Query auto-completion(QAC) is the first step of information retrieval, which helps users formulate the entire query after inputting only a few prefixes. Regarding the models of QAC, the traditional method ignores the ...
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Query auto-completion(QAC) is the first step of information retrieval, which helps users formulate the entire query after inputting only a few prefixes. Regarding the models of QAC, the traditional method ignores the contribution from the semantic relevance between queries. However, similar queries always express extremely similar search intention. In this paper, we propose a hybrid model FS-QAC based on query semantic similarity as well as the query frequency. We choose word2 vec method to measure the semantic similarity between intended queries and pre-submitted queries. By combining both features, our experiments show that FS-QAC model improves the performance when predicting the user's query intention and helping formulate the right query. Our experimental results show that the optimal hybrid model contributes to a 7.54% improvement in terms of MRR against a state-of-the-art baseline using the public AOL query logs.
With various forms of distributed new energy access to the distribution network, the traditional distribution network has changed from the role of "consumer" of electric energy to "producer and consumer...
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ISBN:
(数字)9798350349030
ISBN:
(纸本)9798350349047
With various forms of distributed new energy access to the distribution network, the traditional distribution network has changed from the role of "consumer" of electric energy to "producer and consumer" of electric energy in the active distribution network. It is necessary to evaluate the self-generation and consumption capacity of the active distribution network, and consider the volatility of wind and solar output to optimize the scheduling, so as to improve the absorption rate of new energy and optimize the operation state of the distribution network. Therefore, a self-balancing evaluation index of active distribution network is designed in this paper, and a two-stage robust optimal scheduling method considering self-balancing capability of distribution network is proposed. Firstly, the composition of self-balancing capacity of active distribution network is analyzed, and various resources involved in self-balancing are modeled. Secondly, considering the real-time power balance in the dispatching process and the flexibility demand in a certain time, the index of evaluating the self-balancing ability of active distribution network is proposed. Then, the second-order robust optimal scheduling model is constructed with the goal of the lowest operating cost and the highest regional self-balancing degree, and is solved by column and constraint generation methods. Finally, a numerical example is given to verify the effectiveness of the proposed method for the optimal operation of the distribution network.
With the rapid development of information technology, touch screen applications has become increasingly popular in China, already formed gradually industry, touch input devices will be the future development of the in...
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With the rapid development of information technology, touch screen applications has become increasingly popular in China, already formed gradually industry, touch input devices will be the future development of the information technology of the mainstream products. Based on DMT64480T056-01W touch c8051f020 SCM LCD, hardware interface design as an example, detail the use of its generate graphics to display the man-machine interface and the touch-key test control method, so as to achieve color touch LCD monitor control. Gives interface circuit principle of the microcontroller and serial control LCD module , main control program design method ,and the program design of its main function. It Solves the problems of choosing LCD, driving, and complex software programming in microprocessor use big dot matrix LCD monitor process.
Rust is a new safe system programming language enforcing safety guarantees by novel language features, a rich type system, and strict compile-time checking rules, and thus has been used extensively to build system sof...
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Rust is a new safe system programming language enforcing safety guarantees by novel language features, a rich type system, and strict compile-time checking rules, and thus has been used extensively to build system software. For multilingual Rust applications containing external C code, memory security vulnerabilities can occur due to the intrinsically unsafe nature of C and the improper interactions between Rust and C. Unfortunately, existing security studies on Rust only focus on pure Rust code but cannot analyze either the native C code or the Rust/C interactions in multilingual Rust applications. As a result, the lack of such studies may defeat the guarantee that Rust is a safe *** paper presents CRust, a unified program analysis framework across Rust and C, which enables program analyses to understand the semantics of C code by translating Rust and C into a unified specification language. The CRust framework consists of three key components: (1) a unified specification language CRustIR, which is a strong-typed low-level intermediate language suitable for program analysis; (2) a transformation to build models of C code by converting C code into CRustIR; and (3) program analysis algorithms on CRustIR to detect security vulnerabilities. We have implemented a software prototype for CRust, and have conducted extensive experiments to evaluate its effectiveness and performance. Experimental results demonstrated that CRust can effectively detect common memory security vulnerabilities caused by the interaction of Rust and C that are missed by state-of-the-art tools. In addition, CRust is efficient in bringing negligible overhead (0.23 seconds on average).
Recent advances in the field of network representation learning are mostly attributed to the application of the skip-gram model in the context of graphs. State-of-the-art analogues of skip-gram model in graphs define ...
