Description logics （DLs） are widely employed in recent semantic web application systems. However, classical description logics are limited when dealing with imprecise concepts and roles, thus providing the motivatio...
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Description logics （DLs） are widely employed in recent semantic web application systems. However, classical description logics are limited when dealing with imprecise concepts and roles, thus providing the motivation for this work. In this paper, we present a type-2 fuzzy attributive concept language with complements （ALC） and provide its knowledge representation and reasoning algorithms. We also propose type-2 fuzzy web ontology language （OWL） to build a fuzzy ontology based on type- 2 fuzzy ALC and analyze the soundness, completeness, and complexity of the reasoning algorithms. Compared to type-1 fuzzy ALC, type-2 fuzzy ALC can describe imprecise knowledge more meticulously by using the membership degree interval. We implement a semantic search engine based on type-2 fuzzy ALC and carry out experiments on real data to test its performance. The results show that the type-2 fuzzy ALC can improve the precision and increase the number of relevant hits for imprecise information searches.
Multiple Kernel Learning (MKL) suffers from slow learning speed and poor generalization ability. Existing methods seldom address these problems well simultaneously. In this paper, by defining a multiclass (pseudo-) li...
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Monte-Carlo rendering algorithms are known for producing highly realistic images, but at a significant computational cost, because they rely on tracing up to trillions of light paths through a scene to simulate physic...
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ISBN:
(纸本)9783030050511;9783030050504
Monte-Carlo rendering algorithms are known for producing highly realistic images, but at a significant computational cost, because they rely on tracing up to trillions of light paths through a scene to simulate physically based light transport. For this reason, a large body of research exists on various techniques for accelerating these costly algorithms. As one of the Monte-Carlo rendering algorithms, PSSMLT (Primary Sample Space Metropolis Light Transport) is widely used nowadays for photorealistic rendering. Unfortunately, the computational cost of PSSMLT is still very high since the space of light paths in high-dimension and up to trillions of paths are typically required in such path space. Recent research on PSSMLT has proposed a variety of optimized methods for single node rendering, however, multi-node rendering for PSSMLT is rarely mentioned due in large part to the complicated mathematical model, complicated physical processes and the irregular memory access patterns, and the imbalanced workload of light-carrying paths. In this paper, we present a highly scalable distributed parallel simulation framework for PSSMLT. Firstly, based on light transport equation, we propose the notion of sub-image with certain property for multi-node rendering and theoretically prove that the whole set of sub-images can be combined to produce the final image;Then we further propose a sub-image based assignment partitioning algorithm for multi-node rendering since the traditional demand-driven assignment partitioning algorithm doesn't work well. Secondly, we propose a physically based parallel simulation for the PSSMLT algorithm, which is revealed on a parallel computer system in master-worker paradigm. Finally, we discuss the issue of granularity of the assignment partitioning and some optimization strategies for improving overall performance, and then a static/dynamic hybrid scheduling strategy is described. Experiments show that framework has a nearly linear speedup along wi
Mobile cloud computing (MCC) enhances mobile device capabilities with cloud-based resources, allowing mobile users to outsource more data to the cloud to enjoy services of interest. It uses ciphertext policy attribute...
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Hungarian method is a classical method for solving assignment problems. It also can be widely used in other problems, such as matching problem. This paper researches its application on using structural index reduction...
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Hungarian method is a classical method for solving assignment problems. It also can be widely used in other problems, such as matching problem. This paper researches its application on using structural index reduction method to solve high-index DAEs, based on the combinatorial relaxation theory. Combinatorial relaxation theory converts the complex mathematical problem to the matching problem of bipartite graph. Based on this theory, this paper presents the main idea of Hungarian method and puts up three implementations for Hungarian method. At last, it compares the time performance of the three implementations by running a set of experiments.
As the complexity of cyberattacks continues to increase, traditional static defense strategies have shown significant limitations. This study proposes an intelligent cybersecurity defense framework based on large lang...
