Quality and Emulsion Stability of Milk from Ettawah Crossed Bred Goat During Frozen Storage

Goat milk has specific chemical composition and physical properties. The purpose of this study was to investigate the change of milk quality and emulsion stability during 60 d frozen storage. Milk sample was taken from three Ettawah Crossedbred goats that were divided into three groups. Samples were frozen and stored for 0, 30 and 60 days. At the end of each storage periode, milk sample was thawed in the refrigerator and analyzed for total number of bacteria, chemical (acidity, pH, free fatty acids), physical (alcohol test, clot on boiling test) quality, and emulsion stability. The microbiological and chemical data were analyzed statistically using one way ANOVA, whereas physical quality and emulsion stabilty were expressed qualitatively. There were no change in the total bacteria, acidity, pH and free fatty acid (FFA) of milk during storage, whereas the assessment by 70% alcohol showed positive since 0 d. Emulsions stability changed after 30 d of storage. While, the clot on boiling (COB) test of milk was positive at 60 d of storage. Recommendation is frozen storage of goat milk should not longer than 30 d.     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

A globally convergent BFGS method for pseudo-monotone variational inequality problems

In this paper, we propose a globally convergent BFGS method to solve Variational Inequality Problems (VIPs). In fact, a globalization technique on the basis of the hyperplane projection method is applied to the BFGS method. The technique, which is independent of any merit function, is applicable for pseudo-monotone problems. The proposed method applies the BFGS direction and tries to reduce the distance of iterates to the solution set. This property, called Fejer monotonicity of iterates with respect to the solution set, is the basis of the convergence analysis. The method applied to pseudo-monotone VIP is globally convergent in the sense that subproblems always have unique solutions, and the sequence of iterates converges to a solution to the problem without any regularity assumption. Finally, some numerical simulations are included to evaluate the efficiency of the proposed algorithm.     

Multiple Empirical Kernel Learning with Majority Projection for imbalanced problems

Traditional Multiple Empirical Kernel Learning (MEKL) expands the expressions of the sample and brings better classification ability by using different empirical kernels to map the original data space into multiple kernel spaces. To make MEKL suit for the imbalanced problems, this paper introduces a weight matrix and a regularization term into MEKL. The weight matrix assigns high misclassification cost to the minority samples to balanced misclassification cost between minority and majority class. The regularization term named Majority Projection (MP) is used to make the classification hyperplane fit the distribution shape of majority samples and enlarge the between-class distance of minority and majority class. The contributions of this work are: (i) assigning high cost to minority samples to deal with imbalanced problems, (ii) introducing a new regularization term to concern the property of data distribution, (iii) and modifying the original PAC-Bayes bound to test the error upper bound of MEKL-MP. Through analyzing the experimental results, the proposed MEKL-MP is well suited to the imbalanced problems and has lower generalization risk in accordance with the value of PAC-Bayes bound.     

A New NTRU-Type Public-Key Cryptosystem over the Binary Field

As the development of cloud computing and the convenience of wireless sensor netowrks, smart devices are widely used in daily life, but the security issues of the smart devices have not been well resolved. In this paper, we present a new NTRU-type public-key cryptosystem over the binary field. Specifically, the security of our scheme relies on the computational intractability of an unbalanced sparse polynomial ratio problem (DUSPR). Through theoretical analysis, we prove the correctness of our proposed cryptosystem. Furthermore, we implement our scheme using the NTL library, and conduct a group of experiments to evaluate the capabilities and consuming time of encryption and decryption. Our experiments result demonstrates that the NTRU-type public-key cryptosystem over the binary field is relatively practical and effective.     

Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.     

The generalized discrete ‐centroid problem

The ‐centroid problem or leader–follower problem is generalized considering different customer choice rules where a customer may use facilities belonging to different firms, if the difference in travel distance (or time) is small enough. Assuming essential goods, some particular customer choice rules are analyzed. Linear programming formulations for the generalized ‐medianoid and ‐centroid problems are presented and an exact solution approach is applied. Some computational examples are included.     

Semirigid inclusions in elastic bodies: Mechanical interplay and optimal control

The paper concerns an analysis of an equilibrium problem for 2D elastic body with two semirigid inclusions. It is assumed that inclusions have a joint point, and we investigate a junction problem for these inclusions. The existence of solutions is proved, and different equivalent formulations of the problem are proposed. We investigate a convergence to infinity of a rigidity parameter of the semirigid inclusion. It is proved that in the limit, we obtain an equilibrium problem for the elastic body with a rigid inclusion and a semirigid one. A parameter identification problem is investigated. In particular, the existence of a solution to a suitable optimal control problem is proved.     

Controlled Secure Direct Communication Protocol via the Three-Qubit Partially Entangled Set of States

In this paper, we first re-examine the previous protocol of controlled quantum secure direct communication of Zhang et al.’s scheme, which was found insecure under two kinds of attacks, fake entangled particles attack and disentanglement attack. Then, by changing the party of the preparation of cluster states and using unitary operations, we present an improved protocol which can avoid these two kinds of attacks. Moreover, the protocol is proposed using the three-qubit partially entangled set of states. It is more efficient by only using three particles rather than four or even more to transmit one bit secret information. Given our using state is much easier to prepare for multiqubit states and our protocol needs less measurement resource, it makes this protocol more convenient from an applied point of view.     

基于局部分型面的电器外壳注塑模具设计

电器外壳制品形状结构复杂,有两处侧凸(孔)较难处理。通过对矩形孔内侧凸的结构分析,在其局部设计了分型面,避免了使用侧向抽芯机构;对侧孔部位设计了斜顶杆侧向抽芯机构,其结构简单、紧凑。模具采用一模二腔、平衡式布局,采用经扁推杆由制品内部进料的潜伏式浇口,S型流道。在NX 8.0中完成了模具结构设计。经实践证明,该模具结构合理,产品合格。