Evolving patterns of agricultural production space in China:A network-based approach

The agricultural production space,as where and how much each agricultural product grows,plays a vital role in meeting the increasing and diverse food demands.Previous studies on agricultural production patterns have predominantly centered on individual or specific crop types,using methods such as remote sensing or statistical metrological analysis.In this study,we characterize the agricultural production space(APS)by bipartite network connecting agricultural products and provinces,to reveal the relatedness between diverse agricultural products and the spatiotemporal characteristic of provincial production capabilities in China.The results show that core products are cereal,pork,melon,and pome fruit;meanwhile the milk,grape,and fiber crop show an upward trend in centrality,which is in line with diet structure changes in China over the past decades.The little changes in community components and structures of agricultural products and provinces reveal that agricultural production patterns in China are relatively stable.Additionally,identified provincial communities closely resemble China's agricultural natural zones.Furthermore,the observed growth in production capabilities in North and Northeast China implies their potential focus areas for future agricultural production.Despite the superior production capa-bilities of southern provinces,recent years have witnessed a notable decline,warranting special attentions.The findings provide a comprehensive perspective for understanding the complex relationship of agricultural prod-ucts'relatedness,production capabilities and production patterns,which serve as a reference for the agricultural spatial optimization and agricultural sustainable development.

Requirements ranking based on crowd-sourcing high-end product USs

Based on the characteristics of high-end products,crowd-sourcing user stories can be seen as an effective means of gathering requirements,involving a large user base and generating a substantial amount of unstructured feedback.The key challenge lies in transforming abstract user needs into specific ones,requiring integration and analysis.Therefore,we propose a topic mining-based approach to categorize,summarize,and rank product requirements from user stories.Specifically,after determining the number of story categories based on py LDAvis,we initially classify“I want to”phrases within user stories.Subsequently,classic topic models are applied to each category to generate their names,defining each post-classification user story category as a requirement.Furthermore,a weighted ranking function is devised to calculate the importance of each requirement.Finally,we validate the effectiveness and feasibility of the proposed method using 2966 crowd-sourced user stories related to smart home systems.

ON DOUBLY WARPED PRODUCT OF COMPLEX FINSLER MANIFOLDS

Let （M1, F1） and （M2, F2） be two strongly pseudoconvex complex Finsler man- ifolds. The doubly wraped product complex Finsler manifold （f2 M1 x h M2, F） of （M1, F1） and （M2, F2） is the product manifold M1 x M2 endowed with the warped product complex 2 2 Finsler metric F2 = f2F1 ＋ fl F2, where fl and f2 are positive smooth functions on M1 and M2, respectively. In this paper, the most often used complex Finsler connections, holomorphic curvature, Ricci scalar curvature, and real geodesics of the DWP-complex Finsler manifold are derived in terms of the corresponding objects of its components. Necessary and sufficient conditions for the DWP-complex Finsler manifold to be K/ihler Finsler （resp., weakly K/ihler Finsler, complex Berwald, weakly complex Berwald, complex Landsberg） manifold are ob- tained, respectively. It is proved that if （M1, F1） and （M2,F2） are projectively flat, then the DWP-complex Finsler manifold is projectively flat if and only if fl and f2 are positive constants.

SOME RESULTS ON PRODUCT COMPLEX FINSLER MANIFOLDS

Let （M, F ） be the product complex Finsler manifold of two strongly pseudoconvex complex Finsler manifolds （M 1 , F 1 ） and （M 2 , F 2 ）. In this paper, we obtain the relationship between the Chern Finsler connection coefficients Γ i ; k associated to F and the Chern Finsler connection coefficients Γ a ; c , Γα ; γ associated to F 1 , F 2 , respectively. As applications we prove that, if both （M 1 , F 1 ） and （M 2 , F 2 ） are strongly Ka¨hler Finsler （complex Berwald, or locally complex Minkowski, respectively） manifolds, so does （M, F ）. Furthermore, we prove that the holomorphic curvature K F = 0 if and only if K F1 = 0 and K F2 = 0.

