Analytical Processing Systems Research Articles

Next Generation Data Warehouse Design with OLTP and OLAP Systems Sharing same Database

Online Transaction Processing (OLTP) systems have been using the traditional relational Database management system for many years. Online Analytical Processing (OLAP) system for analytical reporting is optimized to aggregate many records which involve more read operations. Hence to enhance the performance in OLAP systems various modeling options like star schema, extended star schema was implemented. But with the latest innovations in hardware technologies like availability of multi core dual processors, availability of 64 bit processors, decreasing cost of main memory and software technology innovations like In-Memory computing, Columnar storage and other with various other new features now there is less concern towards the performance degradation and performance optimization in a data warehouse system. If there is an option to use same database for the OLTP and OLAP systems then the business intelligence system can get the real time data for the analytical query reporting. This document presents the overview of the next generation data warehouse architecture which shares the database along with OLTP and discuss how it is going to use the in memory capability to apply real time analytics.

Numerical Simulation of Stress-Relief Effects of Protective Layer Extraction / Symulacja numeryczna skutków odprężenia warstwy zabezpieczającej w trakcie jej wybierania

Field test and laboratory analog model test on the stress-relief effects of protective layer extraction are time-consuming and laborious. In this paper, on the basis of full consideration of rock heterogeinity and in combination with gas geology at Pingdingshan Mine 5, a numerical model was estalished with the gas-solid coupling rock failure process analysis system RFPA-Gas to simulate the stress variation law, roof and floor deformation, fracture evolution law, displacement in the protected seam, change in gas permeability and gas migration law during protective layer extraction. The simulation results repoduced stress variations in coal and rock strata, roof and floor deformation and fracture evolution process during protective layer extraction. The movement of rock strata were characterized by upper three zones and lower two zones: caving zone, fracture zone and bending subsidence zone in the vertical direction in the overlying strata; floor deformation and failure zone and elasto-plastic deformation zone in the vertical direction in the underlying strata. It showed that stress relief occurred in the protected seam, which led to vertical and horizontal displacements, significant increase in gas permeability, gas desorption and migration. Hence, the outburst threat in the protected seam was eliminated. Meanwhile, with comprehensive analysis of variaition of stress state, deformation characteristics and fracture distribution in coal seam and with consideration of changes in gas leakage rate, gas pressure and permeability, according to gas leakage rate, the floor strata of the protecive layer were divided into four leakage zones. They corresponded to four zones with different stress states and fracture development: original leakage zone - slow reducing leakage zone - dramatic increasing leakage zone- steady increasing leakage zone. This classification provides a clear direction for gas control in the protective layer. The simulation results are in good agreement with the stress-relief effects in field.

A method for jointly drawing up the functional and design architectures of complex systems during the preliminary system-definition phase

In systems engineering, determining a system's architecture is a crucial part of the preliminary system-definition phase because this architecture greatly impacts the quality of the system, the way the subsequent phases of the design process are organised and the overall performance of this process. Consequently, systems architects need methods for defining the couplings of modules (or sub-systems) and for estimating the impact of allocation decisions on candidate system architectures. This paper presents a method that helps simultaneously define the functional and design architectures of complex systems. Starting from an allocation matrix, or domain mapping matrix, which represents the couplings between the elements of two domains (functions vs. components), the method generates a sesign structure matrix (DSM) for each domain. A clustering algorithm is then applied to each DSM in order to generate a rearranged architecture. This method can be used in the synthesis process to provide architectural output that then forms the input data for the systems analysis process, where these data will help systems architects assess candidate architectures. We illustrate the method via an industrial case study focusing on a new automobile engine development project.

A Novel Association Rule Hiding Approach in OLAP Data Cubes

Data mining services require exact input data for their outcomes to be significant, but privacy concerns may influence users to provide fake information. We study here, with respect to mining association rules, whether or not users can be confident to provide correct information by ensuring that the mining process cannot, with any reasonable degree of certainty, breach their privacy. A data warehouse stores current and historical records consolidated from multiple transactional systems. Protecting data warehouses is of rising interest, particularly in view of areas where data are sold in pieces to third parties for data mining studies. In this case, current normal data warehouse security techniques, like data access control, may not be easy to impose and can be in effective. As an alternative, this paper proposes a data perturbation based approach, to provide privacy preserving in association rule mining on data cubes in a data warehouse. In order to conceal association rules and save the utility of transactions in data cubes, we select Genetic Algorithm to find optimum state of modification. In our approach various hiding styles are applied in different multi-objective fitness functions. To cope with the multi-objective functions, Pareto-front ranking strategy has been applied for obtaining the non-dominated solutions front. First objective of these functions is hiding sensitive rules and the second one is keeping the accuracy of transactions in data cube. After sanitization process we test the sanitization performance by evaluation of various criterions. The major feature is that the proposed strategy does not affect the functionality of the On-Line Analytical Processing system. Finally our experimental results show its effectiveness and feasibility.

