Design of Feedback Shift Register of Against Power Analysis Attack

Stream ciphers based on linear feedback shift register (LFSR) are suitable for constrained environments, such as satellite communications, radio frequency identification devices tag, sensor networks and Internet of Things, due to its simple hardware structures, high speed encryption and lower power consumption. LFSR, as a cryptographic primitive, has been used to generate a maximum period sequence. Because the switching of the status bits is regular, the power consumption of the LFSR is correlated in a linear way. As a result, the power consumption characteristics of stream cipher based on LFSR are vulnerable to leaking initialization vectors under the power attacks. In this paper, a new design of LFSR against power attacks is proposed. The power consumption characteristics of LFSR can be masked by using an additional LFSR and confused by adding a new filter Boolean function and a flip-flop. The design method has been implemented easily by circuits in this new design in comparison with the others.     

胸腺五肽辅助治疗肺癌对免疫功能影响及其疗效的系统评价

为了系统地评价胸腺五肽作为辅助药物治疗各种肺癌的疗效及其对机体免疫功能的影响，利用电子检索收集有关胸腺五肽联合放疗或化疗方案治疗肺癌的临床随机对照试验文献，对符合纳入标准的文献，采用RevMan5.3 软件进行系统评价。最终共纳入文献 9 篇，总样本量 784 例。Meta 分析结果表明，胸腺五肽作为辅助药物治疗各种肺癌提高总有效率的差异无统计学意义[OR ＝ 1.44, 95%CI(0.99, 2.10), P ＝0.06 ＞ 0.05]。在对免疫功能的影响方面，胸腺五肽的使用显著增高外周血中的 CD3+ 细胞水平[OR ＝ 5.88, 95% CI(2.34, 9.42), P ＝0.001]，CD4+ 细胞水平也显著上升[OR ＝8.32, 95%CI(5.22, 11.42), P ＜ 0.00001] , CD4＋ /CD8＋比值也有明显的提高[OR ＝ 0.38, 95% CI(0.18, 0.59), P＝0.0002]，但 CD8+ 细胞水平的差异无统计学意义[OR ＝－3.12, 95% CI ( －9.02, 2.79), P ＞0.05]。总的来说，本研究在一定程度上反映了在辅助治疗肺癌方面，胸腺五肽能显著提高外周血中的 CD3+ 细胞水平、CD4+ 细胞水平、CD4+/CD8+ 比值。而对于治疗的有效率、CD8+ 细胞水平，差异无统计学意义。     

Extending SSD Lifespan with Comprehensive Non-Volatile Memory-Based Write Buffers

Journal of Computer Science and Technology - New non-volatile memory (NVM) technologies are expected to replace main memory DRAM (dynamic random access memory) in the near future. NAND flash...     

Study on metamerism degree evaluation based on wavelength sensitive cone weighting algorithm

Metamerism phenomenon can be used in illuminant detection to ensure the accuracy of light source. A method based on Long‐, Middle‐, Short‐ wavelength cones(LMS) weighting algorithm to evaluate metamerism degree is proposed. The chromatic relationship between the degree of metamerism mismatch and the light source is studied. Herein, the consistency between the metameric indices (MIs) and CIE1976 L*a*b* color difference ranking is analyzed by SRCC, KRCC, PLCC and RMSE. A statistically sampling method to obtain practical LMS cone fundamentals to evaluate metamerism degree is employed. The analysis results obtained show that the method based on LMS weighting algorithm has good evaluation ability and stability in simulation experiments and statistically sampling experiments, which are in line with visual characteristics of human. Proposed method meets the requirements of selecting metameric pairs used in light source detection. The analysis results have certain guiding significance.     

iM-SIMPLE: iMproved stable increased-throughput multi-hop link efficient routing protocol for Wireless Body Area Networks

Wireless Body Area Networks (WBANs) are envisaged to play crucial role in psychological, medical and non-medical applications. This paper presents iM-SIMPLE; a reliable, and power efficient routing protocol with high throughput for WBAN. We deploy sensor nodes on human body to measure the physiological parameters such as blood pressure, temperature, glucose, lactic acid, EMG, acceleration, pressure, and position. Data from sensors is forwarded to intermediate node, from where it is transmitted to sink. An end user can access the required information available at sink via internet. To minimize energy consumption of the network, we utilize multi-hop mode of communication. A cost function is introduced to select the forwarder; node with high residual energy and least distance to sink has minimum cost function value and is selected. Residual energy parameter balances the energy consumption among the sensor nodes, and least distance improves packet delivery to sink because of reduced less path loss. We formulate the minimum energy consumption and high throughput problems as an Integer Linear Program. In order to support mobility, we also consider two body postures. Simulation results confirm the performance advantage of iM-SIMPLE compared to contemporary schemes in terms of maximizing stability period and throughput of the network.     

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

Cell Sheet Comprised of Mesenchymal Stromal Cells Overexpressing Stem Cell Factor Promotes Epicardium Activation and Heart Function Improvement in a Rat Model of Myocardium Infarction

Cell therapy of the post-infarcted myocardium is still far from clinical use. Poor survival of transplanted cells, insufficient regeneration, and replacement of the damaged tissue limit the potential of currently available cell-based techniques. In this study, we generated a multilayered construct from adipose-derived mesenchymal stromal cells (MSCs) modified to secrete stem cell factor, SCF. In a rat model of myocardium infarction, we show that transplantation of SCF producing cell sheet induced activation of the epicardium and promoted the accumulation of c-kit positive cells in ischemic muscle. Morphometry showed the reduction of infarct size (16%) and a left ventricle expansion index (0.12) in the treatment group compared to controls (24–28%; 0.17–0.32). The ratio of viable myocardium was more than 1.5-fold higher, reaching 49% compared to the control (28%) or unmodified cell sheet group (30%). Finally, by day 30 after myocardium infarction, SCF-producing cell sheet transplantation increased left ventricle ejection fraction from 37% in the control sham-operated group to 53%. Our results suggest that, combining the genetic modification of MSCs and their assembly into a multilayered construct, we can provide prolonged pleiotropic effects to the damaged heart, induce endogenous regenerative processes, and improve cardiac function.