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In this work, based on least squares support vector machine regression, a model that characterizes the relationship between constituents of Baikal skullcap root and therapeutic index of anti-respiratory syncytial virus was established. The computational simulation showed that this model fits well with the experimental data, and validation experimental results also supported the theoretical predictions.
Application of clustering algorithms for investigating real life data has concerned many researchers and vague approaches or their hybridization with other analogous approaches has gained special attention due to their great effectiveness. Recently, rough intuitionistic fuzzy c-means algorithm has been proposed by Tripathy et al [3] and they established its supremacy over all other algorithms contained...
In this paper we investigate static memory access predictability in GPGPU workloads, at the thread block granularity. We first show that a significant share of accessed memory addresses can be predicted using thread block identifiers. We build on this observation and introduce a hardware-software prefetching scheme to reduce average memory access time. Our proposed scheme issues the memory requests...
A novel fuzzy clustering algorithm is presented in this paper, which removes the constraints generally imposed to the cluster shape when a given model is adopted for membership functions. An on-line, sequential procedure is proposed where the cluster determination is performed by using suited membership functions based on geometrically unconstrained kernels and a point-to-shape distance evaluation...
Understanding Operating System behavior is very critical for any embedded designer to make informed design decision. We present a new logging method which can capture the high granular details of the kernel activity. It reduces the logging latency by 95–97% & logging memory usage by 70% compared to conventional “printk”. We utilize the string literal pool of the Linux kernel to reconstruct the...
This article builds the system of comprehensive evaluation index system for transformer substation address selection with the analysis of Huadian project for power transmission and transformation, due to the comprehensive evaluation of power transmission and transformation project involving multiple factors, analytic hierarchy process (AHP) is used to determine the weight of each evaluation index...
Normalized Difference Vegetation Index (NDVI) is one of the most widely used vegetation indexes because the NDVI of typical type of land coverage has a clear distinction on a large-scale image, especially has a valid highlight for vegetation. Anisotropic reflectance characteristics of natural land surface affect the retrieval of NDVI, which means the variation of solar zenith angle and view zenith...
Essential genes play vital roles in bacterial survival and they are potential antimicrobial targets and cornerstones of synthetic biology. Accurate recognition of bacterial essential genes by computational methods becomes necessary because of high economical and time consumption in wet experiments. In this paper, we evaluated the effectiveness of four machine learning methods that are Support Vector...
This work makes two major contributions to architectural support for the debugging of memory related bugs. First, it proposes a novel framework for detecting memory related bugs, where the application can be selective, can be extended to kernel modules, and is based on the virtual memory simulation of the application in hand. Secondly, we have tried to formalize the code instrumentation given our...
Identifying spatial patterns of geographic entities such as retail stores is important in city for understanding how they behave. The pattern formed by the distribution of points can be measured by some quantitative methods. In Big Data era, the data sets for spatial patterns analysis are various including traditional street network data and points of interest (POIs) data in LBS (Location based services)...
Compressed sparse row (CSR) is a frequently used format for sparse matrix storage. However, the state-of-the-art CSR-based sparse matrix-vector multiplication (SpMV) implementations on CUDA-enabled GPUs do not exhibit very high efficiency. This has motivated the development of some alternative storage formats for GPU computing. Unfortunately, these alternatives are incompatible with most CPU-centric...
The following paper proposes a set of novel feature selection criteria that can be applied to kernel Principal Component Analysis (kPCA) outcome to derive discriminative feature spaces for complex classification problems, such as biometric recognition tasks. The proposed class-separation criteria that are used to evaluate distributions of samples, which are projected onto nonlinear most discriminative...
Retinal blood vessels damaged from diabetic retinopathy can cause vision loss. Diabetic Retinopathy (DR) detection, poor quality retinal image makes more difficult the analysis for ophthalmologist. In this paper presents a new automatic method of blood vessels extraction with a real time process using optimized matched filter with minimum cross entropy threshold. Minimum cross entropy threshold is...
As robots continue to create long-term maps, the amount of information that they need to handle increases over time. In terms of place recognition, this implies that the number of images being considered may increase until exceeding the computational resources of the robot. In this paper we consider a scenario where, given multiple independent large maps, possibly from different cities or locations,...
Reduced interference distributions are well-known methods used for quadratic time-frequency signal analysis of nonstationary data including Doppler signals. These distributions use kernels that determine the quality of a time-frequency signal representation. Optimal reduced interference distribution kernels are determined based on the employed design criteria, including sparsity and concentration...
The aims of this paper are to find algebraic characterizations of Schreier loops and explore the limits of the non-associative generalization of the theory of Schreier extensions. A loop can have Schreier decomposition with respect to a normal subgroup if and only if the subgroup is the middle and right nuclear. In this case the conjugation by elements of the loop induces inner automorphisms on the...
Taking full advantage of SIMD instructions in C programs still requires tedious and non-portable programming using intrinsics, despite considerable efforts spent developing auto-vectorization capabilities in recent decades. Whole Function Vectorization (WFV) is a recent technique for extending the use of SIMD across entire functions. WFV has so far only been used in data-parallel languages such as...
In this paper nonlinear filtering and identification based on finite support Volterra models is considered. A set of primary signals, defined in terms of the input signal, serve for the efficient mapping of the nonlinear process to an equivalent multichannel format. An efficient order recursive method is presented for the determination of the Volterra model structure. The efficiency of the proposed...
Localization of epileptic focus and motor regions, is presented in the paper using raw referential EEG data from database http://eeg.pl/epi of Warsaw Memorial Child Hospital. The study is carried out on two patients named CHIMIC and JANPRZ who were diagnosed with drug-resistant epilepsy and were subsequently operated. Along with EEG recordings, inter-ictal discharges, magnetic resonance imaging (MRI)...
We introduce Combined Multiple Image Filter (CMIF) as a new approach for noise removal. The processed output is the Bayesian mean square error estimate of the original image. A set of four filters are selected to improve the quality of noisy image that contains regions with different characteristics. Feature vectors are computed at each pixel in order to predict the performance of the filters in estimating...
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