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Chloroplasts are organelles in most green plant and some algal cells. Identifying protein subchloroplast localization in chloroplast organelle is very helpful for understanding the function of chloroplast proteins. There have existed a few computational prediction methods for protein subchloroplast localization. However, these existing works have ignored proteins with multiple subchloroplast locations...
There is an important relationship between the stability of protein complex and hot region. Research has shown that in protein-protein interaction (PPI), residues are denser around the hot region. Therefore, this paper proposed an algorithm based on Gi statistics, regional division rule and regional amplification principle to form residue dense region (RDR); Then, according to the results of cascade...
Despite advances in fingerprint matching, partial/incomplete/fragmentary fingerprint recognition remains a challenging task. While miniaturization of fingerprint scanners limits the capture of only part of the fingerprint, there is also special interest in processing latent fingerprints which are likely to be partial and of low quality. Partial fingerprints do not include all the structures available...
This paper presents new methods for the recognition and categorization of object properties such as surface texture, weight, and compliance using a multi-modal artificial skin mounted on both arms of a humanoid. In addition, it introduces two novel feature descriptors, which are useful for providing high-level information to learning algorithms. The artificial skin has built-in 3-axis accelerometer,...
Internet traffic exhibits self-similarity and long-range dependence (LRD). Accurate estimation of statistical parameters characterizing self-similarity and LRD is an important issue, aiming at best modelling traffic e.g. to the purpose of network simulation. Major attention has been devoted to designing algorithms for estimating the Hurst parameter H of LRD traffic series or, more generally, the exponent...
Attention Deficit Hyperactivity Disorder (ADHD) is one of the common diseases of brain and has brought the growth of teenagers and even the adult indelible damage. It is very different to classify the ADHD symptoms and normal by the existing research. In this paper, the contributions are as two aspects: one is that the attributes of brain network of the resting state fMRI data have been calculated...
Detection of Sleep onset is one of complex processes in the area of sleep medicine. The transition from wake state to sleep is termed as sleep onset and is identified using distinct markers like behavioural features, physiological features and changes in EEC Extraction of appropriate features from EEG recordings helps in automated recognition and classification of wake-sleep transition. This research...
This paper presents a computationally efficient Direction-Of-Arrival (DOA) estimation algorithm by Uniform Linear Array (ULA), which is effective for highly-correlated sources but also works for uncorrelated sources. The proposed algorithm is basically based on the relation between the elements of array covariance matrix, does not need eigendecomposition, iteration or angular peak-search, and leads...
Gene selection is one of important research issues in analysis of gene expression data classification. Current methods try to reduce genes by means of statistical calculations and have used semantic similarity under gene ontology. In this article a technique has been presented based on which in addition to considering biological relation among genes, redundant genes by means of hierarchical clustering...
Vector flow imaging is a critical component in the clinical diagnosis of cardiovascular diseases; however, most current methods are too computationally expensive to scale well to 3D. Less complex techniques, such as Doppler-based imaging (which cannot provide lateral flow measurements) and basic speckle tracking algorithms (which have poor lateral accuracy), are incapable of producing high quality...
A wireless local area network infrastructure, consisting of a couple of tens of access points exists in each office building, university or even block of flats. These can be used for indoor localization purposes without interfering with network activities. In this paper a correlation based method for indoor localization is presented. No specific infrastructure is needed except for the existing wireless...
Stochastic computing (SC) is an approximate computing technique that represents data by probabilistic bit-streams called stochastic numbers (SNs). Arithmetic operations can be implemented at very low cost by means of SC. To achieve acceptable accuracy, interacting SNs must usually be statistically independent or uncorrelated. Correlation is poorly understood, however, and is a key problem in SC because...
In addition to provide charging service, Electric Vehicle (EV) charging station equipped with distributed energy storage system can also participate in the deregulate market to optimize the cost of operation. To support this function, it is necessary to achieve sufficient accuracy on the forecasting of energy resources and market prices. The deregulated market price prediction presents challenges...
In order to prevent the financial risks of enterprises effectively, the risks evaluation is of great importance. This paper analyses the main factors that affect enterprise financial risks by using the T-test and nonparametric test in statistical software SPSS15.0 and the gray relevance theory (GRA). These factors are considered as the input variables of BP neural network and 56 enterprises are selected...
With shorter calibration times and higher information transfer rates, steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have been studied most activity in recent years. Target identification is the ongoing core task in BCI researches, and plays a significant role in practical applications. In order to improve the performance of SSVEP-based BCI system, we proposed...
In this paper, methods to improve a practical Time Difference of Arrival (TDOA) based source localization system are investigated. Firstly, our previous work on the development of a TDOA based source localization system using reconfigurable Software Defined Radios (SDRs) is described in detail. The system can achieve less than 100m error in a coverage of several kilometers. However, the performance...
This paper investigates the design criteria for an ultrasound positioning system used in smart tool applications. A novel range-finding system based upon low cost, ease of implementation, and an automatic gain controller (AGC) is developed. We also design several signal processing algorithms for this system, including an amplitude threshold method (ATM), a frequency threshold method (FTM), and a cross...
Prior works have been elaborated on activity inferences from context information sensed on smart phones. Most of sensing computations are performed on CPU of smart phones. Thus, Sensor Hub is designed to avoid CPU involvement. However, Sensor Hub has several limitations, such as limited memory space and computation power. Since activity inference is a classification problem, prior works have already...
Random forests have been used as effective models to tackle a number of classification and regression problems. In this paper, we present a new type of Random Forests (RFs) called Red(uced)-RF that adopts a new voting mechanism called Priority Vote Weighting (PV) and a new dynamic data reduction principle which improve accuracy and execution time compared to Breiman's conventional RF. Red-RF also...
The ionospheric total electron content (TEC) is an important ionospheric parameters, Research of it has important significance on communication, radar, spaceflight, GNSS and other domains. Traditional short-term forecast model of ionospheric TEC uses single model so as to affects the prediction precision. A combination model based on seasonal model and ARMA model was put forward to overcome the shortages...
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