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User interest mining is widely used in the fields of personalized search and personalized recommendation. Traditional methods ignore the formation of user interest which is a process that evolves over time. This leads to the inability to accurately describe the distribution of user interest. In this paper, we propose the interest tracking model (ITM). To add the timing, ITM uses Dirichlet distribution and multinomial distribution to describe the evolutional process of interest topics and frequent patterns, which well adapts to the evolution of user interest hidden in short texts between different time slices. In addition, it is well known that user interest is composed of long-term interest and situational interest including short-term interest and social hot topics. State-of-the-art methods simply regard the users' long-term interest as the users' final interest, which makes those unable to completely describe the user interest distribution. To solve this problem, we propose the deformable interest model (DIM) which designs an objective function to combine users' long-term interest and situational interest and more comprehensively and accurately mine user interest. Furthermore, we present the degree of deformation which measures the subinterest's degree of influence on final interest and propose in DIM the influence real-time update mechanism. The mechanism adaptively updates the degree of deformation through the linear iteration and reduces the degree of dependence of the interest model on training sets. We present results via a dataset consisting of Flickr users and their uploaded information in three months, a dataset consisting of Twitter users and their tweets in three months, and a dataset consisting of Instagram users and their uploaded information in three months, showing that the perplexity is reduced to 0.378, the average accuracy is increased to 94%, and the average NMI is increased to 0.20, which prove better interest prediction. [ABSTRACT FROM AUTHOR]

SUMMARY Motors are widely utilized in industry. When the mechanical load oscillates, a motor injects interharmonic currents to the grid and becomes an interharmonic source. The interharmonic currents have an important impact on power quality. This paper, respectively, presents the spectrum of the stator interharmonic currents of the induction and synchronous motors. The mathematical models of both motors, which are nonlinear when the load torque oscillates, are linearized. Then, the spectrum expressions of the interharmonic currents of the two types of motors are derived, respectively. On this basis, the relationship between load torque oscillations and the spectrum of the stator interharmonic currents is analyzed. The effect of the various induction motor steady output powers on the spectrum of the interharmonics is investigated. Simulation results validate the theoretical analysis. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

It is critical for microwave ablation (MWA) treatment planning to evaluate the changes of thermal coagulation zones. In MWA procedures, the shapes and sizes of thermal coagulation zones are gradually evolving over time. To this end, a novel characterization and mapping method of thermal coagulation zones is presented in this article. Firstly, finite element method (FEM) models of temperature distributions for 40, 45, 50, 55, and 60 W microwave ablations were built to derive thermal ablation data of ex vivo porcine livers and were compared with experimental results. Secondly, growth models of characteristic lengths were fitted. Finally, characterization functions of thermal coagulation zones were developed using these growth models. In addition, shape variation factors were incorporated to handle the minor shape variations of thermal coagulation zones. Experimental results showed that these characterization functions could accurately represent the changes of thermal coagulation zones. The standard deviations between prediction results and simulated values were less than 1 mm. The comparative results were statistically analyzed by paired t test (P > 0.05), indicating no significant differences. The proposed method can simply and effectively predict the changes of MWA coagulation zones with time, thus providing reliable coagulation dimensions for the thermal ablation therapies. [ABSTRACT FROM AUTHOR]

Temperature predictions of microwave ablation (MWA) are currently restricted by the specific temperature‐dependent data of tissue characteristic parameters. To address this issue, a new parameter feedback method based on temperature simulations and single‐thermometry measurements was presented. Experimental data of 2450‐MHz microwave antenna was obtained from ex vivo porcine livers. A temperature distribution model was constructed, and the contributions of characteristic parameters were acquired by the sensitivity analysis method. Subsequently, parameter feedbacks were conducted based on a minimization of the errors between numerical data and single‐thermometry measurements. The temperature distribution model was then optimized using the feedback parameters. Finally, temperature measurements were compared with simulation data to validate the accuracy of the model. According to the temperature distribution model with parameter feedback, the averages of maximum error, average error, as well as SD between the simulation temperatures and the measurements were 2.952, 1.323, and 0.852°C, respectively. The simulated and measured temperature changes were generally in good agreement. The proposed method can be useful in MWA temperature simulations to improve temperature prediction accuracy. [ABSTRACT FROM AUTHOR]

Summary: An improved dynamic power flow (DPF) model considering governor nonlinearity is presented. The proposed DPF model is intended for the analysis of post‐contingency power flow after primary frequency regulation. During the regulation process, the governors play an important role while it is difficult to involve the nonlinear segments in the static method. So in this paper, the governor model with amplitude‐limit and deadband is simplified and included in DPF model. Using the describing function method, the effect of deadband is equivalent to an increment of regulation coefficient. The amplitude‐limit is handled by iterative correction. Applying the algorithm to a three‐node system, a case study of load variation proves the effectiveness of the algorithm. Simulations on a practical grid in southern China further demonstrates the practicability and applicability. The algorithm enhances the accuracy of post‐contingency power flow analysis and provides effective analysis for the static security of power system. [ABSTRACT FROM AUTHOR]

Summary: The frequency stability of power system is usually jeopardized by the active power deficit for major disturbances. To deal with these events, adaptive load shedding schemes are effective, and the steady frequency prediction is considered as the prerequisite. However, none of previous predictive methods has taken into consideration the nonlinear segment that may distort system frequency response. This paper investigates the effect of speed governor deadband and presents a method to evaluate its effect on the steady frequency. Based on the wide area measurement system measurements, a predictive algorithm of steady frequency is studied. It utilizes the modified regulation coefficient to consider the governor deadband effect and employs instantaneous measurements of postdisturbance to calculate the steady frequency directly. Simulations on the IEEE‐9 system and a practical system of China have solidified the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

We performed an epidemiological investigation of subjects with premenstrual dysphoric disorder (PMDD) to identify the clinical distribution of the major syndromes and symptoms. The pathogenesis of PMDD mainly involves the dysfunction of liver conveyance and dispersion. Excessive liver conveyance and dispersion are associated with liver-qi invasion syndrome, while insufficient liver conveyance and dispersion are expressed as liver-qi depression syndrome. Additionally, a nonconditional logistic regression was performed to analyze the symptomatic features of liver-qi invasion and liver-qi depression. As a result of this analysis, two subtypes of PMDD are proposed, namely, excessive liver conveyance and dispersion (liver-qi invasion syndrome) and insufficient liver conveyance and dispersion (liver-qi depression syndrome). Our findings provide an epidemiological foundation for the clinical diagnosis and treatment of PMDD based on the identification of different types. [ABSTRACT FROM AUTHOR]