Response surface methodology-based hybrid robust design optimization for complex product under mixed uncertainties

Minimizing the impact of the mixed uncertainties(i.e.,the aleatory uncertainty and the epistemic uncertainty) for a complex product of compliant mechanism(CPCM) quality improvement signifies a fascinating research topic to enhance the robustness.However, most of the existing works in the CPCM robust design optimization neglect the mixed uncertainties, which might result in an unstable design or even an infeasible design. To solve this issue, a response surface methodology-based hybrid robust design optimization(RSM-based HRDO) approach is proposed to improve the robustness of the quality characteristic for the CPCM via considering the mixed uncertainties in the robust design optimization. A bridge-type amplification mechanism is used to manifest the effectiveness of the proposed approach. The comparison results prove that the proposed approach can not only keep its superiority in the robustness, but also provide a robust scheme for optimizing the design parameters.

Evaluating the conceptual design schemes of complex products based on FAHP using fuzzy number

In the conceptual design stage of complex products, CBR（Case-Based Reasoning） tool is useful to offer a feasible set of schemes. Then the most adaptive scheme can be generated through a procedure of comparison and evaluation. The procedure is essentially a multiple criteria decision-making problem. The traditional multiple criteria programming is not flexible enough in executing the system evaluation algorithm due to both the limited experimental data and the lack of human experiences. To make the CBR tool to be more efficient, a new method for the best choice among the feasible schemes based on the Fuzzy AHP using Fuzzy numbers （FFAHP） is proposed. Since the final results become a problem of ranking the mean of fuzzy numbers by the optimism of decision-maker using the FFAHP, its execution is much more intuitive and effective than with the traditional method.

A Design Method with Knowledge Modeling for Complex Product Based on Ontology

Innovation design for complex products is a difficult issue in the military manufacturing industry. Ontology may provide a feasible way to rebuild the design process for complex products via sharing and reusing of design knowledge. In this paper, a design method used in the innovation design process of the complex products with knowledge modeling is proposed. Knowledge modeling is realized through ontology construction by combining the cycling evolutional theory of constructing ontology and OWL (Ontology Web Language)-based knowledge representation. As a case study, the satellite is selected as one of the complex products. The application domain of the satellite ontology is analyzed. According to the analysis result, the knowledge structure of satellite ontology is put forward based on OWL. The application of satellite product design shows that the method can effectively organize and reuse the knowledge resources in the innovation design of complex product and help companies to create more competitive products based on the existing knowledge and experience.

Object registration using an RGB-D camera for complex product augmented assembly guidance

Background Augmented assembly guidance aims to help users complete assembly operations more efficiently and quickly through augmented reality technology,breaking the limitations of traditional assembly guidance technology which is single in content and boring in way.Object registration is one of the key technologies in augmented assembly guidance process,which can affect the location and direction of virtual assembly guidance information in real assembly environment.Methods This paper presents an object registration method based on RGB-D camera,which combines Lucas-Kanade(LK)optical flow algorithm and Iterative Closet Point(ICP)algorithm.An augmented assembly guidance system for complex products through this method is built.Meanwhile,in order to compare the effectiveness of the proposed method,we also implemented object registration based on an open source augmented reality SDK Vuforia.Results An engine model and a complex weapon cabin equipment are taken as an case to verify this work.The result shows that the registration method proposed in this paper is more accurate and stable compared with that based on Vuforia and the augmented assembly guidance system through this method greatly improves the user's time compared with the traditional assembly.Conclusions Therefore,we can conclude that the object registration method mentioned in this paper can be well applied in the augmented assembly guidance system,which can do enhance the efficiency of assembly considerably.

COMPLEX INNER PRODUCT AVERAGING METHOD FOR CALCULATING NORMAL FORM OF ODE

This paper puts forward a complex inner product averaging method for calculating normal form of ODE. Compared with conventional averaging method, the theoretic analytical process has such simple forms as to realize computer program easily. Results can be applied in both autonomous and non-autonomous systems. At last, an example is resolved to verify the method.