Digital-image Based Numerical Simulation on Failure Process of High-sulfur Coal

Crushing of high-sulfur coal was important for physical desulfurization, but there were little research on crushing mechanism. This paper combined digital image processing technology and rock failure process analysis system RFPA2D to simulate the failure process of high-sulfur coal in Pu'an of Guizhou under uniaxial compression, and discussed the influence of horizontal restraint, existence and different geometric distribution of pyrite particle on mechanical performance and failure process of high-sulfur coal. The numerical results indicated that without horizontal restraint the compressive strength of high-sulfur coal was lower and monomial dissociation of pyrite particle was more sufficient than that with horizontal restraint. The compressive strength of coal containing pyrite particle was larger than that of pure coal and there was stress concentration in upper and lower pyrite particle during failure process. When pyrite particle distributed in the middle position of a coal sample, the compressive strength was higher than that of the other three positions, but monomial dissociation of pyrite particle was more sufficient than that of the other three positions, and this was beneficial to the following desulfurization operation. The study had certain reference value for crushing mechanism, crushing process design, selection of breaking equipment and energy saving and consumption reduction. DOI: http://dx.doi.org/10.11591/telkomnika.v11i1.1889

Soft Systems Methodology in an Educational Context—Enhancing Students Perception and Understanding

 Abstract—This study was performed within a graduate course in the Organizational Development and Consulting graduate program. The course draws a comparison between the systems analysis processes used in computing systems (hard systems) and the organizational analysis methodologies applied in soft systems, such as Checklands' Soft Systems Methodology (SSM). Since most students' previous academic experience is in social sciences, abstract concepts related to computing systems were difficult to comprehend. The SSM that is mainly used for unstructured and poorly defined problems was exercised for identifying the students' difficulties. Using SSM for analyzing the students' perceived learning system revealed their specific difficulties, while providing a real life example on using the methodology. After understanding the students' difficulties, the course structure was changed for better addressing these difficulties. This paper describes the course, the methodology and the results obtained after implementing the proposed changes to the course.

Optimization and Practice on Method of Roof Control in Single-Support Coalface for Ascending Mining

Based on the geology and mining technology conditions of III2 coal seam in Xinzhuang Mine, the method of similar material simulation test was adopted to analyze the characteristics of overburden caving and weighting in coalface under ascending mining, and the software of Rock Failure Process Analysis System(RFPA2D) was applied to simulate and analyze the roof control effect under different mining sequence and supporting method, then engineering practice was made in III2-12111 coalface. The results showed: mining the III2 coal seam under ascending mining, the periodical weighting was 6.7 m; compared with the method of four rows single-support in maximum roof control span and three rows single-support in minimum roof control span (shorting for three-four rows roof control method) in coalface, adopting the method of three rows single-support in maximum roof control span and two rows single-support in minimum roof control span (shorting for three-two rows roof control method), gob stowing was tighter, and hanging arch distance was reduced, and roof strata stress reduced by 10~15%; the observed result of mine pressure showed, adopting three-two rows roof control method (row space for 1.2 m, column space for 0.5 m) in coalface, compression of props and roof-to-floor convergence meet the requirements, it ensured the safely and efficiently mining in coalface, and obtained the largest monthly output of 30000 t, average monthly output of 26000 t.

