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To serve large user populations, autonomous intervention systems (i.e. intelligent agents) are being developed to play more active roles such as fitness coaches and clinical disease prevention aids. Although generic user models have been developed, users may require extensive individualization to meet their personal needs. Machine learning techniques may be applied to learn tailored intervention policies...
In this paper we present a HAZOP Assistant based on D-higraphs and dedicated to a functional modeling technique that gathers functional and structural information of the process under study. The Assistant and the methodology are presented and applied to a High Density Polyethylene reactor part of the CP2K plant situated in the petrochemical platform of Skikda.
Most stereoscopic 3D (S3D) image visual discomfort predictors use the Support Vector Regressor (SVR) as the regression model. However, there are other good regression models such as the Random Forests (RF) and Gradient Boost Regression Tree (GBRT). Here we study the efficacy of these regression models for S3D image visual discomfort prediction. We deployed several regression models to predict the...
Systems reliability evaluation is an important task in industry. In fact, reliability indices suggest information about equipments quality level, maintenance and investments. Reliability performances can be estimated in different ways. Most used methods are reliability prediction models. In spite of their diffusion, their applications and results are often discussed, since each of them provides a...
Predicting and analyzing runtime performance characteristics is a vital step in the development process of parallel discrete event simulations. For instance, model developers need to identify and eliminate performance bottlenecks within a simulation model in order to derive a model structure that aids parallel execution. Similarly, developers of parallel simulation frameworks require means of assessing...
Storage device performance prediction is a critical element of self-managed storage systems and application planning tasks, such as data assignment and configuration. We proposed a new hybrid method (RT-RBF), which combines regression tree (RT) and radial-based functions network(RBF), to model storage device performance. In our proposed algorithm, the RT is firstly used to split the large space of...
The listed companies will be specially treated when their business performance is bad or there are serious accidents, which is a rule to reveal the investment risk of stock market. So it is very important to study the performance of listed companies under special treatment (ST companies) for the development of stock market in China. We choose 50 companies as the samples in the ST plate of 2006 in...
There is a wide gap between the potential performance of NAND flash-based solid state drives (SSDs) and their performance in many real-world applications; understanding this gap requires knowledge of their behavior and internal algorithms for various workloads. We develop analytic models for two commonly-used Flash Translation Layer (FTL) algorithms, as used in SSDs, as well as a methodology for applying...
The proposed research is aimed at enhancing system design productivity by exploiting the principle of “design and reuse” to its full potential. Specifically, we present a statistical model for selecting from a component library the optimal components for a network-on-chip architecture such that to satisfy certain system performance requirements. Our model is based on regression analysis and Taguchi's...
This paper evaluates the relationship between Roadway Design (Geometric Parameters) and Flow Characteristics under variance range of volume at the weaving area of conventional roundabout. A weaving section of roundabout was investigated and collected from the traffic video recording devices. Previously, the data capture and reduction was made and regressions analysis of data transformation is used...
This work presents a SystemC-based simulation approach for fast performance analysis of parallel software components, using source code annotated with low-level timing properties. In contrast to other source-level approaches for performance analysis, timing attributes obtained from binary code can be annotated even if compiler optimizations are used without requiring changes in the compiler. To consider...
High Performance Computing (HPC) system need to be coupled with efficient parallel file systems, such as Lustre file system, that can deliver commensurate IO throughput to scientific applications. It is important to gain insights into the deliverable parallel file system IO efficiency. In order to gain a good understanding on what and how to impact the performance of parallel file systems. This paper...
Virtual experiment is an approach to utilize numerical computation to study the complex physics processes, and is used widely in the areas of weapon system development and performance evaluation. The virtual experiment for warhead aims at studying various conditions of damage on target by warhead, analyzing the factors of warhead power, and provide the basis for the warhead design, with high quality...
Flash-based Solid-State Drives (SSDs) have become a promising alternative to magnetic Hard Disk Drives (HDDs) thanks to the large improvements in performance, power consumption, and shock resistance. An accurate SSD performance model will provide the important research tools for exploring the design space of flash-based storage systems. While many HDD performance models have been developed, architectural...
The product development phase of a single processor design from inception till production is an extremely long process taking up to ~4 years per cycle. Along the way, numerous tools have been developed for pre-silicon performance prediction in order to forecast the yield, power and frequency of the product. These data are critical in order for product and resource planning to be carried out efficiently...
A challenging issue in performance evaluation of parallel storage systems through trace-driven simulation is to accurately characterize and emulate I/O behaviors in real applications. The correlation study of inter-arrival times between I/O requests, with an emphasis on I/O-intensive scientific applications, shows the necessity to further study the self-similarity of parallel I/O arrivals. This paper...
Predicting how well applications may run on modern systems is becoming increasingly challenging. It is no longer sufficient to look at number of floating point operations and communication costs, but one also needs to model the underlying systems and how their topology, heterogeneity, system loads, etc, may impact performance. This work focuses on developing a practical model for heterogeneous computing...
Predicting application performance for any hardware change is challenging as multiple factors like environment, application architecture, workload etc also need to be considered. Industry benchmarks that provide means to compare hardware performance however lack in giving insight into the applications' service levels. LQN models help in performance analysis of multi-tiered, distributed applications;...
Performance trade-offs between fast data access by local data replication and cache capacity maximization by global data sharing have been extensively studied for many-core Chip Multiprocessors (CMPs). Costly simulations over a wide spectrum of the design space are generally required to gain insight for a sound design. To lower the cost, we develop an abstract model for understanding the performance...
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