Special Issue on Innovative Design of Complex Products

With the development of science and technology as well as the diversification and individualization of market demand,modern products update more and more rapidly.e rapid development of new products to satisfy the increasingly improved and personalized customer demands greatly depends on the progress in the innovative design theory and performance optimization

Predicting Model for Complex Production Process Based on Dynamic Neural Network

Based on the comparison of several methods of time series predicting, this paper points out that it is necessary to use dynamic neural network in modeling of complex production process. Because self feedback and mutual feedback are adopted among nodes at the same layer in Elman network, it has stronger ability of dynamic approximation, and can describe any non linear dynamic system. After the structure and mathematical description being given, dynamic back propagation (BP) algorithm of training weights of Elman neural network is deduced. At last, the network is used to predict ash content of black amber in jigging production process. The results show that this neural network is powerful in predicting and suitable for modeling, predicting, and controling of complex production process.

CARBONACEOUS PRODUCTS OF POLYMER-PALLADIUM COMPLEXES AS CATALYSTS FOR THE HYDROGENATION OF METHYL ACRYLATE

Many catalysts were pcrpared by carbonization of ion exchange resin-PdCl_2 complexes at high temperature in nitrogen, hydrogen atmosphere. The rates for the hydrogenation of methyl acrylate and the amounts of Pd elution of the carbonaceous products were measured and compared with those of commercial Pd/C catalyst. It indicates that the carbonaceous products are less active than Pd/C. However, the leaching of Pd from carbonaceous products is very small and much less than that from Pd/C.

A method of manufacturing process modeling based on activity network for large-sized and complex products

Simulation technique is an efficient approach to realize the planning and scheduling of manufacturing process of products. An appropriate and efficient manufacturing process model is the basis and key of manufacturing process simulation. By analyzing the features of large-sized and complex products, a method of manufacturing process modeling based on activity network is presented and a mapping algorithm of translating BOM/BOP into the manufacturing process model is designed in detail.

重复压裂裂缝系统产能对比与分析

单井重复压裂的裂缝生成模式可以分为两种形式,包括在井筒处形成新的转向裂缝以及在原有裂缝的基础上形成扩充缝。如何评价重复压裂后不同形式裂缝系统下油气井的产能,对优化重复压裂施工方案至关重要。以重复压裂产生的两种不同复杂裂缝系统为研究对象,利用嵌入式离散裂缝方法建立数值模型,开展重复压裂后转向型和扩充型裂缝系统的生产规律研究,明确不同裂缝系统对井产能的影响。研究发现:储层及裂缝参数会在不同程度上影响重复压裂后井的产能,且对扩充型裂缝系统的影响程度始终大于转向型裂缝系统。考虑储层基质渗透率各向异性,正交于初始裂缝延伸方向的基质渗透率越大,重复压裂后增产效果越好,并且扩充型裂缝系统累计产量升高更显著。重复压裂裂缝与初始裂缝越趋向于正交,重复压裂后增产效果越明显,扩充型裂缝系统的增产率高于转向型裂缝系统。重复压裂裂缝渗透率和重复压裂裂缝长度均与重复压裂井产能提升呈现正相关,且扩充型裂缝系统的累计产量增大趋势更显著。结果表明,扩充型裂缝系统能更加有效地提高重复压裂井产能,为重复压裂增产机理与矿场应用结合提供理论指导。

生产性服务业与制造业协同集聚对城市创新的影响研究

强化国家战略科技力量,提升国家创新体系整体效能是当今中国加快进入创新型国家前列的重要命题。在构建城市创新质量新指标的基础上,运用空间误差模型和空间滞后模型就生产性服务业与制造业协同集聚对城市创新的影响机制进行深入剖析。研究结果显示:生产性服务业与制造业协同集聚能提升城市创新质量,并能通过推进产业结构高级化、提升城市科技投入水平和吸引研发人员流入三个渠道促进城市创新质量的提升,协同集聚对东部和中部地区城市创新质量有促进作用,高端生产性服务业和低端生产性服务业与制造业协同集聚均能促进城市创新质量提升。此外,生产性服务业与制造业协同集聚能够推动新企业注册量的递增,进而提升城市的创业积极性与创业活跃度。生产性服务业与制造业协同集聚具有促进城市创新质量和创业活力两大功能,可以成为推动城市高质量增长和提升城市竞争力的重要工具。