Data Cube Representation for Vehicle Insurance Policy System

On-Line Analytical Processing (OLAP) systems have a strong focus on the interactive analysis of data and typically provide extensive capabilities for visualizing the data and generating summary statistics. Most of the data sets can be represented as a table, where each row is an object and each column is an attribute. Data cube represents the multidimensional data with all possible aggregates. The three dimensional data cubes represent the different attributes entirely controlled with the help of objects. In general, a data cube is generalization of statistical terminology as a cross-tabulation. In the present work, authors have designed a framework of OLAP data cube to analyze the Vehicle Insurance Policy (VIP) system to identify the entity, which is highly preferred by the customer. The study describes a methodology with OLAP data cube and pivot table as well as a correlation technique which represents strong relationship among the data attributes. Tables and graphs are designed for the sample database of the Vehicle Insurance Policy System

Enhancing the Search in MOLAP Sparse Data

Multidimensional on-line analytical processing (MOLAP) systems deal well with dense data than relational ones (ROLAP). In the existence of sparse data, MOLAP systems become memory consuming, which may limit and slow down data processing tasks. Many compression techniques have been proposed to deal with the sparsity of data in MOLAP systems. One of these techniques is the bitmap compression, which allows a significant reduction of the memory space used for data processing. In this article, we propose an extension to the bitmap compression technique by storing the compressed data as bits into multiple efficient data structures based on a new indexing strategy instead of the linear structure. Compared with the classical bitmap, the proposed enhancement not only allows space reduction but also reduces the search time through the compressed data. We present some algorithms that allow maintaining and searching within the compressed structure without the need for decompression. We demonstrate that the complexity of the proposed algorithms varies from logarithmic to constant, compared with the linear complexity of the classical bitmap technique.

The Application of Data Cubes in Business Data Visualization

Data cubes are used in online analytical processing (OLAP) systems to support decision making. Constructed from base business data, this interactive visualization system introduces a conditional 1D cuboid hierarchical tree structure to represent data cubes and use 2D graphical icons to illustrate data elements. Users can then interactively explore multidimensional data in hierarchical levels.

A knowledge-management based process analysis system design through the classification of analysis parameters

In this study, a process analysis system is designed to provide web-based systematic support for small-and-medium manufacturing business which has difficulties in quality management through manufacturing informationization which requires high expenses. This system suggests an effective outcome searching methodology by defining systematic relationship between relevant database and parameters for outcome searching though development of outcome database based on outcome management and analysis parameters which are difficult in existing statistics program; suggests and realize the process analysis system based on web-oriented knowledge management through knowledge construction which is able to replace in the system through knowledge-construction for the parts required expertise to conduct analysis.

System Replacement to a New HIS and Data Warehouse

Large-scale hospital information systems (HIS) generally consist of (i) online transaction processing (OLTP) and (ii) online analytical processing (OLAP) systems. Electronic medical records (EMR) are a major OLTP element. The data warehouse (DWH) assumes many important OLAP roles and maintains an institution’s medical care at a high level by providing EMR with the best practice cases available. This article focuses mainly on why OLTP and OLAP are needed and what roles the DWH plays, which means that the DWH has its own utilities and supplementary merits. The background of this discussion is closely related to the HIS at Nagasaki University Hospital introduced before the DWH is discussed.

The Role of Justice in Historical Negotiations

AbstractThis study explores the role of justice in eleven historical cases of inter‐governmental negotiation. Building on results obtained in several recent studies on justice in negotiation, we examine a set of hypotheses about relationships among negotiating process (as distributive bargaining or problem solving), justice (as procedural and distributive), outcomes (as compromise or integrative), and the duration of the agreements. The process variables were coded from negotiators’ statements with categories from the bargaining process analysis system. The justice variables were coded with a system developed in recent studies on peace agreements. Similar to the results obtained by Hollander‐Blumoff and Tyler (2008: 473) in a simulated legal setting, we find correlations between procedural justice, problem solving, and integrative outcomes. Similar to the results obtained by Druckman and Albin (2011: 1137) on peace agreements, we find a strong relationship between distributive justice and the durability of the agreement. In these cases, problem‐solving processes were shown to mediate the relationship between procedural justice and integrative outcomes. The findings suggest that justice plays an important role across a variety of negotiation settings. We present these results as heuristic, suggesting avenues for further research on larger and more diverse samples of cases.

