developers a structured way to prepare for quantum attacks. It is intended to help developers start planning for the creation of new software and the evolution of cryptography in existing software. In this paper, we use a case study to validate the viability of 7E. Our software under study is the IBM Db2 database system. We upgrade the current cryptographic schemes to post-quantum cryptographic ones (using Kyber and Dilithium schemes) and report our findings and lessons learned. We show that the 7E roadmap effectively plans the evolution of existing software security features towards quantum safety, but it does require minor revisions. We incorporate our experience with IBM Db2 into the revised 7E roadmap. The U.S. Department of Commerce's National Institute of Standards and Technology is finalizing the post-quantum cryptographic standard. The software engineering community needs to start getting prepared for the quantum advantage era. We hope that our experiential study with IBM Db2 and the 7E roadmap will help the community prepare existing software for quantum attacks in a structured manner.

Reconstruction of incomplete surface electromyography based on an adversarial autoencoder network

Surface electromyography (sEMG) signals are often incomplete due to interferences during data measurement, which can degrade sEMG-based applications. To address this issue, this paper proposes a novel adversarial autoencoder model, called the SGMD-AAE, which includes a self-mask generator and a multi-view discriminator. The generator’s binary mask is replaced with a self-mask mechanism, and an adversarial loss is added to promote the reconstruction performance. The multi-view discriminator extracts and fuses deep features of sEMG from time and frequency domains to enhance the generator’s reconstruction ability. The SGMD-AAE model is evaluated on the benchmark NinaPro DB2 database, and the experimental results show that it significantly outperforms incomplete sEMG signals, reducing NRMSE by 88.04% and increasing PSNR by 116.21%. The proposed model also achieves high recognition accuracy for hand gesture recognition even in extreme cases where 90% of the sEMG signals are missing, with an average accuracy exceeding 84%. The effectiveness of the SGMD-AAE model is further verified on a self-collected dataset, demonstrating similar recognition results.

Construction of Digital Case Base System Based on DB2 Database

DB2 database supports from mainframe to single-user environment, and makes database localization and remote connection transparent, simplifies the operation and maintenance process of database system, and has become the most important platform for data storage and processing of mainframe system. Digital teaching resources simplify the knowledge and teaching difficulties through multimedia devices, making the communication and interaction between teachers and students more convenient. Teaching case base is one of the digital teaching resources, and the construction of digital teaching case base for recitation based on DB2 database meets the needs of teaching reform and development in the information age. The DB2 object architecture and DB2 Viper architecture are analysed, the database design and functional design of digital teaching case base system for recitation are carried out, and the specific application scheme is proposed.

RIDGE FREQUENCY ESTIMATION FOR LOW-QUALITY FINGERPRINT IMAGES ENHANCEMENT USING DELAUNAY TRIANGULATION

In this paper, we propose a hybrid computational geometry-gray scale algorithm that enhances fingerprint images greatly. The algorithm extracts the local minima points that are positioned on the ridges of a fingerprint, then, it generates a Delaunay triangulation using these points of interest. This triangulation along with the local orientations give an accurate distance and orientation-based ridge frequency. Finally, a tuned anisotropic filter is locally applied and the enhanced output fingerprint image is obtained. When the algorithm is applied to rejected fingerprint images from FVC2004 DB2 database by the veryfinger application, these images pass and experimental results show that we obtain a low false and missed minutiae rate with an almost uniform distribution over the database. Moreover, the application of the proposed algorithm enables the extraction of features from all low-quality fingerprint images where the equal error rate of verification is decreased from 6.50% to 5% using nondamaged low-quality images in the database.

Modified color motif co-occurrence matrix for image indexing and retrieval

In this paper, the modified color motif co-occurrence matrix (MCMCM) is presented for content-based image retrieval. The proposed method collects the inter-correlation between the red, green, and blue color planes which is absent in color motif co-occurrence matrix. The proposed method integrates the MCMCM and difference between the pixels of a scan pattern (DBPSP) features with equal weights in contrast to the system which integrates motif co-occurrence matrix, DBPSP, and color histogram with k-mean features with optimized weights. The retrieval results of the proposed method are tested on different image databases i.e. MIT VisTex (DB1) and Corel-1000 (DB2). The results after being investigated show a significant improvement in terms of average retrieval rate and average retrieval precision on DB1 database and average precision, average recall and average retrieval rate on DB2 database as compared to the state-of-art techniques on respective databases.

Statistical Descriptors for Fingerprint Matching

paper presents a novel algorithm for fingerprint matching using statistical descriptors. This fingerprint-matching algorithm overcomes the problems faced during matching of low quality fingerprint images. The steps of the algorithm include extraction of core point using Poincare index method, extraction of Region of Interest (ROI) around core point, and similarity evaluation of statistical descriptors using k-NN classifier. Statistical descriptors are computed from 16 Gray Level Co-occurrence Matrices (GLCM) from Extracted ROI. The proposed algorithm is evaluated on the FVC2002 DB2 database. The experimental results show the effectiveness of proposed algorithm. Computational efficiency is improved by considering the ROI of size 101  101 around the core point.