浅议土的复杂性

土的复杂性使人很难对其严密地定名与分类,几乎不可能精准地预测其行为。土的复杂性来源于其是天然的产物和碎散的颗粒集合体。土的天然属性使其具有三相组成,土中水成为土力学中理论上的难点,也常常是一切地质灾害与工程事故的根源。土力学教学中所谓的土是被简单化了的,与大自然中的原状土有着很大的差别。土的碎散性使其受力变形性状与物理性质相耦合,在受力变形的过程中其组成、状态、结构都处于不断地变化中,这就是其力学性质非常复杂的主要原因。通过DDA(Discontinuous deformation analysis)分析揭示了土颗粒运动与土的各种变形特性间的联系;土的湿化试验表明了塑性应变是度量土的应力-应变特性的主要因素。人类与土之间有着长期的密切的关系,土作为人类的载体、材料、工具与武器,是人类须臾不可离开的东西。在长期的生活与生产过程中,人们积累了关于土的丰富的经验,也吸取了很多教训。至今经验性的方法仍然是在岩土工程的综合判断与工程决策中的基本方法。

复杂产品人工智能生产调度研究

针对复杂产品生产调度协同性不足问题,提出一种基于关键链的多产品人工智能生产调度模式。结合复杂产品时序约束特点,以最小产品拖期和在制品库存为优化目标,搭建了基于关键链的多产品项目人工智能生产调度优化模型,基于遗传算法与模拟退火算法,设计了遗传退火算法(GA-SA)对多产品项目人工智能生产调度优化模型求解,并以某重型机械企业生产的矿渣立磨为例验证了优化模型和智能算法的有效性,实现了复杂产品生产调度精益性和智能性目标,研究结果表明:采用GA-SA+关键链调度方法,产品可以做到准时交付且在制品库存减少24%。

基于光学定位的三维超声引导肌肉注射仪设计研究

目的解决光学定位技术在引入肌肉痉挛治疗的注射手术应用中,光学定位设备与现有医用超声仪器之间的不适配问题,旨在进一步提升理论定位精度稳定性,简化必需操作并降低实际应用难度。方法在现有超声仪及相关设备功能基础上,结合光学定位设备工作条件需求进行需求分析,重新构建产品元件功能流模型并映射为网络节点,并基于复杂网络节点重要度评价方法,确定目标产品设计重心点并分层设计,最后采用仿真验证测试设计合理性。结果实验结果符合预期假设,目标节点所对应功能元件与其它节点的相关性程度与目标元件所需兼容连接的复杂度呈正相关。基于实验得出能够适配光学定位仪与超声设备的设计方案,有效解决二维超声导航引导肌肉注射所面临的不直观、不可视等问题。结论基于复杂网络节点的重要度评价方法更适用于复杂功能产品的设计研究,评价结果重要度差异更为显著。

基于复杂网络的产品族造型意象耦合网络模型构建方法

目的拓展产品族多意象设计相关知识的获取途径,提升产品族造型创新设计的能效。方法基于产品族造型意象耦合特性,引入复杂网络中的多层网络概念,利用造型特征间的多意象表达关系,构建了产品族造型意象耦合网络模型。利用节点敏感性与中心性分析产品族造型意象耦合网络,识别各造型特征节点属性类型以作为模型析出知识。结合产品族设计的特点,总结归纳适用于产品族设计的各造型特征节点类型并制定其类型运用规则,以辅助设计师进行产品族造型创新设计。结果以马自达汽车前脸造型设计为例,构建了马自达汽车前脸造型意象耦合网络模型,析出了产品族相关设计知识并运用于汽车前脸设计。结论产品族造型意象耦合网络模型丰富了产品族多意象设计相关知识的获取途径,可用于辅助产品族设计,提升设计能效。