“数字信号处理”课程的几何视角

“数字信号处理”的经典课程体系以“系统”为中心，以离散时间傅立叶变换、z变换和离散傅立叶变换为分析工具，以滤波器设计为目的，注重定理和公式推导及其性质分析，很难让学生建立一个形象的、完整统一的知识体系框架。本文从几何视角将 “系统”化和“代数”化的经典课程体系重构为面向“信号”的“几何”知识体系，从而提升学生对本质问题的“洞察力”，帮助学生建立系统的知识体系。     

Synthesis of hollow Fe,Co, and N-doped carbon catalysts from conducting polymer-metal-organic-frameworks core-shell particles for their application in an oxygen reduction reaction

Oxygen reduction reaction (ORR), one of the key reactions for fuel cells and zinc-air batteries, should be improved for higher performance. Herein, we fabricated hollow Fe, Co, and nitrogen co-doped carbon (H-FeCo-NC) catalyst, which was prepared by carbonization of core-shell particles made of polypyrrole (PPy)-coated polystyrene (PS) spheres as cores and (Zn, Co) bimetallic-zeolitic imidazolate frameworks (ZnCoBZIFs) as shells. PPy was used as a nitrogen and a carbon source. The H-FeCo-NC catalyst had a high surface area of 324.08 m² g^?1 with uniformly distributed Fe and Co species, and excellent ORR performance with the half-wave potential of 0.888 V vs. reversible hydrogen electrode in alkaline media. Furthermore, the H-FeCo-NC catalyst demonstrated exceptional stability, durability, and tolerance to methanol crossover.     

Design of frameworks for self-adaptive service-oriented applications: A systematic analysis

Self-adaptive service-oriented Applications (Self-Apps) must be able to understand themselves or the environment in which they are executed, and propose solutions to meet changing conditions. The development of these applications is not a trivial task, since it encompasses issues from different research areas. Despite the importance of frameworks for Self-Apps, there is a lack of comprehensive analysis of how the design of such applications is performed, and regarding the standardization of concepts and coverage of minimum requirements for Self-Apps. The main contribution of this article is to present this comprehensive analysis, providing the state of the art for this subject. This analysis was built through a Systematic Mapping Study, based on a total of 65 studies, from which we identify the main attributes for Quality of Service (QoS), search strategies, and service management strategies employed in the design of frameworks for Self-Apps. The main aspects of requirements involved in the design of Self-Apps were pointed out to stakeholders. For example, these applications must implement a method for evaluation of QoS based on metrics. We also put forward the S-Frame, a modular solution that brings together the main features for the design of Self-Apps, and describe the main challenges concerning these applications.     

Molecular fingerprint and machine learning to accelerate design of high-performance homochiral metal–organic frameworks

Computational screening was employed to calculate the enantioseparation capabilities of 45 functionalized homochiral metal–organic frameworks (FHMOFs), and machine learning (ML) and molecular fingerprint (MF) techniques were used to find new FHMOFs with high performance. With increasing temperature, the enantioselectivities for (R,S)-1,3-dimethyl-1,2-propadiene are improved. The “glove effect” in the chiral pockets was proposed to explain the correlations between the steric effect of functional groups and performance of FHMOFs. Moreover, the neighborhood component analysis and RDKit/MACCS MFs show the highest predictive effect on enantioselectivities among the four ML classification algorithms with nine MFs that were tested. Based on the importance of MF, 85 new FHMOFs were designed, and a newly designed FHMOF, NO₂-NHOH-FHMOF, with high similarity to the optimal MFs achieved improved chiral separation performance, with enantioselectivities of 85%. The design principles and new chiral pockets obtained by ML and MFs could facilitate the development of new materials for chiral separation.     

Enhanced photoreactivity of MOFs by intercalating interlayer bands via simultaneous ?NCO and ?SCu modification

Herein, we propose a novel method to enhance the photoreactivity of an MOF catalyst by grafting isocyanate bonds ( NCO) and sulfhydryl-complexed copper ( SCu) onto ZIF-8 (NIF-SCu). The grafting process intercalated interlayer bands between the conduction and valence bands of ZIF-8, thereby providing a “ladder” for facile electron transition. The extreme improvement in the photoreactivity of NIF-SCu could be attributed to the enhancement in light responses in the range of 350–450 nm by  NCO groups and the widening of the visible light range of the MOF by  SCu groups. The formation of staggered energy levels in NIF-SCu could also narrow the band gap, lower the resistance, and facilitate the transfer of photogenerated carriers, thereby generating electrons with strong reduction potential in the  SCu conduction band. This study provides a new strategy for improving or even endowing the photoactivity of environmental functional materials with wide bandgaps.     

Implication of Size-Controlled Graphite Nanosheets as Building Blocks for Thermal Conductive Three-Dimensional Framework Architecture of Nanocarbons

Preparation of three-dimensional (3D) networks has received significant attention as an effective approach for applications involving transport phenomena, such as thermal management materials, and several nanomaterials have been examined as potential building blocks of 3D networks for the improvement of heat conduction in polymer nanocomposites. For that purpose, nanocarbons such as graphene and graphite nanoplatelets have been spotlighted as suitable filler materials because of their excellent thermal conductivities (ca. 10²–10³ W·(m·K)^?1 along their lateral axes) and morphological merits. However, the implications of morphological features such as the lateral length and thickness of graphene or graphene-like materials have not yet been identified. In this study, a controlled dissociation of bulk graphite to graphite nanosheets (GNSs) using a low-cost, ecofriendly bead mill process was extensively examined and, when configured in a 3D framework architecture formation, the size-controlled GNSs demonstrated that the thermal conductivities of a 3D interconnected framework of GNSs and the corresponding polymer nanocomposite were intimately correlated with the size of the GNSs, thus demonstrating the successful preparation of an efficient thermal management material without highly sophisticated efforts. The capability of controlling the lateral size and thickness of the GNSs as well as the use of a 3D interconnected framework architecture should greatly assist the commercialization of high-quality graphene-based thermal management materials in a scalable production process.     

Early-warning performance monitoring system (EPMS) using the business information of a project

An early-warning performance monitoring system (EPMS) is proposed to objectively measure and monitor the performance of a project for early detection of inherent poor performance problems. The EPMS is built based on project progress data and consists of a database of business information, an optimized theoretical model used as a performance measurement baseline, and an index for monitoring and forecasting the performance. By monitoring the performance through an application of the EPMS to the Korean construction project, the quarterly variation of index was found to differ by project type. These results could explain the environmental changes in the project execution. Therefore, the EPMS is expected to be an alternative for objective performance monitoring and forecasting while applying the existing methods is difficult because of the limited available data on performance indicators. The development procedures may also be useful to researchers interested in approaches to quantitatively analyze trends in various industries.     

多机器人体间动态碰撞检测方法仿真研究

当前多结合包围求碰撞检测法、Average-Case法、K-DOPs法等实现多机器人体间动态碰撞的检测,均存在寻优性能较差、检测效率较低的问题。为此提出一种基于动态粒子群的多机器人体间动态碰撞检测方法。采用OBB层次包围盒方法,缩小多机器人之间需要动态碰撞检测的区域,同时把动态碰撞检测问题转换为物体特征对间距离机制的非线性优化问题,进而构建层次拓扑框架进行局部碰撞检测,将机器人体引入到粒子群算法中建立混合进化算法,找到动态碰撞检测的最优解,实现多机器人体间动态碰撞检测。仿真结果证明,所提方法的检测效率高达96%,且具有较高的寻优性能。