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ISBN:
(纸本)9781538660522
Recent advances in the field of network representation learning are mostly attributed to the application of the skip-gram model in the context of graphs. State-of-the-art analogues of skip-gram model in graphs define a notion of neighbourhood and aim to find the vector representation for a node, which maximizes the likelihood of preserving this neighborhood. In this paper, we take a drastic departure from the existing notion of neighbourhood of a node by utilizing the idea of coreness. More specifically, we utilize the well-established idea that nodes with similar core numbers play equivalent roles in the network and hence induce a novel and an organic notion of neighbourhood. Based on this idea, we propose core2vec, a new algorithmic framework for learning low dimensional continuous feature mapping for a node. Consequently, the nodes having similar core numbers are relatively closer in the vector space that we learn. We further demonstrate the effectiveness of core2vec by comparing word similarity scores obtained by our method where the node representations are drawn from standard word association graphs 11 In linguistics, such networks built from various linguistic units are known to have a core-periphery structure (see [3] and the references therein), against scores computed by other state-of-the-art network representation techniques like node2vec, Deep-Walk and LINE. Our results always outperform these existing methods, in some cases achieving improvements as high as 46 % on certain ground-truth word similarity datasets. We make all codes used in this paper available in the public domain: https://***/Sam131112/Core2vec_test.
Chinese culture is extensive and profound, and Chinese medicine has emerged as a shining pearl in Chinese culture thousands of years ago. In the development of traditional Chinese medicine, various treatments are also...
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Chinese culture is extensive and profound, and Chinese medicine has emerged as a shining pearl in Chinese culture thousands of years ago. In the development of traditional Chinese medicine, various treatments are also emerging. In such a development process, there is a medical model called "Chinese medicine psychology." It was not until the 1980 s that it was proposed to be separated from traditional Chinese medicine and develop into an independent research discipline. Such a discipline that has been accompanied by the development of traditional Chinese culture is in harmony with the traditional culture of China for thousands of years. This paper discusses the interaction between traditional Chinese culture and traditional Chinese medicine psychology, so that people can more accurately understand the mysteries between traditional Chinese medicine psychology and traditional culture.
Taking the required courses of art design major in higher institutions as the breakthrough point,this paper studies the ideological innovation of teaching management,the practical innovation of teaching content and th...
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Taking the required courses of art design major in higher institutions as the breakthrough point,this paper studies the ideological innovation of teaching management,the practical innovation of teaching content and the technological innovation of teaching methods. The result shows: classroom teaching is the main teaching method of creative education,practical teaching activities are complementary,perfect and extended to the traditional teaching methods in creative education;teachers should strive to strengthen their innovative education consciousness,sum up the scientific methods of innovative education,cultivate students' ability of independent learning,and create the free learning environment for students.
Lung cancer is one of the most common forms of cancer resulting in over a million deaths per year worldwide. In order to classify the lung CT images, this paper presents a classification method using 3 D-CNN with a sc...
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Lung cancer is one of the most common forms of cancer resulting in over a million deaths per year worldwide. In order to classify the lung CT images, this paper presents a classification method using 3 D-CNN with a scheduled learning strategy. To get compact and uniform data for training and feature extracting, the input should be unified into 100×100×20 dimension. We construct a 3 D-CNN model where a scheduled learning strategy method is proposed in the process of network training. This method is shown to out-perform the state-of-the-art approaches by experiments conducted on the datasets of lung CT scans in Kaggle.
In order to make Qiang culture continue to spread and spread in modern times, this paper studies the digital protection and inheritance of Qiang *** research mainly focuses on the characteristics of Qiang's cultur...
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In order to make Qiang culture continue to spread and spread in modern times, this paper studies the digital protection and inheritance of Qiang *** research mainly focuses on the characteristics of Qiang's cultural heritage, the design of digital database and the application of *** dissemination forms and ways of Qiang's cultural heritage are analyzed, so that we can understand how Qiang's culture is disseminated through digital form and verify its *** the analysis, it can be seen that under the database application designed in this paper, Qiang culture can be connected with the Internet environment, spread by digital animation or other forms, and the dissemination effect is good, which shows that the design of this paper is effective;there is a good coincidence between digitalization and the Internet, and the Internet as a modern popular one." Virtual environment" has a large number of users of different interests and ages, so Qiang culture can be known by more people in the Internet environment, indicating that it has been protected and inherited continuously.
Distribution networks with renewable energy encounter two challenges. One is that during the peak load, generation is normally low or zero and it will cause the voltage drop. Meanwhile, during peak generation period, ...
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Distribution networks with renewable energy encounter two challenges. One is that during the peak load, generation is normally low or zero and it will cause the voltage drop. Meanwhile, during peak generation period, the generated power will exceed the load and be injected to the grid, which will cause the voltage rise. This paper proposes a MILP(Mixed Integer Linear programming) approach to accommodate more wind generation in distribution networks. Optimal system contains battery energy storage system(BESS), wind power, external grid, critical load and controllable load. By coordinating the states of controllable load, battery and wind power direction, the objective to minimize the total cost from grid can be reached. Detailed case study is given to demonstrate the feasibility of this approach.
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