Abstract: With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.
Abstract: Net fee and commission income is one of the key elements of a bank’s core income. In the current low-interest rate environment, this type of income is gaining importance relative to net interest income. This paper analyses the effects of bank and country specific determinants of net fee and commission income on a set of cooperative banks from European countries in the 2007-2014 period. In order to do that, dynamic panel data methods (system Generalized Methods of Moments) were employed. Subsequently, alternative panel data methods were run as robustness checks of the analysis. Strong positive impact of bank concentration on the share of net fee and commission income was found, which proves that cooperative banks tend to display a higher share of fee income in less competitive markets. This is probably connected with the fact that they stick with their traditional deposit-taking and loan-providing model and fees on these services are driven down by the competitors. Moreover, compared to commercial banks, cooperatives do not expand heavily into non-traditional fee bearing services under competition and their overall fee income share is therefore decreasing with the increased competitiveness of the sector.
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: Governments constantly seek to offer faster, more secure, efficient and effective services for their citizens. Recent changes and developments to communication services and technologies, mainly due the Internet, have led to immense improvements in the way governments of advanced countries carry out their interior operations Therefore, advances in e-government services have been broadly adopted and used in various developed countries, as well as being adapted to developing countries. The implementation of advances depends on the utilization of the most innovative structures of data techniques, mainly in web dependent applications, to enhance the main functions of governments. These functions, in turn, have spread to mobile and wireless techniques, generating a new advanced direction called m-government. This paper discusses a selection of available m-government applications and several business modules and frameworks in various fields. Practically, the m-government models, techniques and methods have become the improved version of e-government. M-government offers the potential for applications which will work better, providing citizens with services utilizing mobile communication and data models incorporating several government entities. Developing countries can benefit greatly from this innovation due to the fact that a large percentage of their population is young and can adapt to new technology and to the fact that mobile computing devices are more affordable. The use of models of mobile transactions encourages effective participation through the use of mobile portals by businesses, various organizations, and individual citizens. Although the application of m-government has great potential, it does have major limitations. The limitations include: the implementation of wireless networks and relative communications, the encouragement of mobile diffusion, the administration of complicated tasks concerning the protection of security (including the ability to offer privacy for information), and the management of the legal issues concerning mobile applications and the utilization of services.
Abstract: Ecological systems are exposed and are influenced by
various natural and anthropogenic disturbances. They produce
various effects and states seeking response symmetry to a state of
global phase coherence or stability and balance of their food webs.
This research project addresses the development of a computational
methodology for modeling plankton food webs. The use of
algorithms to establish connections, the generation of representative
fuzzy multigraphs and application of technical analysis of complex
networks provide a set of tools for defining, analyzing and evaluating
community structure of coastal aquatic ecosystems, beyond the
estimate of possible external impacts to the networks. Thus, this
study aims to develop computational systems and data models to
assess how these ecological networks are structurally and
functionally organized, to analyze the types and degree of
compartmentalization and synchronization between oscillatory and
interconnected elements network and the influence of disturbances on
the overall pattern of rhythmicity of the system.
Abstract: The network designing and data modeling developments which are the two significant research tasks in direction to tolerate power control of Microgrid concluded using IEC 61850 data models and facilities. The current casing areas of IEC 61580 include infrastructures in substation automation systems, among substations and to DERs. So, for LV microgrid power control, previously using the IEC 61850 amenities to control the smart electrical devices, we have to model those devices as IEC 61850 data models and design a network topology to maintenance all-in-one communiqué amid those devices. In adding, though IEC 61850 assists modeling a portion by open-handed several object models for common functions similar measurement, metering, monitoring…etc., there are motionless certain missing smithereens for building a multiplicity of functions for household appliances like tuning the temperature of an electric heater or refrigerator.
Abstract: Nowadays companies strive to survive in a
competitive global environment. To speed up product
development/modifications, it is suggested to adopt a collaborative
product development approach. However, despite the advantages of
new IT improvements still many CAx systems work separately and
locally. Collaborative design and manufacture requires a product
information model that supports related CAx product data models. To
solve this problem many solutions are proposed, which the most
successful one is adopting the STEP standard as a product data model
to develop a collaborative CAx platform. However, the improvement
of the STEP-s Application Protocols (APs) over the time, huge
number of STEP AP-s and cc-s, the high costs of implementation,
costly process for conversion of older CAx software files to the STEP
neutral file format; and lack of STEP knowledge, that usually slows
down the implementation of the STEP standard in collaborative data
exchange, management and integration should be considered. In this
paper the requirements for a successful collaborative CAx system is
discussed. The STEP standard capability for product data integration
and its shortcomings as well as the dominant platforms for supporting
CAx collaboration management and product data integration are
reviewed. Finally a platform named LAYMOD to fulfil the
requirements of CAx collaborative environment and integrating the
product data is proposed. The platform is a layered platform to enable
global collaboration among different CAx software
packages/developers. It also adopts the STEP modular architecture
and the XML data structures to enable collaboration between CAx
software packages as well as overcoming the STEP standard
limitations. The architecture and procedures of LAYMOD platform
to manage collaboration and avoid contradicts in product data
integration are introduced.