E3: an Elastic Execution Engine for Scalable Data Processing

With the unprecedented growth of data generated by mankind nowadays, it has become critical to develop efficient techniques for processing these massive data sets. To tackle such challenges, analytical data processing systems must be extremely efficient, scalable, and flexible as well as economically effective. Recently, Hadoop, an open-source implementation of MapReduce, has gained interests as a promising big data processing system. Although Hadoop offers the desired flexibility and scalability, its performance has been noted to be suboptimal when it is used to process complex analytical tasks. This paper presents E3, an elastic and efficient execution engine for scalable data processing. E3 adopts a “middle” approach between MapReduce and Dryad in that E3 has a simpler communication model than Dryad yet it can support multi-stages job better than MapReduce. E3 avoids reprocessing intermediate results by adopting a stage-based evaluation strategy and collocating data and user-defined (map or reduce) functions into independent processing units for parallel execution. Furthermore, E3 supports block-level indexes, and built-in functions for specifying and optimizing data processing flows. Benchmarking on an in-house cluster shows that E3 achieves significantly better performance than Hadoop, or put it another way, building an elastically scalable and efficient data processing system is possible.

The Need for Qualitative Methods in Undergraduate IS Education

Introduction curriculum for Information (IS) programs is in a flux presently owing to the much reduced enrollment across the nation. Students are simply shying away from IS programs. Even the prediction that there will be a great demand for IS-related jobs in the near future (U.S. Bureau of Labor Statistics, 2010) failed to increase enrolment in IS program across the United States. IS departments re-examined their programs and in some instances re-packaged their entire program to make it more attractive to students. With the changes in the curriculum, IS departments might also want to re-examine non-IS courses in their curriculum. A course that should be given more consideration is the qualitative research methods course. IS students in and Analysis Design and Human Computer Interaction courses are ill-equipped to utilize qualitative methods to gather and analyze users' requirement. Gathering and analyzing users' requirements is a critical step in the whole system design life cycle. Failure to correctly gather and analyze the users requirements would result in costly delays or failure of the entire system or project. This exploratory paper examines the need for the inclusion of qualitative methods course in the undergraduate IS curriculum. Literature Review need for an IS curriculum is greater in the 1980s than when it was first outlined in the position paper by a committee of the ACM (Nunamaker, Couger, & Davis, 1982). Even though the curriculum recommendations have expanded over the years, the motivations for the 1982-revised curriculum built upon those that motivated earlier curriculum efforts. expansion takes into consideration changes in the importance of information systems, advances in technology, improvements in information systems analysis and development processes, and an increased need for information systems management skills. Nunamaker et al. (1982) stress that in order for the information systems community to face the current and future demands; the curriculum should address the basic goals of people needs, skill needs, and tool needs. Furthermore, the basic philosophy of the IS program is based on the premise that graduates of the program will be employed for major segments of their careers in positions involving organizational information systems. They will * Assist in defining and planning information systems * Elicit information requirements for applications and assist in designing the systems * Implement information systems applications * Manage information system development and operation. All aspects of the global computing field continue to face rapid and frequent changes. As a result, university-level Information curricula need frequent updating to remain effective. IS 2010 Curriculum Guidelines for Undergraduate Degree Programs in Information is the latest curriculum recommendation. IS 2010 Curriculum Guidelines has four broad key characteristics that shape the outcome significantly. First, the curriculum reaches beyond the schools of business and management. Second, the outcome expectations of the curriculum have been very carefully reevaluated and articulated first in the form of high-level IS capabilities and then in three knowledge and skills categories. Third, the curriculum is structured so that it separates the core of the curriculum from electives with the intent of supporting the concept of career tracks. Finally, the design of this curriculum includes enough flexibility to allow its adoption in a variety of educational system contexts. (Topi, et al., 2010. p. vii) IS 2010 Curriculum Guidelines states the following as one of its key principles that guided the report is that The model curriculum should be designed to help Information programs to produce competent and confident entry-level graduates well suited to workplace responsibilities or further studies of Information Systems (Topi, et al. …

When logic and belief collide: Individual differences in reasoning times support a selective processing model

When the validity of a deductive conclusion conflicts with its believability people often respond in a belief-biased manner. This study used response times to test the selective processing model, which views belief-bias effects as arising from the interplay between superficial heuristic processes and more rigorous analytic processes. Participants were split into three response groups according to their propensity to endorse logically normative conclusions. The low-logic, high belief-bias group demonstrated rapid responding, consistent with heuristic processing. The medium-logic, moderate belief-bias group showed slower responding, consistent with enhanced analytic processing, albeit selectively biased by conclusion believability. The high-logic, low belief-bias group's relatively unbiased responses came at the cost of increased processing times, especially with invalid-believable conclusions. These findings support selective processing claims that distinct heuristic and analytic processing systems underpin reasoning, and indicate that certain individuals differentially engage one system more than the other. A minor amendment is proposed to the current selective processing model to capture the full range of observed effects.

