51 research outputs found

    Learning Tree-based Deep Model for Recommender Systems

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    Model-based methods for recommender systems have been studied extensively in recent years. In systems with large corpus, however, the calculation cost for the learnt model to predict all user-item preferences is tremendous, which makes full corpus retrieval extremely difficult. To overcome the calculation barriers, models such as matrix factorization resort to inner product form (i.e., model user-item preference as the inner product of user, item latent factors) and indexes to facilitate efficient approximate k-nearest neighbor searches. However, it still remains challenging to incorporate more expressive interaction forms between user and item features, e.g., interactions through deep neural networks, because of the calculation cost. In this paper, we focus on the problem of introducing arbitrary advanced models to recommender systems with large corpus. We propose a novel tree-based method which can provide logarithmic complexity w.r.t. corpus size even with more expressive models such as deep neural networks. Our main idea is to predict user interests from coarse to fine by traversing tree nodes in a top-down fashion and making decisions for each user-node pair. We also show that the tree structure can be jointly learnt towards better compatibility with users' interest distribution and hence facilitate both training and prediction. Experimental evaluations with two large-scale real-world datasets show that the proposed method significantly outperforms traditional methods. Online A/B test results in Taobao display advertising platform also demonstrate the effectiveness of the proposed method in production environments.Comment: Accepted by KDD 201

    Load regulation application of university campus based on solar power generation forecasting

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    For a solar photovoltaic power system on a university campus, the electricity generated by the system meets the campus load, and the extra electricity is delivered to the grid. Generally, the price of the photovoltaic system is cheaper than that of the utility power system. The full use of solar electricity can reduce the electricity cost of the school. The deep belief network is used to predict solar photovoltaic generation and electricity load, and the gap is found. According to the gap, the power loads on the campus are adjusted to improve the utilization rate of solar power generation. Through the practical application of Changqing Campus of Qilu University of Technology in China, it is found that the utilization rate of solar photovoltaic power generation effectively improved from 91.24% in 2017 to 98.16% in 2019, and the annual electricity is saved by 68 610 yuan (in 2019)

    Analysis of Microbial Communities in Three Rounds of High-temperature Daqu Using Metagenomic Technology

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    Metagenomic sequencing technology was used to analyze the microbial community structures and functional composition in three rounds of Daqu. The results showed that the average assembly length of the 25 samples was 100.5 Mb, a total of 439 000 gene catalogs were detected, and 5 104 species were identified. The results of species annotation showed that Kroppenstedtia eburnea was the dominant species, and the subdominant species were multiple Bacillus species. There was no significant difference in microbial community diversity between samples from the first feeding (Xiasha) and those from the first round of fermentation, and the β-diversity of the microbial community in samples from the second feeding (Zaosha) was higher than that in samples from Xiasha and the first round of fermentation. The results of gene functional annotation showed that the most abundant genes in Daqu were related to metabolism, while the most representative genes were related to carbohydrate metabolism and amino acid metabolism. The number of glycoside hydrolase genes in Zaosha samples was largest and the activities of related enzymes were highest. The above results indicated that the microbial community structures and functional composition in the three rounds of Daqu were basically consistent, whereas there was a difference in functional performance between the Zaosha samples and the other two samples

    Common Molecular Etiologies Are Rare in Nonsyndromic Tibetan Chinese Patients with Hearing Impairment

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    Background: Thirty thousand infants are born every year with congenital hearing impairment in mainland China. Racial and regional factors are important in clinical diagnosis of genetic deafness. However, molecular etiology of hearing impairment in the Tibetan Chinese population living in the Tibetan Plateau has not been investigated. To provide appropriate genetic testing and counseling to Tibetan families, we investigated molecular etiology of nonsyndromic deafness in this population. Methods: A total of 114 unrelated deaf Tibetan children from the Tibet Autonomous Region were enrolled. Five prominent deafness-related genes, GJB2, SLC26A4, GJB6, POU3F4, and mtDNA 12S rRNA, were analyzed. Inner ear development was evaluated by temporal CT. A total of 106 Tibetan hearing normal individuals were included as genetic controls. For radiological comparison, 120 patients, mainly of Han ethnicity, with sensorineural hearing loss were analyzed by temporal CT. Results: None of the Tibetan patients carried diallelic GJB2 or SLC26A4 mutations. Two patients with a history of aminoglycoside usage carried homogeneous mtDNA 12S rRNA A1555G mutation. Two controls were homozygous for 12S rRNA A1555G. There were no mutations in GJB6 or POU3F4. A diagnosis of inner ear malformation was made in 20.18 % of the Tibetan patients and 21.67 % of the Han deaf group. Enlarged vestibular aqueduct, the most common inner ear deformity, was not found in theTibetan patients, but was seen in 18.33 % of the Han patients. Common molecular etiologies

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    Integral Command Filtered Backstepping Control of a Flexible UAV

