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Enterprise Resource Planning (ERP) systems are large scale integrated systems covering most of the business processes of an enterprise. ERP projects differ from software projects with customization, modification, integration and data conversion phases. Most of the time effort and time estimations are performed in an ad-hoc fashion in ERP projects and as a result they frequently suffer from time and...
The mechanism behind collisions between vehicles and pedestrians must be thoroughly studied in order to prevent future traffic accidents. In particular, preventing collisions where pedestrian steps out onto the road from behind an obstruction such as buildings, walls or vehicles is a challenging problem. To tackle this problem, we propose situation dependent topic model (SDTM), a regression model...
Quality prediction performance of recently standardized parametric P.1203 models for real-streaming services: YouTube, Vimeo, Amazon Instant Video and a proprietary DASH-based streaming framework, is analyzed. In particular, a validation database comprising of bitstream traces from aforementioned services is used to evaluate the performance of P.1203 (mode 0 and mode 1) models. It is understood from...
SQL injection is the most common web application vulnerability. The vulnerability can be generated unintentionally by software developer during the development phase. To ensure that all secure coding practices are adopted to prevent the vulnerability. The framework of SQL injection prevention using compiler platform and machine learning is proposed. The machine learning part will be described primarily...
Predicting memory occupancy during the execution of large-scale analytical workloads becomes critical for in-memory databases. In particular, probabilistic performance measures for such systems are of interest, but difficult to model with analytical methods due to the highly variable threading levels in corresponding workloads. Since literature with queueing theoretic background largely ignores the...
Recently, a large number of P2P network financial platforms emerged, market competition is fierce. With the size of platforms and the number of customers increasing, how to effectively manage the users on the platforms has become an urgent problem to be solved for network financial platforms. Also, effective user management will be the key to keeping the competitive advantage. For network financial...
Mechanical rock cutting is the fundamental operation in underground construction and mining industry, representing a stochastic process with complicated relations between its variables. Identification and assessment of the parameters affecting the mechanical rock cutting process set up the basic assumptions not only for control and optimization, but also for assessment of the rock drillability as...
The recent growth of interest for in-memory databases poses the question on whether established prediction methods such as response surfaces and simulation are effective to describe the performance of these systems. In particular, the limited dependence of in-memory technologies on the disk makes methods such as simulation more appealing than in the past, since disks are difficult to simulate. To...
Average diurnal variations of ionospheric profile parameters B0 and B1 in 2009 are studied over Chumphon province, Thailand, and compared those variations with IRI-2012 model. The thickness parameter (B0) and the shape parameter (B1) are two main parameters to compute and depict the F2-layer electron density profile. IRI-2012, the latest version of IRI model, offers three options to provide B0 and...
Financial services companies are concerned with identifying when customers have moved because of customer service and marketing concerns. Knowing when customers have moved can create opportunities for these companies to better market their financial products and provide improved customer service. This paper focuses on identifying features of customers who have moved for the purpose of predicting customer...
Five fully automatic methods for X-ray digital mammogram enhancement based on a fast analytical textural model are presented. These efficient single and double view enhancement methods are based on the underlying two-dimensional adaptive causal autoregressive texture model. The methods locally predict breast tissue texture from single or double view mammograms and enhance breast tissue abnormalities,...
Software cost estimation is the process of predicting effort required to develop a software system. This effort may be in terms of number of hours of work or number of workers. Precise effort estimation with a high grade of reliability is an indispensable part of effectively software management. Software project costs include the cost incurred in all the expenses, i.e. the cost of project from initiation,...
AHP Construct Mining Component (ACMC), which is a new term, is an enhancement of applicable structure for multidimensional and multi-level complex dataflow. ACMC is applied into data mining framework and different processing components with the purpose are improvement on numerous aspects in multiply level. ACMC provides not only an integrated platform to support different processing components with...
This article presents a new method and tools for the development of full neural predictors and controllers, with fixed time horizon, based on static multilayer feedforward networks, when describing backward movements of multi-articulated mobile robots, in the configuration space. The predictors are necessary for robot's assisted tasks and useful to be used as cores in simulators to synthesize and...
As knowledge and rules are hided in e-commerce data, how to mine them is not achieved well in the present e-commerce. IEC (Intelligent E-commerce) is proposed as the next period e-commerce and main feature is to mine e-commerce knowledge and rules from e-commerce data. An Extended K-Means algorithm is proposed to analyze customers' consumptions in the IEC and results indicate that the performance...
A new propagation model and software implementation combines the best of the NTIA-ITS Longley-Rice methodology and it's Irregular Terrain Methodology (ITM) software implementation, a set of deterministic approximation equations derived from the empirical data in ITU-R P.1546 and other ITU Recommendations, and Snell's Law and Beer's Law, to create the first truly point-to-point, terrain-specific international...
In the present paper we present a new approach to the synthesis of filled pauses. The problem is tackled from the point of view of disfluent speech synthesis. Based on the synthetic disfluent speech model, we analyse the features that describe filled pauses and propose a model to predict them. The model was implemented and perceptually evaluated with successful results.
In order to meet the need of local power optimally allocating its cascade hydropower plants, a decision support system for optimal operation of local cascaded hydropower plants is studied and designed out in this paper. The functions of the system include data management, hydrological forecast, long-time optimal operation alternative, short-term optimal operation alternative and daily operation scheming...
Back-propagation neural network model was developed to predict the coal and gas outburst. After trained, the artificial neural network model was used to predict the coal and gas outburst of several samples. Moreover, ANN model was also used to analyse the quantitative effects of influencing factors on the coal and gas outburst. The prediction performance of ANN model is satisfactory. The prediction...
Traffic forecasting is an important task which is required by overload warning and capacity planning for mobile networks. Based on analysis of real data collected by China Mobile Communications Corporation (CMCC) Heilongjiang Co. Ltd, this paper proposes to use the multiplicative seasonal ARIMA models for mobile communication traffic forecasting. Experiments and test results show that the whole solution...
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