Transcendental functions are important functions in various high performance computing *** these functions are time-consuming and the vector units on modern processors become wider and more scalable,there is an increa...
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Transcendental functions are important functions in various high performance computing *** these functions are time-consuming and the vector units on modern processors become wider and more scalable,there is an increasing demand for developing and using vector transcendental functions in such performance-hungry ***,the performance of vector transcendental functions as well as their accuracy remain largely *** address this issue,we perform a comprehensive evaluation of two Single Instruction Multiple Data(SIMD)intrinsics based vector math libraries on two ARMv8 compatible *** first design dedicated microbenchmarks that help us understand the performance behavior of vector transcendental ***,we propose a piecewise,quantitative evaluation method with a set of meaningful metrics to quantify their performance and *** analyzing the experimental results,we find that vector transcendental functions achieve good performance speedups thanks to the vectorization and algorithm ***,vector math libraries can replace scalar math libraries in many cases because of improved performance and satisfactory *** this,the implementations of vector math libraries are still immature,which means further optimization is needed,and our evaluation reveals feasible optimization solutions for future vector math libraries.
Improving website security to prevent malicious online activities is crucial,and CAPTCHA(Completely Automated Public Turing test to tell computers and Humans Apart)has emerged as a key strategy for distinguishing huma...
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Improving website security to prevent malicious online activities is crucial,and CAPTCHA(Completely Automated Public Turing test to tell computers and Humans Apart)has emerged as a key strategy for distinguishing human users from automated ***-based CAPTCHAs,designed to be easily decipherable by humans yet challenging for machines,are a common form of this ***,advancements in deep learning have facilitated the creation of models adept at recognizing these text-based CAPTCHAs with surprising *** our comprehensive investigation into CAPTCHA recognition,we have tailored the renowned UpDown image captioning model specifically for this *** approach innovatively combines an encoder to extract both global and local features,significantly boosting the model’s capability to identify complex details within CAPTCHA *** the decoding phase,we have adopted a refined attention mechanism,integrating enhanced visual attention with dual layers of Long Short-Term Memory(LSTM)networks to elevate CAPTCHA recognition *** rigorous testing across four varied datasets,including those from Weibo,BoC,Gregwar,and Captcha 0.3,demonstrates the versatility and effectiveness of our *** results not only highlight the efficiency of our approach but also offer profound insights into its applicability across different CAPTCHA types,contributing to a deeper understanding of CAPTCHA recognition technology.
Time series data plays a crucial role in intelligent transportation *** flow forecasting represents a precise estimation of future traffic flow within a specific region and time *** approaches,including sequence perio...
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Time series data plays a crucial role in intelligent transportation *** flow forecasting represents a precise estimation of future traffic flow within a specific region and time *** approaches,including sequence periodic,regression,and deep learning models,have shown promising results in short-term series ***,forecasting scenarios specifically focused on holiday traffic flow present unique challenges,such as distinct traffic patterns during vacations and the increased demand for long-term ***,the effectiveness of existing methods diminishes in such ***,we propose a novel longterm forecasting model based on scene matching and embedding fusion representation to forecast long-term holiday traffic *** model comprises three components:the similar scene matching module,responsible for extracting Similar Scene Features;the long-short term representation fusion module,which integrates scenario embeddings;and a simple fully connected layer at the head for making the final *** results on real datasets demonstrate that our model outperforms other methods,particularly in medium and long-term forecasting scenarios.
Session-based Recommendation(SBR)aims to accurately recom-mend a list of items to users based on anonymous historical session *** methods for SBR suffer from several limitations:SBR based on Graph Neural Network often...
