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A promising solution to reduce the testing costs of analog/RF circuits is the alternate test strategy, which permits to replace costly specification measurements by simple low-cost indirect measurements. This approach has been widely explored and demonstrated in the literature on various case studies over the past twenty years. However it is clear that the efficiency of this strategy strongly depends...
The long-term reproducibility of the platform inertial navigation system (PINS) is key parameter to evaluate whether the comprehensive performance of PINS has met the navigation accuracy. Under the conditions of given standard trajectory parameters, PINS navigation error model can accurately describe the propagation relationship between each individual performance parameter of the PINS and comprehensive...
<?Pub Dtl?>This paper proposes the use of two indicators of the predictability of the load series along with an accuracy value such as mean average percentage error as standard measures of load forecasting performance. Over the last 10 years, there has been a significant increase in load forecasting models proposed in engineering journals. Most of these models provide a description of the inner...
Today's storage systems and database systems are highly complex and configurable, which makes storage management intricate and costly. One critical aspect of storage management, particularly in large storage infrastructures (e.g. cloud storage), is to determine which application data sets to store on which devices. With a mechanism which has the ability to predict the performance of the storage device...
Letter-to-Sound(LTS) conversion, which is used to compress the lexicon for embedded application purpose, has become an important part in Text-to-Speech (TTS) system. In this paper, coupled Hidden Markov Models (CHMM) for LTS conversion is proposed. In the phase of preprocessing, many-to-many alignment is adopted for lexicon alignment instead of one-to-one alignment which is commonly used in previous...
This paper presents an alternate test implementation based on model redundancy that permits to achieve lower prediction errors than a classical implementation, even if training is performed over a small set of devices. The idea is to build different regression models for each specification during the training phase, and then to verify prediction consistency between the different models during the...
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...
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...
Rapidly and accurately estimating the impact of design decisions on performance metrics is critical to both the manual and automated design of wireless sensor networks. Estimating system-level performance metrics such as lifetime, data loss rate, and network connectivity is particularly challenging because they depend on many factors, including network design and structure, hardware characteristics,...
Supplier performance evaluation is a key issue of supply chain and is complicated since a variety of attributes must be considered. In this article, an integrated DEA-NN model is proposed. By taking advantages from both data envelopment analysis (DEA) and neural networks (NN), an application of the integrated DEA-NN method is given. The results indicate that the method is effective and applicable.
Many techniques have been developed to accelerate micro-architecture simulation since it is becoming increasingly urgent as the complexity of workloads and simulated processors increases. However, most of popular techniques need profiles or trial simulations to determine parameters before real simulations. When the number of dynamic instructions of workloads such as SPEC CPU2006 is huge, the profiles...
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...
This paper quantitatively studies the trace effects to the performance and accuracy of the BigSim Emulator, a scalable parallel emulator for large-scale computers. To assess the accuracy effect we modify the emulator code to collect the predicted computation time. Four MPI programs with different computation to communication ratios are used as benchmarks. The emulation time and the predicted computation...
This paper performs an experiment to forecast stock market movement in India using Artificial Neural Network (ANN) tools and a comparative study is made for selected stock indices to find the optimal selection of parameters in ANN approach. Our objective is to apply the ANN applications in financial market prediction to check whether ANN models add value and may be worthwhile to undertake a research...
As the size of today's supercomputers grow exponentially in numbers of processors, the applications that run on these systems scale to larger processor counts. The majority of these applications commonly use Message Passing Interface (MPI); a trace of these MPI communication events is an important input to the tools that visualize, simulate for performance modeling, or enable tuning of parallel applications...
In order to meet the increasing demands of present and upcoming data-intensive computer applications, there has been a major shift in the disk subsystem, which now consists of more disks with higher storage capacities and higher rotational speeds. These have made the disk subsystem a major consumer of power, making disk power management an important issue. People have considered the option of spinning...
In order to evaluate the performance and choose combining forecast method, the paper uses two single forecasting methods, namely BP neural networks and support vector machines (SVM), to forecast the Shanghai Industrial Index, the Shanghai Commercial Index, the Shanghai Real Estate Index and the Shanghai Public Utilities Index. Then it uses BP neural-based combining forecast model and SVM-based combining...
Computer manufacturers spend a huge amount of time, resources, and money in designing new systems and newer configurations, and their ability to reduce costs, charge competitive prices, and gain market share depends on how good these systems perform. In this work, we concentrate on both the system design and the architectural design processes for parallel computers and develop methods to expedite...
Online auction is popular due to the flexibility and convenience it offers to consumers. Variety of items is put up for sale due to the high demands from users in the e-market. Each item has a reserve price which is the minimum price seller is willing to accept and agree to sell. The reserve price plays an important role in determining how much profit sellers stand to gain. A low price setting will...
This document presents a compilation of results from tests performed by iRoC Technologies on SER induced by alpha particles on SRAM memories for technology nodes from 180 nm to 65 nm. The aim of this study is to establish the variation of sensitivity with technology node for SEU and MCU, and to analyze the possible influence of different designs and technological parameters at a given technology node.
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