Molecular Dynamics, Physical Properties, Diffusion Coefficients and Activation Energy of the Lithium Oxide (Li-O) and Sodium Oxide (Na-O) Electrolyte (Cathode)

This work is a simulation model with the LAMMPS calculation code of an electrode based on alkali metal oxides (lithium, sodium and potassium) using the Lennard Jones potential. For a multiplicity of 8*8*8, we studied a gap-free model using molecular dynamics. Physical quantities such as volume and pressure of the Na-O and Li-O systems exhibit similar behaviors around the thermodynamic ensembles NPT and NVE. However, for the Na2O system, at a minimum temperature value, we observe a range of total energy values;in contrast, for the Li2O system, a minimum energy corresponds to a range of temperatures. Finally, for physicochemical properties, we studied the diffusion coefficient and activation energy of lithium and potassium oxides around their melting temperatures. The order of magnitude of the diffusion coefficients is given by the relation Dli-O >DNa-O for the multiplicity 8*8*8, while for the activation energy, the order is well reversed EaNa-O > EaLi-O.

Repeated sending file delivery protocol in satellite networking communication

Satellite networking communications in navigation satellite system and spacebased deep space exploration have the features of a long delay and high bit error rate （BER）. Through analyzing the advantages and disadvantages of the Consulta tive Committee for the Space Data System （CCSDS） file delivery protocol （CFDP）, a new improved repeated sending file delivery protocol （RSFDP） based on the adaptive repeated sending is put forward to build an efficient and reliable file transmission. According to the estimation of the BER of the transmission link, RSFDP repeatedly sends the lost protocol data units （PDUs） at the stage of the retransmission to improve the success rate and reduce time of the retransmission. Theoretical analyses and results of the Opnet simulation indicate that the performance of RSFDP has significant improvement gains over CFDP in the link with a long delay and high BER. The realizing results based on the space borne filed programmable gate array （FPGA） platform show the applicability of the proposed algorithm.

A novel clustering and supervising users' profiles method

To better understand different users' accessing intentions, a novel clustering and supervising method based on accessing path is presented. This method divides users' interest space to express the distribution of users' interests, and directly to instruct the constructing process of web pages indexing for advanced performance.

ERROR COUNTER-BASED NEGATIVE ACKNOWLEDGEMENT MODE IN CCSDS FILE DELIVERY PROTOCOL

Deep space communication has its own features such as long propagation delays,heavy noise,asymmetric link rates,and intermittent connectivity in space,therefore TCP/IP protocol cannot perform as well as it does in terrestrial communications.Accordingly,the Consultative Committee for Space Data Systems(CCSDS) developed CCSDS File Delivery Protocol(CFDP),which sets standards of efficient file delivery service capable of transferring files to and from mass memory located in the space segment.In CFDP,four optional acknowledge modes are supported to make the communication more reliable.In this paper,we gave a general introduction of typical communication process in CFDP and analysis of its four Negative Acknowledgement(NAK) modes on the respect of file delivery delay and times of retransmission.We found out that despite the shortest file delivery delay,immediate NAK mode suffers from the problem that frequent retransmission may probably lead to network congestion.Thus,we proposed a new mode,the error counter-based NAK mode.By simulation of the case focused on the link between a deep space probe on Mars and a ter-restrial station on Earth,we concluded that error counter-based NAK mode has successfully reduced the retransmission times at negligible cost of certain amount of file delivery delay.

MobSafe:Cloud Computing Based Forensic Analysis for Massive Mobile Applications Using Data Mining

With the explosive increase in mobile apps, more and more threats migrate from traditional PC client to mobile device. Compared with traditional Win＋Intel alliance in PC, Android＋ARM alliance dominates in Mobile Internet, the apps replace the PC client software as the major target of malicious usage. In this paper, to improve the security status of current mobile apps, we propose a methodology to evaluate mobile apps based on cloud computing platform and data mining. We also present a prototype system named MobSafe to identify the mobile app＇s virulence or benignancy. Compared with traditional method, such as permission pattern based method, MobSafe combines the dynamic and static analysis methods to comprehensively evaluate an Android app. In the implementation, we adopt Android Security Evaluation Framework （ASEF） and Static Android Analysis Framework （SAAF）, the two representative dynamic and static analysis methods, to evaluate the Android apps and estimate the total time needed to evaluate all the apps stored in one mobile app market. Based on the real trace from a commercial mobile app market called AppChina, we can collect the statistics of the number of active Android apps, the average number apps installed in one Android device, and the expanding ratio of mobile apps. As mobile app market serves as the main line of defence against mobile malwares, our evaluation results show that it is practical to use cloud computing platform and data mining to verify all stored apps routinely to filter out malware apps from mobile app markets. As the future work, MobSafe can extensively use machine learning to conduct automotive forensic analysis of mobile apps based on the generated multifaceted data in this stage.

The NUBASE2016 evaluation of nuclear properties

This paper presents the NUBASE2016 evaluation that contains the recommended values for nuclear and decay properties of 3437 nuclides in their ground and excited isomeric （T1/2〉 100 ns） states. All nuclides for which any experimental information is known were considered. NUSASE2016 covers all data published by October 2016 in primary （journal articles） and secondary （mainly laboratory reports and conference proceedings） references, together with the corresponding bibliographical information. During the development of NUBASE2016, the data available in the ＂Evaluated Nuclear Structure Data File＂ （ENSDF） database were consulted and critically assessed for their validity and completeness. Furthermore, a large amount of new data and some older experimental results that were missing from ENSDF were compiled, evaluated and included in NUBASE2016. The atomic mass values were taken from the ＂Atomic Mass Evaluation＂ （AME2016, second and third parts of the present issue）. In cases where no experimental data were available for a particular nuclide, trends in the behavior of specific properties in neighboring nuclides （TNN） were examined. This approach allowed to estimate values for a range of properties that are labeled in NUBASE2016 as ＂non-experimental＂ （flagged ＂#＂）. Evaluation procedures and policies used during the development of this database are presented, together with a detailed table of recommended values and their uncertainties.