Abstract: Process mining provides ways to analyze business
processes. Common process mining techniques consider the process
as a whole. However, in real-life business processes, different
behaviors exist that make the overall process too complex to interpret.
Process comparison is a branch of process mining that isolates
different behaviors of the process from each other by using process
cubes. Process cubes organize event data using different dimensions.
Each cell contains a set of events that can be used as an input to apply
process mining techniques. Existing work on process cubes assume
single case notions. However, in real processes, several case notions
(e.g., order, item, package, etc.) are intertwined. Object-centric
process mining is a new branch of process mining addressing multiple
case notions in a process. To make a bridge between object-centric
process mining and process comparison, we propose a process cube
framework, which supports process cube operations such as slice and
dice on object-centric event logs. To facilitate the comparison, the
framework is integrated with several object-centric process discovery
approaches.
Abstract: A graphenated–polyaniline (GR-PANI) nanocomposite sensor was constructed and used for the determination of anthracene. The direct electro-oxidation behavior of anthracene on the GR-PANI modified glassy carbon electrode (GCE) was used as the sensing principle. The results indicate thatthe response profile of the oxidation of anthracene on GR-PANI-modified GCE provides for the construction of sensor systems based onamperometric and potentiometric signal transductions. A dynamic linear range of 0.12- 100 µM anthracene and a detection limit of 0.044 µM anthracene were established for the sensor system.
Abstract: The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects. Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.
Abstract: This paper discusses the intake of combining multi-criteria
decision analysis (MCDA) with OLAP systems, to generate
an integrated analysis process dealing with complex multi-criteria
decision-making situations. In this context, a multi-agent modeling is
presented for decision support systems by combining multi-criteria
decision analysis (MCDA) with OLAP systems. The proposed
modeling which consists in performing the multi-agent system
(MAS) architecture, procedure and protocol of the negotiation model
is elaborated as a decision support tool for complex decision-making
environments. Our objective is to take advantage from the multi-agent
system which distributes resources and computational
capabilities across interconnected agents, and provide a problem
modeling in terms of autonomous interacting component-agents.
Thus, the identification and evaluation of criteria as well as the
evaluation and ranking of alternatives in a decision support situation
will be performed by organizing tasks and user preferences between
different agents in order to reach the right decision. At the end, an
illustrative example is conducted to demonstrate the function and
effectiveness of our MAS modeling.
Abstract: This paper presents an approach of on-line control of
the state of technosphere and environment objects based on the
integration of Data Warehouse, OLAP and Expert systems
technologies. It looks at the structure and content of data warehouse
that provides consolidation and storage of monitoring data. There is a
description of OLAP-models that provide a multidimensional
analysis of monitoring data and dynamic analysis of principal
parameters of controlled objects. The authors suggest some criteria of
emergency risk assessment using expert knowledge about danger
levels. It is demonstrated now some of the proposed solutions could
be adopted in territorial decision making support systems.
Operational control allows authorities to detect threat, prevent natural
and anthropogenic emergencies and ensure a comprehensive safety of
territory.
Abstract: The separation of Hg (II) from produced water by
hollow fiber contactors (HFC) was investigation. This system
included of two hollow fiber modules in the series connecting. The
first module used for the extraction reaction and the second module
for stripping reaction. Aliquat336 extractant was fed from the organic
reservoirs into the shell side of the first hollow fiber module and
continuous to the shell side of the second module. The organic liquid
was continuously feed recirculate and back to the reservoirs. The feed
solution was pumped into the lumen (tube side) of the first hollow
fiber module. Simultaneously, the stripping solution was pumped in
the same way in tube side of the second module. The feed and
stripping solution was fed which had a countercurrent flow. Samples
were kept in the outlet of feed and stripping solution at 1 hour and
characterized concentration of Hg (II) by Inductively Couple Plasma
Atomic Emission Spectroscopy (ICP-AES). Feed solution was
produced water from natural gulf of Thailand. The extractant was
Aliquat336 dissolved in kerosene diluent. Stripping solution used was
nitric acid (HNO3) and thiourea (NH2CSNH2). The effect of carrier
concentration and type of stripping solution were investigated.