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Session-based Recommendation(SBR)aims to accurately recom-mend a list of items to users based on anonymous historical session *** methods for SBR suffer from several limitations:SBR based on Graph Neural Network often has information loss when constructing session graphs;Inadequate consideration is given to influencing factors,such as item price,and users’dynamic interest evolution is not taken into account.A new session recommendation model called Price-aware Session-based Recommendation(PASBR)is proposed to address these *** constructs session graphs by information lossless approaches to fully encode the original session information,then introduces item price as a new factor and models users’price tolerance for various items to influence users’*** addition,PASBR proposes a new method to encode user intent at the item category level and tries to capture the dynamic interest of users over ***,PASBR fuses the multi-perspective features to generate the global representation of users and make a ***,the intent,the short-term and long-term interests,and the dynamic interests of a user are *** on two real-world datasets show that PASBR can outperform representative baselines for SBR.
Scattering medium in light path will cause distortion of the light field,resulting in poor signal-to-noise ratio(SNR)of ghost *** disturbance is usually eliminated by the method of *** deduce the intensity fluctuation...
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Scattering medium in light path will cause distortion of the light field,resulting in poor signal-to-noise ratio(SNR)of ghost *** disturbance is usually eliminated by the method of *** deduce the intensity fluctuation correlation function of the ghost imaging with the disturbance of the scattering medium,which proves that the ghost image consists of two correlated results:the image of scattering medium and the target *** effect of the scattering medium can be eliminated by subtracting the correlated result between the light field after the scattering medium and the reference light from ghost image,which verifies the theoretical *** research may provide a new idea of ghost imaging in harsh environment.
In the era of big data and growing privacy concerns, Federated Learning (FL) has emerged as a promising solution for collaborative model training while preserving user data privacy. However, FL faces challenges such a...
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Human-machine cooperative control has become an important area of intelligent driving,where driver intention recognition and dynamic control authority allocation are key factors for improving the performance of cooper...
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Human-machine cooperative control has become an important area of intelligent driving,where driver intention recognition and dynamic control authority allocation are key factors for improving the performance of cooperative decision-making and *** this paper,an online learning method is proposed for human-machine cooperative control,which introduces a priority control parameter in the reward function to achieve optimal allocation of control authority under different driver intentions and driving safety ***,a two-layer LSTM-based sequence prediction algorithm is proposed to recognise the driver's lane change(LC)intention for human-machine cooperative steering ***,an online reinforcement learning method is developed for optimising the steering authority to reduce driver workload and improve driving *** driver-in-the-loop simulation results show that our method can accurately predict the driver's LC intention in cooperative driving and effectively compensate for the driver's non-optimal driving *** experimental results on a real intelligent vehicle further demonstrate the online optimisation capability of the proposed RL-based control authority allocation algorithm and its effectiveness in improving driving safety.
In today’s world, the demand for computing power and the need for environmental protection and energy saving have made Green Cloud Computing (GCC) popular in various fields. Customers from all over the world can acce...
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Higher-order topological phases of matter, including insulators and semimetals, have attracted much attention, since they can induce novel multidimensional topological boundary states. Recently, a two-dimensional (2D)...
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Higher-order topological phases of matter, including insulators and semimetals, have attracted much attention, since they can induce novel multidimensional topological boundary states. Recently, a two-dimensional (2D) multipole chiral-symmetric higher-order topological insulator (MCTI) with multipole corner states, protected by multiple chiral numbers (MCNs), has been proposed theoretically and soon will be implemented in circuit and acoustic systems. However, the chiral-symmetry higher-order topological semimetals remain unexplored. In this work, we study the multipole chiral symmetry on the three-dimensional topological semimetals based on long-range hoppings. We theoretically propose two types of multiple chiral topological semimetals (MCTSs). The multipole hinge states, which are protected by kz-dependent MCNs, are observed at one-dimensional (1D) hinge boundaries in the corresponding subspace. To verify our theory, we construct one type of MCTS in acoustic crystal as an example. Four groups of topological hinge states are obtained at each 1D hinge boundary of the constructed acoustic system. These multiple hinge states may have potential applications to improve the sensing and calculation of quantum devices.
In today’s computing power era, AI model training, weather forecasting, aircraft design, and so on are inseparable from parallel computing. Parallel computing is everywhere. However, effectively tackling parallel com...
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