单向函数与对称密码体制

可靠的密码学是建立在数学和形式化的计算机科学产生的结论之上的。本文从计算理论的角度阐述了构建对称密码体制所需的数学背景：算法复杂性与问题复杂性的关系;NP问题与密码学的关系;密钥长度与密码安全的关系．从保长和置换的概念入手。说明了构造对称密码体制的理论基础——单向置换和单向函数,并以计算机口令系统为实例说明了如何构造对称密码系统．     

如果城市并非树形——亚历山大与萨林加罗斯的城市设计复杂性理论研究

城市复杂性理论是当代城市设计理论研究的重要方向之一。克里斯托弗·亚历山大和尼科斯·萨林加罗斯具有一定的学术师承关系。同为当代著名的建筑城市复杂性理论研究者,其研究成果均在学术界引起极大反响。本文试图通过对亚历山大和萨林加罗斯相关理论的比较分析。辨析二者之间在传承与递进、关联与变异、表象与内涵等方面特质,进而深化对当代城市设计理论研究的理解与认识。     

An epistemological approach to human systems integration

Can we contribute to developing a consistent terminology and, to some extent, an acceptable ontology in the rapidly expanding field of human systems integration (HSI)? We often define HSI as a process and a product at the confluence of several areas, such as systems engineering, human factors and ergonomics, information technology, and specific sectors, such as aerospace, health, and energy. It is a broader transdisciplinary field in our increasingly complex human-machine world that focuses on integrating technology, organizations, and people within a complex sociotechnical system throughout its life cycle. Therefore, HSI is no longer a question of usability and user interface design once a complex machine is technologically developed, but also about considering people and organizations early on in the design and development processes. Indeed, rooted in industrial engineering research and operational worlds, HSI requires a deeper foundation based on an epistemological approach. This assertion is even more crucial today as technology has become predominantly digital, and, more specifically, the concept of the digital twin is emphasized because it has become essential to support model-based HSI. In other words, software-based assistant systems are replacing traditional tools. Therefore, appropriate social-cognitive (multi-agent) models and methods are helpful throughout the life cycle of contemporary sociotechnical designs to account for the complexity and tangibility of their human-centered context-sensitive architectures, combining procedural and declarative knowledge. By considering these reasons, this article provides a set of fundamental axioms, some theoretical abstractions, and valuable practical models, which are presented and illustrated through the lens of an evolutionary HSI ontology.     

Low calculation cost of HEVC coding unit size based on spatial homogeneity detection

For the same video quality, HEVC gives 25% to 50% bitrate savings, compared to its predecessor the Advanced Video Coding H.264 and thus supports resolutions up to 8 K UHD. However, the reduction in bitrates provided by the HEVC leads to an increase in the computational cost of the encoding operation. This complexity can become a true handicap especially for real-time video streaming and also for VANET (Vehicular Ad-Hoc Network) applications such as traffic safety and Video surveillance. The improvement in the bitrates and also the increase in the calculation cost are due to the use of large and multi-sized coding, prediction and transform blocks. Indeed, the H264 coder is based on structure macroblocks with sizes 4 × 4, 8 × 8 and 16 × 16, while H.265 depends on Coding Tree Units (CTUs), CTUs select sizes 4 × 4, 8 × 8, 16 × 16, 32 × 32 and 64 × 64 blocks. This paper proposes a fast CU (Coding Unit) size decision method to reduce the HEVC calculation cost based on spatial homogeneity. Compared with the HM16.13 benchmark test model, the average coding time is reduced by around 40% for CIF / QCIF video sequences, 35% to 43% for class A, B and C test sequences. These important reductions in coding time are obtained with negligible loss of quality and an average increase in bitrates which does not exceed 0.89% for the three configuration modes (All intra, Random Access and Low Delay).     

Accelerating QTMT-based CU partition and intra mode decision for versatile video coding

The H.266/VVC achieves about 50% bitrate saving compared to its predecessor H.265/HEVC at the expense of exponentially increased computational complexity. The most efficient but complex technique for H.266/VVC intra frame coding is the QuadTree with a nested Multi-type Tree encoding structure (QTMT), which usually requires traversing the Rate-Distortion (R-D) cost of each partition and each mode for the best option. To alleviate such computational burden while preserving the coding efficiency as much as possible, this paper develops a multi-feature guided Fast CU Partition (FCP) and Laplacian guided Fast Mode Selection (FMS) to accelerate the intra QTMT decision together. For FCP, we regard the CU partition as a classification problem and adopt the Support Vector Machine (SVM) for its low-complexity implementation; after evaluating the contribution of a set of features, three representative features of video textures are selected and used to train the SVM model. Additionally, an advanced technique is applied by adopting a soft decision in SVM for a more flexible trade-off between the complexity and R-D performance. For FMS, we utilize the Laplace operator to determine the most probable directions of the current CU and skip half of the candidate modes for runtime saving. Experimental results demonstrate that the proposed FCP reduces the encoding time of H.266/VVC by 51.03% with 1.65% Bjøntegaard Delta Bit-Rate (BDBR) increase; the proposed FMS reduces the encoding time by 12.68% with 0.09% BDBR loss. Their direct combination and advanced combination finally lead to 54.84% encoding time reduction with 1.74% BDBR increase and 40.39% encoding time reduction with 1.33% BDBR increase, respectively, outperforming state-of-the-art approaches significantly.