泛代数上的Groebner-Shirshov基理论

综述了域上或交换代数上的线性（-）代数的相应的簇（范畴）的 Groebner-Shirshov 基理论的新成果，如:结合代数（包括群（半群）代数），自由代数的张量积，李代数，Di-代数，pre-李代数，Rota-Baxter代数，metabelian李代数，L-代数，半环代数，范畴代数，等．以上结果包含了许多应用，尤其是给出了一些著名结论的新的证明．     

Preface to the Special Topic on Computer Mathematics

Journal of Systems Science and Complexity -     

带漂移布朗运动的一个局部时的Laplace变换

在Borodin和Salminen(2002)文献中有关带漂移布朗运动占位时的Laplace变换结果的基础上,运用Li等(2014)计算局部时的方法,推出了带漂移布朗运动在独立指数时间e_q前,及停留在0处的局部时的Laplace变换表达式Ee~(-λl(e_q,0))=lima→0I(λ/a;0,a,e_q)=((2q+μ~2)~(1/2))/(λ+(2q+μ~2)~(1/2))。当μ=0时,本文结果与标准布朗运动的结果吻合。     

采用Sn中介层的覆Al薄膜硅片键合技术研究

研究采用Sn作为中间层键合覆盖Al薄膜的硅片。相对于Al-Al直接热压键合,该系统能提供低温、低压、快速的圆片级键合方案。采用直径为100 mm硅片,溅射一层500 nm厚度的Al层后,在N2气氛下进行450°C,30分钟退火,采用Ar等离子体清洗后,溅射一层500 nm厚度的Sn层。将硅片金属面紧贴在一起放入键合机中键合,在真空中进行。键合时间为3分钟条件下,得到平均剪切强度为9.9 MPa,随着键合时间增加,剪切强度显著降低。     

System optimization model of adoption of a new infrastructure with multi-resource and multi-demand sites

This study develops a conceptual system optimization model of adoption of a new infrastructure technology with multiple resource sites and multiple demand sites. With the model, this paper analyzes how the distance, spillover effect, demand, initial investment cost, and learning rate influence the adoption of the new infrastructure technology and presents optimization results of the model in different scenarios. The main findings of the study are: from the perspective of system optimization, (1) different distances among different resource-demand pairs will result in different adoption time of a new infrastructure; (2) technological spillover among different resource-demand pairs will accelerate the adoption of a new infrastructure; (3) it is hard to say that higher demand will pull faster adoption of a new infrastructure, and the optimal time of adopting of a new infrastructure is very sensitive to its technological learning rate.     

Secure pairing with wearable devices by using ambient sound and light

Wearable devices usually work together with smart phones. To ensure only legitimate smart phones can read the data, they must conduct pairing to establish a shared key. Traditional pairing methods require that the pairing devices have a keyboard or screen for user interaction. However, due to the size limitation, keyboards or screens are hard to be installed in the wearable devices. To solve this problem, we propose a novel pairing method by using ambient sound and light. In this new scheme, any pairing request from smart phone will trigger wearable device vibration. Only after users press the confirm key on the device can the pairing process continues. Then pairing devices collect ambient sound and light at the predetermined time and establish a shared key by using the Diffie-Hellman protocol. To protect against potential man-in-the-middle attacks in the key establishment process, an improved interlock protocol with sound and light comparison is conducted to authenticate the key. If both the sound and light collected by the pairing devices are similar enough, the key is accepted. Otherwise, it is rejected. Compared with current context based pairing methods, our scheme does not impose strict synchronization on devices to collect ambient context data. Moreover, our scheme need not collect and exchange contextual information for multiple times to resist offline brute force attacks. The experimental results and security analysis prove the effectiveness of our scheme.     

电阻绝缘检测中低压脉冲信号注入法的算法改进

在有源式低压脉冲信号注入法的基础上,重新推导了计算电阻值的数学模型,并设计了一种运用该模型的有源式动力电池绝缘电阻监测系统,该系统可以有效地解决部分无源式和有源式绝缘检测法无法有效精确测量同时下降的正负端绝缘电阻与正负端单侧绝缘电阻的问题.此外,通过台架实验验证了该监测系统的有效性,在改进电动汽车动力电池监测系统方面具有一定的应用价值.     

有界复形的 Modi ed Ringel Hall 代数的结构常数

设k是有限域.A是k上的满足一定有限性条件的本质小的遗传阿贝尔范畴.本文研究了有界复形范畴的modified Ringel—Hall 代数MH(A)中零微分复形乘积的结构常数，给出了它们与A的Ringel-Hall 代数H(A)的Hall数之间的关系.     

C3N4/ZnO复合材料可见光下的甲醛光电气敏性能

以水热法合成的ZnO纳米棒花为载体,将C_3N_4定量负载在其表面,制备C_3N_4/ZnO复合材料.由于C_3N_4与ZnO的能级匹配,可有效促进其光生电荷的分离,降低光生电荷复合率,显著提高载流子浓度,使其光电流明显增加.C_3N_4与ZnO质量比为2%的样品(2%C_3N_4/ZnO)性能最佳,其光电流在370 nm处可达120μA,为纯ZnO的2.4倍.在室温可见光下,2%C_3N_4/ZnO样品对HCHO的光电气敏响应值可达122%,比纯ZnO高4倍左右.结果表明,适量C_3N_4的负载有效延长了光生电荷的寿命,使ZnO材料在可见光区对HCHO气体表现出高效的光电气敏性能.     

Efficient Feature Extraction Using Apache Spark for Network Behavior Anomaly Detection

Extracting and analyzing network traffic feature is fundamental in the design and implementation of network behavior anomaly detection methods. The traditional network traffic feature method focuses on the statistical features of traffic volume. However, this approach is not sufficient to reflect the communication pattern features. A different approach is required to detect anomalous behaviors that do not exhibit traffic volume changes,such as low-intensity anomalous behaviors caused by Denial of Service/Distributed Denial of Service(Do S/DDo S)attacks, Internet worms and scanning, and Bot Nets. We propose an efficient traffic feature extraction architecture based on our proposed approach, which combines the benefit of traffic volume features and network communication pattern features. This method can detect low-intensity anomalous network behaviors and conventional traffic volume anomalies. We implemented our approach on Spark Streaming and validated our feature set using labelled real-world dataset collected from the Sichuan University campus network. Our results demonstrate that the traffic feature extraction approach is efficient in detecting both traffic variations and communication structure changes.Based on our evaluation of the MIT-DRAPA dataset, the same detection approach utilizes traffic volume features with detection precision of 82.3% and communication pattern features with detection precision of 89.9%. Our proposed feature set improves precision by 94%.