Binary Wavelet Transform Based Histogram Feature for Content Based Image Retrieval

In this paper a new visual feature, binary wavelet transform based histogram (BWTH) is proposed for content based image retrieval. BWTH is facilitated with the color as well as texture properties. BWTH exhibits the advantages of binary wavelet transform and histogram. The performance of CBIR system with proposed feature is observed on Corel 1000 (DB1) and Corel 2450 (DB2) natural image database in color as well as gray space. The results analysis of DB1 database illustrates the better average precision and average recall of proposed method in RGB space (73.82%, 44.29%) compared to color histogram (70.85%, 42.16%), auto correlogram (66.15%, 39.52%) and discrete wavelet transform (60.83%, 38.25%). In case of gray space also performance of proposed method (66.69%, 40.77%) is better compared to auto correlogram (57.20%, 35.31%), discrete wavelet transform (52.70%, 32.98%) and wavelet correlogram (64.3%, 38.0%). It is verified that in case of DB2 database also average precision, average recall and average retrieval rate of proposed method are significantly better.

Enhancement of feature extraction for low-quality fingerprint images using stochastic resonance

This paper presents a new approach to enhancing feature extraction for low-quality fingerprint images by adding noise to the original signal. Feature extraction often fails for low-quality fingerprint images obtained from excessively dry or wet fingers. In nonlinear signal processing systems, a moderate amount of noise can help amplify a faint signal while excessive amounts of noise can degrade the signal. Stochastic resonance (SR) refers to a phenomenon where an appropriate amount of noise added to the original signal can increase the signal-to-noise ratio. Experimental results show that Gaussian noise added to low-quality fingerprint images enables the extraction of useful features for biometric identification. SR was applied to 20 fingerprint images in the FVC2004 DB2 database that were rejected by a state-of-the-art fingerprint verification algorithm due to failures in feature extraction. SR enabled feature extraction from 10 out of 11 low-quality images with poor contrast. The remaining nine images were damaged fingerprints from which no meaningful features can be obtained. Improved feature extraction using SR decreases an equal error rate of fingerprint verification from 6.55% to 5.03%. The receiver operating characteristic curve shows that the genuine acceptance rates are improved for all false acceptance rates.

Comparing Effects of Auricular Acupressure with and Without an Internet-Assisted Program on Smoking Cessation and Self-Efficacy of Adolescents

This study aimed to develop an Internet-assisted smoking cessation program accompanied with auricular acupressure, and compare the quit rate and self-efficacy of youth smokers receiving auricular acupressure with and without the Internet-assisted smoking cessation program. A Website was constructed on IBM Websphere 5.0 and DB2 database using HTML, Javascript, and JSP. A quasiexperimental research design was adopted. Subjects were assigned nonrandomly to two groups. Group 1 received auricular acupressure plus the Internet-assisted smoking cessation program, whereas group 2 received auricular acupressure only. The data of demographic factors, serum cotinine, quitting rate, nicotine dependence, and self-efficacy of subjects were collected before and after a 4-week intervention. After intervention, the quit rate was 15.78% in group 1 and 2.56% in group 2. Nicotine dependence was significantly lowered in group 1, but remained unchanged in group 2. The improvement of self-efficacy between groups 1 and 2 was significantly different. The combination of auricular acupressure and Internet-assisted smoking cessation program was more efficacious than auricular acupressure alone in terms of quit rate.

Improvements to GALA and dbERGE II: databases featuring genomic sequence alignment, annotation and experimental results.

We describe improvements to two databases that give access to information on genomic sequence similarities, functional elements in DNA and experimental results that demonstrate those functions. GALA, the database of Genome ALignments and Annotations, is now a set of interlinked relational databases for five vertebrate species, human, chimpanzee, mouse, rat and chicken. For each species, GALA records pairwise and multiple sequence alignments, scores derived from those alignments that reflect the likelihood of being under purifying selection or being a regulatory element, and extensive annotations such as genes, gene expression patterns and transcription factor binding sites. The user interface supports simple and complex queries, including operations such as subtraction and intersections as well as clustering and finding elements in proximity to features. dbERGE II, the database of Experimental Results on Gene Expression, contains experimental data from a variety of functional assays. Both databases are now run on the DB2 database management system. Improved hardware and tuning has reduced response times and increased querying capacity, while simplified query interfaces will help direct new users through the querying process. Links are available at http://www.bx.psu.edu/.

EMC information sharing

In this extended abstract we briefly describe EMC's information sharing technology that enables UNIX and NT systems to directly access MVS mainframe datasets and how this technology can be used to directly access an MVS DB2 database.

Cooperative Processing: A Team Approach

Summary PRISM (PRoducing Information System for Mobil E&P U.S.) is a production-and drilling-information collection and retrieval system with a centralized data-storage facility that uses both PC’s and mainframes. The system uses cooperative processing through PC programs that enter and extract data that reside on a mainframe. The mainframe and PC’s work together as a team, cooperatively processing the data input to and output from the system. This team concept provides the capability to maximize the best features of both types of computers, providing the user with a very powerful, yet extremely simple, system. This system has been developed on multiple platforms, including the IBM PC, IBM mainframes, and the Apple Macintosh. The PC’s are used to display the input and output screens and reports to the user. The application is written with Microsoft Windows™ on the IBM PC and the same type of graphical interface native to the Macintosh. The PC programs interactively transmit the data to and from the mainframe DB2 data base. The users interact with a program that appears to exist entirely on their own PC’s. The system was developed with the same type of cooperative philosophy exhibited in the system itself. The development team consisted of engineers, geologists, accountants, field supervisors, computer professionals, and other client representatives. This team approach included a major commitment of the client sponsors, who assigned full-time staff members to work on the project from start to finish. The project team could use the best characteristics and experience of each team member to develop a system to meet the ever-increasing informational needs of the user community.