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Most existing topic models focus either on extracting static topic-sentiment conjunctions or topic-wise evolution over time leaving out topic-sentiment dynamics and missing the opportunity to provide a more in-depth analysis of textual data. In this paper, we propose an LDA-based topic model for analyzing topic-sentiment evolution over time by modeling time jointly with topics and sentiments. We derive...
Missing data cases are a problem in all types of statistical analyses and arise in almost all application domains. Several schemes have been studied in this paper to overcome the drawbacks produced by missing values in data mining tasks, one of the most well known is based on pre processing, formerly known as imputation. In this work, we propose a new multiple imputation approach based on sampling...
Corticomuscular coupling analysis based on multiple datasets such as electroencephalography (EEG) and electromyography (EMG) signals provides a useful tool for understanding human motor control systems. A popular conventional method to assess corticomuscular coupling has been the pair-wise magnitude-squared coherence (MSC) between EEG and concomitant EMG recordings. However, there are certain limitations...
A detailed discussion on contributions from feature attributes to the classifying attribute in the nonlinear classification model based on the Choquet integral is given in this paper. The work provides a new understanding to the geometric structure of the model with contribution rates from the feature attributes towards the classification, as well as the interaction among them.
This paper introduces Copula approach, which has been widely used in statistical field, to the construction of OLAP cubes for the first time. Based on this approach, a novel scheme is proposed to compress data and answer any OLAP query without accessing raw data. The procedure of this scheme can be generally divided into three steps. Firstly, find the proper distribution functions to fit the marginal...
While data mining aims to identify hidden knowledge from massive and high dimensional datasets, the importance of dependence structure among time, space, and between different variables is less emphasized. Analogous to the use of probability density functions in modeling individual variables, it is now possible to characterize the complete dependence space mathematically through the application of...
We describe a system that successfully transfers value function knowledge across multiple subdomains of real-time strategy games in the context of multiagent reinforcement learning. First, we implement an assignment-based decomposition architecture, which decomposes the problem of coordinating multiple agents into the two levels of task assignment and task execution. Second, a hybrid model-based approach...
For multitarget tracking problems, occlusions between targets are quite tough tasks. We present a novel algorithm to solve such problems. For the two targets in occlusions, Fukunaga-Koontz transform is exploited to achieve the projection matrix, with which the two targets are projected into a low dimensional space where they are quite distinguishing. To solve the problem of the change of target appearance,...
This paper presents the mean-square joint state filtering and parameter identification problem for uncertain linear stochastic systems with unknown parameters in both state and observation equations, where the unknown parameters are considered Wiener processes. The original problem is reduced to the filtering problem for an extended state vector that incorporates parameters as additional states. The...
By analyzing the constraint characteristic of each limb which connected the fixed platform with the moving platform of parallel manipulators, the form of limbs can be designed corresponding to certainty kinetic catachrestic form of parallel manipulator. Conventional design method is that one or more actuated joints included in one limb and other joints are passive, then the coefficients of these passive...
We introduce an optimization framework called prioritized optimization control, in which a nested sequence of objectives are optimized so as not to conflict with higher-priority objectives. We focus on the case of quadratic objectives and derive an efficient recursive solver for this case. We show how task-space control can be formulated in this framework, and demonstrate the technique on three sample...
A nonlinear reference shaping method for manipulators which are operated in living environments is proposed. It generates an intermediate reference position, and it is combined with a control based on the virtual spring-damper hypothesis proposed by Arimoto et al. The initial acceleration is moderated by an intermediate reference position inserted between the original target and the current position...
This paper describes a new methodology for designing bilateral controllers based on transparency that applies a modified scheme of control by state of convergence. The design is based on modelling the behavior of the master and slave which regard state space equations, and also taking into account that perfect transparency cannot be reached. This methodology allows designing the controllers in order...
Cooperative relaying transmission is proved to be a feasible method for QoS guaranteed and dead-spot coverage. In this paper, the power and frame allocation schemes are proposed for TDD-based cooperative relaying system. Based on the related work on adaptive frame allocation (FA), the optimal power allocation (PA) is deduced for compress-and-forward (CF) relaying, and the optimal PA and FA schemes...
We consider the problem of jointly estimating the affine transformations of multiple objects from a single noisy observation, where each object is undergoing a different affine transformation. The derived algorithm is employed directly, such that prior segmentation of the observation into the distinct objects is avoided. Explicit expressions recovering the parameters of the transformation of each...
Adaptively monitoring the states of nodes in a large complex network is of interest in domains such as national security, public health, and energy grid management. Here, we present an information theoretic adaptive tracking and sampling framework that recursively selects measurements using the feedback from performing inference on a dynamic Bayesian Network. We also present conditions for the existence...
In this paper appears a behavior analysis of the Mexican stock-market between a previous period to the economic debacle of the 2008 and during the period of the first month of the debacle. We propose to use a mathematical model of linear programming for the selection of an investment portfolio in Mexican stock-market. The mathematical model is based on the modification of Markowitz Model and Capital...
In this article, we propose a SMC based method for estimating the static parameter of a general state space model. The proposed method is based on maximizing the joint likelihood of the observation and unknown state sequence with respect to both the unknown parameters and the unknown state sequence. This in turn, casts the problem into simultaneous estimations of state and parameter. We show the efficacy...
In this paper, tendon-sheath actuated robots working under narrow space are introduced. These kinds of robots are often used to accomplish some rescue tasks, operate minimally invasive surgeries or fulfill some detection mission. The application of tendon-sheath mechanism can reduce the size and weight of the robots. Friction between the tendon and the sheath which introduces some nonlinear phenomenon...
The mathematical model of isometric polygonal curve was analyzed. To predigest the construct of isometric polygonal profile, and the realization on engineering application and the favorable of NC machining being taken into account, the practical isometric polygonal curve was put forward. The mathematical model of practical isometric polygonal was analysed, and the 2D model and solid machining process...
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