Quantitative Analysis of Primary Phase Morphology in Semi-Solid Alloys Based on LabVIEW and IMAQ Vision

This paper researched on metallographic image analysis of primary phase morphology in semi-solid alloys. The image processing and quantitative analysis system is based on labVIEW and IMAQ Vision. The system uses image processing and analysis technology, such as manual threshold, removing small particles and filling holes processing, edge detection and quantitative analysis of the volume fraction, size and shape of the primary solid. According to the testing results, this system has characteristics of less time-consuming, quick inspection speed and high measurement accuracy, which completely satisfies the requirements.

Constructing a water quality 2.0 OLAP system in Taiwan

Abstract Obtaining water suitable for human consumption is an important issue in both agricultural and industrialized countries. In areas with limited water supplies, water should be carefully managed by all users instead of by only the water agency. Therefore, a water monitoring system should allow interested monitors, such as government economists, researchers and public users, to participate in managing the water quality. However, most water information is distributed in formats that are not convenient for a general holistic analysis. Moreover, interpreting the output of environmental systems involves specialized domain knowledge that is not well understood by the public. How to integrate all of the available data to provide useful knowledge and understandable conclusions to users of different backgrounds is an important issue. This paper presents a water quality 2.0 OLAP system designed for the South Water Resources Bureau (TSWRB) of Taiwan. The concept of Web 2.0 has been adopted to integrate qualified data resources. In addition, an On-Line Analytical Processing (OLAP) system was used to analyze data from distributed resources to increase the understanding of water quality information of non-experts. This system provides a framework for all users to collaborate in monitoring water quality and in protecting limited water resources.

Visualizing and Assessing a Compositional Approach to Service-Oriented Business Process Design Using Unified Modelling Language (UML)

In the context of Service-Oriented Architecture (SOA), complex systems can be realized through the visualization of business driven processes. The automation of Service Supported Systems (SSS) is the future integral part of core SOA which provides preprocessed information and solution suggestions for the Cloud Computing Users (CCU). CCU requires compact and fast decision supporting displays and user interface in order to handle the increasing work load. This requires intelligent, intuitive and robust preprocessing system as a backbone for automation lifecycle management. Complex business management processes often entail complex environmental decision-making procedures. This process can be greatly enhanced if it is based on an exploratory-envisioning system such as Information Exploration and Visualization Environment. Current scientific research has taken advantage of e-science to enhance distributed simulation, analysis and visualization. Many of these infrastructures use one or more collaborative software paradigms like Grid Computing, High Level Architecture (HLA) and Service Oriented Architecture (SOA), which together provide an optimal environment for heterogeneous and distant, real-time collaboration. While significant progress has been made using these collaborative platforms, often there is no particular software suite that fulfils all requirements for an entire organization or case study. End-user must cope manually with a collection of tools and its exporting/importing capabilities to obtain the output needed for a particular purpose. We presents how service oriented architecture can be utilized in automation services support system using RCD framework as underlying composition platform. The introduced framework combines rapid analysis development and intelligent process state visualization for CCU and discusses the challenges met in building reliable cloud computing services for web services. Unified Modeling Language (UML) is used as a specification technique for the system analysis and design process which is the only way to visualize one’s design and check it against requirements before developers start to code.

Dynamic View Management System for Query Prediction to View Materialization

On-Line Analytical Processing (OLAP) systems based on data warehouses are the main systems for managerial decision making and must have a quick response time. Several algorithms have been presented to select the proper set of data and elicit suitable structured environments to handle the queries submitted to OLAP systems, which are called view selection algorithms to materialize. As users’ requirements may change during run time, materialization must be viewed dynamically. In this work, the authors propose and operate a dynamic view management system to select and materialize views with new and improved architecture, which predicts incoming queries through association rule mining and three probabilistic reasoning approaches: Conditional probability, Bayes’ rule, and Naïve Bayes’ rule. The proposed system is compared with DynaMat system and Hybrid system through two standard measures. Experimental results show that the proposed dynamic view selection system improves these measures. This system outperforms DynaMat and Hybrid for each type of query and each sequence of incoming queries.