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ISBN:
(数字)9798331520298
ISBN:
(纸本)9798331520304
As the complexity of cyberattacks continues to increase, traditional static defense strategies have shown significant limitations. This study proposes an intelligent cybersecurity defense framework based on large language model Agents, and conducts a comparative analysis of the effectiveness of various leading models in the cybersecurity defense domain. By developing an attack behavior model, designing an Agent decision-making mechanism, and constructing a defense strategy execution and evaluation system, we assess the defense performance of models such as GPT-4.5, Claude 3.7, LLaMA 3.3, and Gemini 2.0 under different attack scenarios. The experimental results demonstrate that defense strategies based on LLM Agents outperform traditional methods in terms of attack detection rate, response time, and false alarm rate. Furthermore, each model exhibits unique advantages in specific security contexts. This research provides new insights for the development of more adaptive and efficient cybersecurity defense systems.
Cellular Manufacturing is a manufacturing strategy implemented to improve productivity and flexibility. Over the past two decades, it has shown significant effectiveness in practical applications. Its benefits include...
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Cellular Manufacturing is a manufacturing strategy implemented to improve productivity and flexibility. Over the past two decades, it has shown significant effectiveness in practical applications. Its benefits include simplifying production processes, reducing production time, minimizing material handling, enhancing productivity innovation, and reducing quality issues. However, in the manufacturing of cellular systems, the issue of exceptional elements is always unavoidable. This refers to parts or operations that do not fit neatly into any single production cell and must be processed outside their designated cell. For manufacturers, there are three possible ways to deal with such exceptional elements: purchasing additional machines for the current manufacturing cell to process the parts, transporting the parts to other manufacturing cells for processing, or outsourcing the processing of the parts. However, any of these methods will inevitably increase the manufacturing costs for the manufacturer. Decision-makers must consider all potential issues to minimize overall costs as much as possible;however, few studies have addressed this in the past. This research proposes heuristic Tabu search algorithms to tackle the optimization of exceptional elements within manufacturing cells. Three models are developed: Model 1 allows partial outsourcing of part processing, while Model 2 requires full process outsourcing. The objective functions and constraints of these models account for the diversity of manufacturing cells and the treatment of exceptional elements, providing a comprehensive solution for system optimization. Model 3 apply the multi-objective function for compromising different objectives. Experimental results demonstrate the effectiveness of the proposed algorithm in finding feasible or near-optimal solutions within a reasonable timeframe, ensuring the efficient handling of exceptional elements in manufacturing cell formation.
We show that the EXPSPACE-hardness result for structural liveness of Petri nets [Jančar and Purser, 2019] holds even for a simple subclass of conservative nets. As the main result we then show that for structural...
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Container technology represents a dynamic and adaptable solution in the field of software development for cloud computing applications and services, presenting the advantages of both portability and operational effici...
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Sweep spread carrier (S2C) acoustic communication uses wideband chirp waveforms as they are well suited for communicating in an undersea multipath environment. While the gradient heterodyne receivers in the S2C system...
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ISBN:
(数字)9798350368741
ISBN:
(纸本)9798350368758
Sweep spread carrier (S2C) acoustic communication uses wideband chirp waveforms as they are well suited for communicating in an undersea multipath environment. While the gradient heterodyne receivers in the S2C systems can handle the multipath arrivals, we show that they are extremely sensitive to a time scaling of the communication waveform induced by the Doppler effect or carrier frequency offset. The time-scaling can be estimated, and compensated for by re-scaling the received waveform. However, estimation errors leave out a residual timescale even in the re-scaled waveform. We show that even a timescale estimation error of the order of ±10 –5 can lead to deleterious variations in the symbol phases within a received S2C frame. We also show the existence of multiple, frequency-dependent, approximately affine symbol phase migration trajectories in a received frame in the presence of small residual time-scales and timing errors. Motivated by this observation, we propose a parallel bank of low complexity decision-aided progressive symbol phase (DAPSP) equalizers to effectively suppress the symbol phase migration in the S2C receiver.
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