Abstract: Selecting the data modeling technique for an
information system is determined by the objective of the resultant
data model. Dimensional modeling is the preferred modeling
technique for data destined for data warehouses and data mining,
presenting data models that ease analysis and queries which are in
contrast with entity relationship modeling. The establishment of data
warehouses as components of information system landscapes in
many organizations has subsequently led to the development of
dimensional modeling. This has been significantly more developed
and reported for the commercial database management systems as
compared to the open sources thereby making it less affordable for
those in resource constrained settings. This paper presents
dimensional modeling of HIV patient information using open source
modeling tools. It aims to take advantage of the fact that the most
affected regions by the HIV virus are also heavily resource
constrained (sub-Saharan Africa) whereas having large quantities of
HIV data. Two HIV data source systems were studied to identify
appropriate dimensions and facts these were then modeled using two
open source dimensional modeling tools. Use of open source would
reduce the software costs for dimensional modeling and in turn make
data warehousing and data mining more feasible even for those in
resource constrained settings but with data available.
Abstract: This paper proposes a framework for product
development including hardware and software components. It
provides separation of hardware dependent software, modifications of
current product development process, and integration of software
modules with existing product configuration models and assembly
product structures. In order to decide the dependent software, the
framework considers product configuration modules and engineering
changes of associated software and hardware components. In order to
support efficient integration of the two different hardware and
software development, a modified product development process is
proposed. The process integrates the dependent software development
into product development through the interchanges of specific product
information. By using existing product data models in Product Data
Management (PDM), the framework represents software as modules
for product configurations and software parts for product structure.
The framework is applied to development of a robot system in order to
show its effectiveness.
Abstract: Smoothing or filtering of data is first preprocessing step
for noise suppression in many applications involving data analysis.
Moving average is the most popular method of smoothing the data,
generalization of this led to the development of Savitzky-Golay filter.
Many window smoothing methods were developed by convolving
the data with different window functions for different applications;
most widely used window functions are Gaussian or Kaiser. Function
approximation of the data by polynomial regression or Fourier
expansion or wavelet expansion also gives a smoothed data. Wavelets
also smooth the data to great extent by thresholding the wavelet
coefficients. Almost all smoothing methods destroys the peaks and
flatten them when the support of the window is increased. In certain
applications it is desirable to retain peaks while smoothing the data
as much as possible. In this paper we present a methodology called
as peak-wise smoothing that will smooth the data to any desired level
without losing the major peak features.
Abstract: In order to assess optical fiber reliability in different environmental and stress conditions series of testing are performed simulating overlapping of chemical and mechanical controlled varying factors. Each series of testing may be compared using statistical processing: i.e. Weibull plots. Due to the numerous data to treat, a software application has appeared useful to interpret selected series of experiments in function of envisaged factors. The current paper presents a software application used in the storage, modelling and interpretation of experimental data gathered from optical fibre testing. The present paper strictly deals with the software part of the project (regarding the modelling, storage and processing of user supplied data).
Abstract: The problem of estimating time-varying regression is
inevitably concerned with the necessity to choose the appropriate
level of model volatility - ranging from the full stationarity of instant
regression models to their absolute independence of each other. In the
stationary case the number of regression coefficients to be estimated
equals that of regressors, whereas the absence of any smoothness
assumptions augments the dimension of the unknown vector by the
factor of the time-series length. The Akaike Information Criterion
is a commonly adopted means of adjusting a model to the given
data set within a succession of nested parametric model classes,
but its crucial restriction is that the classes are rigidly defined by
the growing integer-valued dimension of the unknown vector. To
make the Kullback information maximization principle underlying the
classical AIC applicable to the problem of time-varying regression
estimation, we extend it onto a wider class of data models in which
the dimension of the parameter is fixed, but the freedom of its values
is softly constrained by a family of continuously nested a priori
probability distributions.