3D soft-tissue tracking using spatial-color joint probability distribution and thin-plate spline model

Visual tracking techniques based on stereo endoscope are developed to measure tissue motion in robot-assisted minimally invasive surgery. However, accurate 3D tracking of tissue surfaces remains challenging due to complicated deformation, poor imaging conditions, specular reflections and other dynamic effects during surgery. This study employs a robust and efficient 3D tracking scheme with two independent recursive processes, namely kernel-based inter-frame motion estimation and model-based intra-frame 3D matching. In the first process, target region is represented in joint spatial-color space for robust estimation. By defining a probabilistic similarity measure, a mean-shift-based iterative algorithm is derived for location of the target region in a new image. In the second process, the thin-plate spline model is used to fit the 3D shape of tissue surfaces around the target region. An iterative algorithm based on an efficient second-order minimization technique is derived to compute optimal model parameters. The two processes can be computed in parallel. Their outputs are combined to recover 3D information about the target region. The performance of the proposed method is validated using phantom heart videos and in vivo videos acquired by the daVinci^®${\mathrm{daVinci}}^{\circledR }$ surgical robotic platform and a synthesized data set with known ground truth.     

Discriminative multi-task objects tracking with active feature selection and drift correction

In this paper, we propose a discriminative multi-task objects tracking method with active feature selection and drift correction. The developed method formulates object tracking in a particle filter framework as multi-Task discriminative tracking. As opposed to generative methods that handle particles separately, the proposed method learns the representation of all the particles jointly and the corresponding coefficients are similar. The tracking algorithm starts from the active feature selection scheme, which adaptively chooses suitable number of discriminative features from the tracked target and background in the dynamic environment. Based on the selected feature space, the discriminative dictionary is constructed and updated dynamically. Only a few of them are used to represent all the particles at each frame. In other words, all the particles share the same dictionary templates and their representations are obtained jointly by discriminative multi-task learning. The particle that has the highest similarity with the dictionary templates is selected as the next tracked target state. This jointly sparsity and discriminative learning can exploit the relationship between particles and improve tracking performance. To alleviate the visual drift problem encountered in object tracking, a two-stage particle filtering algorithm is proposed to complete drift correction and exploit both the ground truth information of the first frame and observations obtained online from the current frame. Experimental evaluations on challenging sequences demonstrate the effectiveness, accuracy and robustness of the proposed tracker in comparison with state-of-the-art algorithms.     

Fisher discrimination based low rank matrix recovery for face recognition

In this paper, we consider the issue of computing low rank (LR) recovery of matrices with sparse errors. Based on the success of low rank matrix recovery in statistical learning, computer vision and signal processing, a novel low rank matrix recovery algorithm with Fisher discrimination regularization (FDLR) is proposed. Standard low rank matrix recovery algorithm decomposes the original matrix into a set of representative basis with a corresponding sparse error for modeling the raw data. Motivated by the Fisher criterion, the proposed FDLR executes low rank matrix recovery in a supervised manner, i.e., taking the with-class scatter and between-class scatter into account when the whole label information are available. The paper shows that the formulated model can be solved by the augmented Lagrange multipliers and provides additional discriminating power over the standard low rank recovery models. The representative bases learned by the proposed method are encouraged to be closer within the same class, and as far as possible between different classes. Meanwhile, the sparse error recovered by FDLR is not discarded as usual, but treated as a feedback in the following classification tasks. Numerical simulations demonstrate that the proposed algorithm achieves the state of the art results.     

Subcarrier allocation in multi-hop orthogonal frequency division multiple access wireless networks

Orthogonal frequency division multiplexing (OFDM) has been widely considered as a key technique for next generation mobile communication systems. Meanwhile, relaying technologies can improve users’ quality of service, increase network capacity and enlarge cellular coverage at a low cost. In this paper, we focus on subcarrier allocation and utilization in multi-hop OFDM access (OFDMA) wireless networks, and propose two efficient subcarrier allocation schemes aiming to increase network throughput and subcarrier utilization. The first scheme selects suitable links for data transmission from base stations to terminals at the beginning. Then, interference-free links are included into the same group for network resource reuse. For the purpose of global optimization, we propose a Tabu-based searching algorithm as the second subcarrier allocation scheme. Simulation results demonstrate that our proposed algorithms outperform other schemes in both network throughput and subcarrier utilization.     

Transport property measurements in sheared granular flows

Experiments were performed in a shear cell device under four different solid fractions. The glass spheres with a mean diameter of 3 mm were used as granular materials. The motions of the granular materials were recorded by a high-speed camera. By using image processing technology and a particle tracking method, the average and fluctuation velocities in the streamwise and the transverse directions could be successfully measured and analyzed. Three bi-directional stress gages were used to measure the normal and shear stresses along the upper boundary. The effective viscosity of the granular material flow can be calculated. By tracking the movements of particles continually, the curves of the mean-square diffusive displacements versus time were plotted and were used to determine the self-diffusion coefficients from the slopes of the curves. The fluctuations and the self-diffusion coefficients in the streamwise direction were much higher than those in the transverse direction. The fluctuations were found to increase with the solid fraction, but the diffusion coefficients were greater in a more dilute flow system.     

3600煤气发生炉系统优化设计

分析了传统 36 0 0造气工艺流程存在的缺点 ,针对邯钢集团化肥公司的实际情况并配合 12 2 0工程的顺利实施 ,决定采用设备紧凑、发气量大、工艺设备较先进的 36 0 0煤气发生炉系统。在该系统的设计中 ,除了采用新型高效旋风除尘器和联合热管锅炉回收器外 ,还充分吸收了近年来我国造气技术涌现出来的先进技术装备     

离子自拆分法合成D-(一)-对羟基苯甘氨酸

研究了用离子自拆分方法拆分外消旋对羟基苯甘氨酸(DL-HPG)而合成D-(—)-对羟基苯甘氨酸(D-HPG)。采用正交试验确定了最佳反应条件:在丙酮和水的混合溶剂中,等物质的量的DL-HPG和硫酸在60℃下加入D-HPG,搅拌反应15min左右,降温过滤得到D-HPG的硫酸盐,水解即可得到D-HPG(光学纯度99％),一次性总收率达到20％。适于工业生产。     

露天开采下盘无台阶采矿法

新桥硫矿首次在国内推行露天开采下盘无台阶采矿新工艺,该工艺具有剥岩少、基建快、出矿早、采矿工程延深快等特点。由于该工艺具有独特的靠帮方式和端部过渡方式,需严格控制底盘因爆破而导致的岩体滑动。该工艺的实施已取得了显著的经济效益。     

新型离子液体气相色谱固定相研究

合成了一种用作新型气相色谱固定相的室温离子液体[C7H17NO] [(CF3SO2)2N]-,并考察其色谱性能。该固定相具有较好的成膜性、较高的柱效、较强的极性,对正构烷烃、芳香族化合物以及一些位置异构体具有良好的分离效果。