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    Airships, as the significant UAV, have a need for greater autonomy in their new missions. Therefore, airship flight control systems require precise dynamic modeling, taking into account the effect of flexibility and the interaction with aerodynamic forces. This research effort develops an efficient modeling of the autonomous flexible airship. The formalisation used is based on the Lagrange method. The resulting model includes the rigid body motion, the elastic deformation, and the coupling between them. Based on the precise flexible dynamic model, a novel backstepping nonlinear controller with integral action is proposed for motion control systems. The resulting feedback controller is able to adapt to actuator performance limitations, such as limitations in magnitude and rate of change of rudder, than conventional backstepping controller without integral action. With the deformation considered, the presented controller could resist the flexible uncertainty effect, and the system’s trajectory tracking ability is significantly improved. The approach guarantees exponential stability of a compensated tracking error in the sense of Lyapunov

    A Novel Sensor System for In Vivo Perception Reconstruction Based on Long Short-Term Memory Networks

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    Monitoring bodily pressure could provide valuable medical information for both doctors and patients. Long-term implantation of in vivo sensors is highly desirable in situations where perception reconstruction is needed. In particular, for fecal incontinence, artificial anal sphincters without perceptions could not remind patients when to defecate and even cause ischemic tissue necrosis due to uncontrolled clamping pressure. To address these issues, a novel self-packaging strain gauge sensor system is designed for in vivo perception reconstruction. In addition, long short-term memory (LSTM) networks, which show excellent performance in processing time series-related features and fitting properties, are used in this article to improve the prediction accuracy of the perception model. The proposed system has been tested and compared with the traditional linear regression (LR) approach using data from in vitro experiments. The results show that the Root-Mean-Square Error (RMSE) is reduced by more than 69%, which demonstrates that the prediction accuracy of the proposed LSTM model is higher than that of the LR model to reach a more accurate prediction of the amount of intestinal content. Furthermore, outcomes of in vivo experiments show that the robustness of the novel sensor system based on long short-term memory networks is verified through experiments with limited data

    A Three-Dimensional Orthogonal Receiving Coil for In Vivo Microrobot Wireless Power Transmission Systems

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    Approaches to studying electromagnetic induction in weak coupling have recently received attention in robotics since they could be used to supply energy to robots, allowing robots to diagnose and treat diseases in the human body. A three-dimensional orthogonal receiving coil connected in parallel, with a size of 13 mm × 13 mm × 13 mm, for an intestinal examination microrobot is designed in this article. Based on the defined attitude functions, we build and verify the stability and effectiveness of the proposed coil model through both analytical calculation and simulation analysis. In addition, to supply enough power to the microrobot, the number of turns of the receiving coil is optimized, considering both the electrical coil parameters and the limited space inside the robot. Then, an evaluation of the proposed 3D orthogonal receiving coil is presented in the bench tests. The results show that the power transmission efficiency can reach as high as 9.6%, with 1271 mW. This paper also uses a curved pipe to simulate the robot’s movement with the designed coil in the tortuous intestine. The average speed is 0.97 mm/s, with the path covering 180°. The experiments illustrate the excellent performance of the wireless power transmission, even when the positions of the two induction coils are constantly changing

    Integral Command Filtered Backstepping Control of a Flexible UAV

    No full text
    Airships, as the significant UAV, have a need for greater autonomy in their new missions. Therefore, airship flight control systems require precise dynamic modeling, taking into account the effect of flexibility and the interaction with aerodynamic forces. This research effort develops an efficient modeling of the autonomous flexible airship. The formalisation used is based on the Lagrange method. The resulting model includes the rigid body motion, the elastic deformation, and the coupling between them. Based on the precise flexible dynamic model, a novel backstepping nonlinear controller with integral action is proposed for motion control systems. The resulting feedback controller is able to adapt to actuator performance limitations, such as limitations in magnitude and rate of change of rudder, than conventional backstepping controller without integral action. With the deformation considered, the presented controller could resist the flexible uncertainty effect, and the system’s trajectory tracking ability is significantly improved. The approach guarantees exponential stability of a compensated tracking error in the sense of Lyapunov

    Research on parafoil optimal flight path planning algorithm for precise recovery of sub-stage booster of rocket

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    Parafoil is an important novel method to realize the precise recovery of sub-stage booster of rocket. In this paper, a parafoil optimal path planning algorithm based on longicorn algorithm is proposed to solve the problems that the parafoil is easily affected by wind field and the error of landing point is large in the recovery of sub-stage booster of rocket. Firstly, according to the dynamics and kinematics equations of the parafoil and a rocket sub-stage combined system, a 6-degree-of-freedom model of the system was established to analyze the effects of different downward deviation on the forward velocity, vertical velocity and the trajectory planning of the parafoil during the homing process of the rocket sub-stage. On this basis, the number of circling turns, radius and azimuth of the cutting-high section of the combination of the parafoil and the sub-stage booster were taken as the optimal parameters, and the optimal path planning was carried out by using the longicorn algorithm. Finally, a homing path with comprehensive consideration of energy and the accuracy of the landing point was obtained. The simulation results show that the piecewise optimal flight path planning algorithm based on longicorn algorithm proposed in this paper has fast convergence speed and high precision of flight track landing point
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