火箭弹道附近大气参数辨识系统的研究

研究了利用雷达实测数据对沿火箭飞行弹道的大气参数进行辨识和外推落点的方法，进而提出了一个对效力射诸元进行修正的方法。在此基础上，对软件系统进行了设计。最后通过仿真试验，分析了系统的准确性。     

乳状液膜法制备草酸稀土

系统研究了在乳状液膜内水相直接制备草酸稀土的方法，讨论了内水相草酸浓度、表面活性剂浓度、载体浓度、外水相酸度和外水相稀土浓度对迁移率的影响，找到了制备草酸稀土的最佳条件，草酸稀土经灼烧所得的氧化物含ＲＥ２Ｏ３〉９９．５％，与萃取法相比，此方法具有成本低、能耗少、污染程度低的特点，具有工业化前景。     

筒形件反旋工艺塑性流动刚塑性有限元分析

建立了筒形件反旋工艺平面变形刚塑性有限元分析的力学模型，比较了把反旋工艺视为正挤和本文力学模型条件下的速度场，有限元分析结果与反旋实际条件相符。     

全数字高清晰度电视中8—VSB传输系统

分析了全数字高清晰度电视（ＨＤＴＶ）中地面广播信道的干扰及抑制措施，给出了抑制同频干扰的梳状滤波器的设计方法和ＨＤＴＶ中８－ＶＳＢ基本原理及传输方案，并基于传信率１／Ｔ＝２３．５４８Ｍｂｐｓ的８－ＶＳＢ作了计算机模拟。     

带平衡约束矩形布局优化问题的深度强化学习算法

带平衡约束的矩形布局问题源于卫星舱设备布局设计,属于组合优化问题。深度强化学习利用奖赏机制,通过数据训练实现高性能决策优化。针对布局优化问题,提出一种基于深度强化学习的新算法DAR及其扩展算法IDAR。DAR用指针网络输出定位顺序,再利用定位机制给出布局结果,算法的时间复杂度是O（n³）;IDAR算法在DAR的基础上引入迭代机制,算法时间复杂度是O（n⁴）,但能给出更好的结果。测试表明DAR算法具有较好的学习能力,用小型布局问题进行求解训练所获得的模型,能有效应用在大型问题上。在两个大规模典型算例的对照实验中,提出算法分别超出和接近目前最优解,具有时间和质量上的优势。     

Fracture mechanics of a shaft-loaded blister of thin flexible membrane on rigid substrate

A shaft-loaded blister test has been developed to measure the interfacial energy W of a thin flexible polymeric film adhered to a rigid substrate. A theoretical analysis is given of an axisymmetric debond (blister) in terms of an external applied load P, tensile stretching modulus E and thickness h of the adhering layer. The fracture mechanics model presented considers both elastic and elastoplastic deformations in the thin film. The intrinsic stable interface debonding process provides an attractive alternative to the conventional adhesion measurement techniques.     

An iterative gradient convolutional neural network and its application in endoscopic photoacoustic image formation from incomplete acoustic measurement

Neural Computing and Applications - Endoscopic photoacoustic tomography (EPAT) is a rapidly developing catheter-based imaging technique to provide cross-sectional images of anatomical, functional...     

A new look at software piracy: Soft lifting primes an inauthentic sense of self,prompting further unethical behavior

Soft lifting refers to the process whereby a legally licensed software program is installed or copied in violation of its licensing agreement. Previous research on this pervasive kind of unethical computer use has mainly focused on the determinants of this unethical act, which are rooted in personal, economic, technological, cultural, socio-political, or legal domains. However, little is known about the symbolic power that soft lifting has on the sense of self. Based on recent advances in behavioral priming, we hypothesized that soft lifting can influence the signals one sends to oneself; more specifically, soft lifting may prime individuals to experience an inauthentic sense of self, which, in turn, prompts further unethical behavior. In Study 1, we showed that participants, primed with the memory of a recent soft lifting experience, cheated more than participants recalling a recent experience of purchasing authentic software or than control participants. Moreover, feelings of inauthenticity mediated the priming effect of soft lifting on dishonest behavior. In Study 2, participants primed with soft lifting showed a greater willingness to purchase a wide range of counterfeit products over authentic products. Besides those antecedents or correlates of soft lifting already identified in the literature, educators should pay more attention to the negative impact of soft lifting on the self-images of users, which may go beyond computer-related behaviors. Priming may provide a new direction for HCI researchers to examine the impact of computer-use-related factors on users' perceptions, motivations, and behaviors.     

Simple culling methods for continuous collision detection of deforming triangles

We present a simple and efficient approach for continuous collision detection of deforming triangles based on conservative advancement. The efficiency of our approach is due to a sequence of simple collision-free conditions for deforming triangles. In our experiment, we show that our CCD algorithm achieves 2-30 times performance improvement over existing algorithms for triangle primitives.     

Data-driven facial expression synthesis via Laplacian deformation

Realistic talking heads have important use in interactive multimedia applications. This paper presents a novel framework to synthesize realistic facial animations driven by motion capture data using Laplacian deformation. We first capture the facial expression from a performer, then decompose the motion data into two components: the rigid movement of the head and the change of the facial expression. By making use of the local-detail preserving property of the Laplacian coordinate, we clone the captured facial expression onto a neutral 3D facial model using Laplacian deformation. We choose some expression “independent points” in the facial model as the fixed points when solving the Laplacian deformation equations. Experimental results show that our approach can synthesize realistic facial expressions in real time while preserving the facial details. We compare our method with the state-of-the-art facial expression synthesis methods to verify the advantages of our method. Our approach can be applied in real-time multimedia systems.