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An effective knowledge representation has always proved its importance for mankind intelligence. Among various kinds of knowledge, declarative knowledge has a vital role in medical domain and is critical for health-care safety and quality. A large volume of declarative knowledge is hidden in multiple knowledge resources such as clinical notes, standard guidelines etc. that can play an important role...
Social networks are highly dynamic objects; they grow and change quickly over time through the addition of new edges, signifying the appearance of new interactions in the underlying social structure. In present online social networks have become necessary communication tools in peoples' daily life. Links prediction of social network can not only recommend future friends to a user, but also can predict...
Face recognition is one of the most natural biometrics identification approaches. But the accuracy of face recognition is significantly influenced by poses, facial expressions, and lighting conditions. This paper presents a novel robust facial recognition system by incorporating color information into a modified active shape model (ASM). The selected robust geometric and chromatic information of facial...
Total knee arthroplasty (TKA) is one of the common knee surgeries. Because there are some types of TKA implant, it is hard to select appropriate type of TKA implant for individual patient. For the sake of pre-operative planning, this study presents a novel approach, which predicts post-operative implanted knee function of individuals. It is based on a clinical big data analysis. The big data is composed...
In this paper, we proposed the human action recognition method using the variational Bayesian HMM with Gaussian — Wishart emission mixture model. First, we defined the Bayesian HMM based on a finite number of Gaussian-Wishart mixture components to support continuous emission observations. Second, we have considered a variational Bayesian inference method to derive the posterior distributions for hidden...
Attribute reduction is one of the key issues for data preprocess in data mining. Many heuristic attribute reduction algorithms based on discernibility matrix have been proposed for inconsistent decision tables. However, these methods are usually computationally time-consuming. To address this issue, the derived consistent decision tables are defined for different definitions of relative reducts. The...
Decision-theoretic rough set model interprets the parameters of existing probabilistic rough sets by introducing Bayesian theory to minimize the risks of classification. It is a representative probabilistic rough set model. As an important extension of decision-theoretic rough set model, fuzzy decision-theoretic rough set model can deal with numerical data directly. To investigate the attribute reduction...
Nowadays, drivers cannot avoid bumpy roads because of unfamiliarity with traffic conditions, and poor visibility may cause traffic accidents. Therefore, the state of the roadways and driving safety are important topics. In this paper, the main experimental equipment is a golf cart equipped with a webcam, laser range finder, inertial measurement unit (IMU) and real-time kinematics differential global...
Collaborative filtering is one of the most popular recommendation techniques which makes recommendations to a user based on other users with similar tastes (i.e. neighbors) to the target user. Although most of existing similarity measure between users are symmetry, a user with less uncommonly rated items is able to provide more accurate recommendation to another user. Therefore, the contribution on...
In many scenarios, a persons behavior in office environment needs to be monitored and some predefined abnormal actions or activities should be detected and recognized. In this paper, we attempted towards the solution starting from a persons pose with poselets as the basic building blocks. The existed powerful pose representation, i.e., poselets, together with deep convolutional neural networks, are...
In this paper, aimed at the neutral-point potential unbalance of the three-level neutral point clamped inverter, an improved new control scheme about neutral-point potential balance was proposed and a simplified direct torque prediction scheme was used for induction motor fed by three-level inverter. Firstly, stator voltage vectors to be applied at the next time was preselected by the torque prediction...
Scrum process is methodology for software development. Members in a scrum team have self-organizing team by planning and sharing knowledge. This paper introduces optimization algorithm using the population as scrum team doing the scrum process to find an optimum solution. The proposed algorithm maintains the level of exploration and the exploitation search by specific of the scrum-team. The experiment...
It has been established that it is possible to reveal human emotions using electroencephalogram (EEG) signals. Most studies used a wide variety of data sets and methods, therefore a comparison between the performances of their approaches is difficult. This paper reports a study on the effects of the number of electrode channels and frequency bands for emotion classification based on a database for...
High accuracy segmentation of the retinal hemorrhage in fundus is a foundation for ophthalmology-related diagnosis and evaluation. However, it is a challenging task to segment the retinal hemorrhage accurately. This paper proposes a scheme to segment the hemorrhage accurately. Firstly, a non-linear enhancement was used to balance the non-uniform of background that induced by light during imaging....
To solve the problem of poor robustness and low effectiveness of visual tracking in complex scenes, a novel target tracking algorithm based on adaptive observation weight is proposed in this paper. First of all, a weighted observation model is established by linear visual tracking representation. Then an iterative optimization algorithm is proposed to obtain the parameters of the model, and adaptively...
With the rapid development of machine-learning and data-mining techniques, biclustering (co-clustering) has become an important and widespread technique in multiple areas such as gene expression analysis, text mining and market segmentation. In this work, we proposed an efficient co-clustering method named SVD-based hybrid pattern search (SHPS). It is a score-function-based method, and specifically...
Analytic Hierarchy Process is a popular decision tool that ranks the aggregated results from prioritizing the pairwise reciprocal matrices judged by the users. Saaty's Eigen method for prioritizing pairwise reciprocal matrix leads to the possibility of rank reversal, and is still one of the unsettled issues, although many applications of this method have been made. This study proposes the genetic...
In clinical examinations, acoustic methods are non-invasive and inexpensive diagnostic tools for the assessment of aortic and vascular stenosis or occlusion. To ensure the early detection of a dysfunctional arteriovenous access (AVA), we developed a monitoring interface by using phonoangiography (PCG) techniques to examine stenosis among hemodialysis patients. AVAs are vital lines for hemodialysis...
There are two main areas in saliency detection: fixation prediction and salient object detection. Researchers always use bottom-up low-level features and straightforward rules for salient object detection. However these rules are unreliable in common scenes. As a result, most salient object detection technologies can gain a fine performance in limited situation. While in a more complex scene (such...
In search engine advertising, the right selection of keywords is one of the most important step to maximize the advertisers' profitability. Keyword suggestion methodologies are used to map the advertisers selection of keywords and the recent popular queries using statistical data. In this project we are trying to classify the search queries into relevant and non-relevant. In other words, we are trying...
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