Results showed that the best condition were 10 % (v/v) Aliquat336
and 1.0 M NH2CSNH2. At the optimum condition, the extraction and
stripping of Hg (II) were 98% and 44.2%, respectively.
Abstract: OLAP uses multidimensional structures, to provide
access to data for analysis. Traditionally, OLAP operations are more
focused on retrieving data from a single data mart. An exception is
the drill across operator. This, however, is restricted to retrieving
facts on common dimensions of the multiple data marts. Our concern
is to define further operations while retrieving data from multiple
data marts. Towards this, we have defined six operations which
coalesce data marts. While doing so we consider the common as well
as the non-common dimensions of the data marts.
Abstract: Homogeneous composites of alumina and zirconia
with a small amount of MgO (99%) were obtained for ZTA ceramic containing 0.05 wt% MgO in
1500 °C.
Abstract: Trends in business intelligence, e-commerce and
remote access make it necessary and practical to store data in
different ways on multiple systems with different operating systems.
As business evolve and grow, they require efficient computerized
solution to perform data update and to access data from diverse
enterprise business applications. The objective of this paper is to
demonstrate the capability of DTS [1] as a database solution for
automatic data transfer and update in solving business problem. This
DTS package is developed for the sales of variety of plants and
eventually expanded into commercial supply and landscaping
business. Dimension data modeling is used in DTS package to
extract, transform and load data from heterogeneous database
systems such as MySQL, Microsoft Access and Oracle that
consolidates into a Data Mart residing in SQL Server. Hence, the
data transfer from various databases is scheduled to run automatically
every quarter of the year to review the efficient sales analysis.
Therefore, DTS is absolutely an attractive solution for automatic data
transfer and update which meeting today-s business needs.
Abstract: Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.
Abstract: Decision support systems are usually based on
multidimensional structures which use the concept of hypercube.
Dimensions are the axes on which facts are analyzed and form a
space where a fact is located by a set of coordinates at the
intersections of members of dimensions. Conventional
multidimensional structures deal with discrete facts linked to discrete
dimensions. However, when dealing with natural continuous
phenomena the discrete representation is not adequate. There is a
need to integrate spatiotemporal continuity within multidimensional
structures to enable analysis and exploration of continuous field data.
Research issues that lead to the integration of spatiotemporal
continuity in multidimensional structures are numerous. In this paper,
we discuss research issues related to the integration of continuity in
multidimensional structures, present briefly a multidimensional
model for continuous field data. We also define new aggregation
operations. The model and the associated operations and measures
are validated by a prototype.
Abstract: In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.
Abstract: Typical Intelligent Decision Support System is 4-based, its design composes of Data Warehouse, Online Analytical Processing, Data Mining and Decision Supporting based on models, which is called Decision Support System Based on Data Warehouse (DSSBDW). This way takes ETL,OLAP and DM as its implementing means, and integrates traditional model-driving DSS and data-driving DSS into a whole. For this kind of problem, this paper analyzes the DSSBDW architecture and DW model, and discusses the following key issues: ETL designing and Realization; metadata managing technology using XML; SQL implementing, optimizing performance, data mapping in OLAP; lastly, it illustrates the designing principle and method of DW in DSSBDW.
Abstract: The use of polypropylene mesh devices for Pelvic
Organ Prolapse (POP) spread rapidly during the last decade, yet our
knowledge of the mesh-tissue interaction is far from complete. We
aimed to perform a thorough pathological examination of explanted
POP meshes and describe findings that may explain mechanisms of
complications resulting in product excision. We report a spectrum of
important findings, including nerve ingrowth, mesh deformation,
involvement of detrusor muscle with neural ganglia, and
polypropylene degradation. Analysis of these findings may improve
and guide future treatment strategies.