Toward a Comparison of Classical and New Privacy Mechanism

In the last decades, the development of interconnectivity, pervasive systems, citizen sensors, and Big Data technologies allowed us to gather many data from different sources worldwide. This phenomenon has raised privacy concerns around the globe, compelling states to enforce data protection laws. In parallel, privacy-enhancing techniques have emerged to meet regulation requirements allowing companies and researchers to exploit individual data in a privacy-aware way. Thus, data curators need to find the most suitable algorithms to meet a required trade-off between utility and privacy. This crucial task could take a lot of time since there is a lack of benchmarks on privacy techniques. To fill this gap, we compare classical approaches of privacy techniques like Statistical Disclosure Control and Differential Privacy techniques to more recent techniques such as Generative Adversarial Networks and Machine Learning Copies using an entire commercial database in the current effort. The obtained results allow us to show the evolution of privacy techniques and depict new uses of the privacy-aware Machine Learning techniques.     

Efficiency of Classical and Quantum Games Equilibria

Nash equilibria and correlated equilibria of classical and quantum games are investigated in the context of their Pareto efficiency. The examples of the prisoner’s dilemma, battle of the sexes and the game of chicken are studied. Correlated equilibria usually improve Nash equilibria of games but require a trusted correlation device susceptible to manipulation. The quantum extension of these games in the Eisert–Wilkens–Lewenstein formalism and the Frąckiewicz–Pykacz parameterization is analyzed. It is shown that the Nash equilibria of these games in quantum mixed Pauli strategies are closer to Pareto optimal results than their classical counter-parts. The relationship of mixed Pauli strategies equilibria and correlated equilibria is also studied.     

Application of Euler Neural Networks with Soft Computing Paradigm to Solve Nonlinear Problems Arising in Heat Transfer

In this study, a novel application of neurocomputing technique is presented for solving nonlinear heat transfer and natural convection porous fin problems arising in almost all areas of engineering and technology, especially in mechanical engineering. The mathematical models of the problems are exploited by the intelligent strength of Euler polynomials based Euler neural networks (ENN’s), optimized with a generalized normal distribution optimization (GNDO) algorithm and Interior point algorithm (IPA). In this scheme, ENN’s based differential equation models are constructed in an unsupervised manner, in which the neurons are trained by GNDO as an effective global search technique and IPA, which enhances the local search convergence. Moreover, a temperature distribution of heat transfer and natural convection porous fin are investigated by using an ENN-GNDO-IPA algorithm under the influence of variations in specific heat, thermal conductivity, internal heat generation, and heat transfer rate, respectively. A large number of executions are performed on the proposed technique for different cases to determine the reliability and effectiveness through various performance indicators including Nash–Sutcliffe efficiency (NSE), error in Nash–Sutcliffe efficiency (ENSE), mean absolute error (MAE), and Thiel’s inequality coefficient (TIC). Extensive graphical and statistical analysis shows the dominance of the proposed algorithm with state-of-the-art algorithms and numerical solver RK-4.     

基于差分Pattern时延差编码和海豚whistles信号的仿生水声通信技术研究

为解决传统的隐蔽水声通信方法带来的通信性能降低问题, 提出了一种将差分 Pattern 时延差编码通信体制与海豚whistles信号相结合的仿生水声通信技术. 海豚whistles信号频带较窄且各信息码元间隔不等、码元之间互相关性较弱, 选取whistles信号作同步码和Pattern 码, 并以相邻whistles信号之间的时延差值携带信息. 这种仿生的水声通信信号不易被敌方探测、截获, 且差分Pattern时延差特殊的编码方式也不易使信息被破译, 因此该水声通信技术具有较强的隐蔽性和保密性, 且在抗码间干扰以及抗多普勒效应方面具有优异性能. 本文对系统进行了水池实验, 在信噪比为0 dB、存在相对运动时实现了通信速率为67 bit/s的低误码数据传输, 验证了系统的有效性、稳健性和隐蔽性. 关键词： 仿生水声通信 差分Pattern时延差编码 海豚whistles信号 隐蔽性     

Coevolutionary,coexisting learning and teaching agents model for prisoner’s dilemma games enhancing cooperation with assortative heterogeneous networks

Unlike other natural network systems, assortativity can be observed in most human social networks, although it has been reported that a social dilemma situation represented by the prisoner’s dilemma favors dissortativity to enhance cooperation. We established a new coevolutionary model for both agents’ strategy and network topology, where teaching and learning agents coexist. Remarkably, this model enables agents’ enhancing cooperation more than a learners-only model on a time-frozen scale-free network and produces an underlying assortative network with a fair degree of power-law distribution. The model may imply how and why assortative networks are adaptive in human society.     

Effect of Temperature and Comonomer Content on Thermal Behavior and Crystallization Property of the Propylene–Ethylene Random Copolymers

The effects of ethylene units content and crystallization temperature on the conformations, and the thermal and crystallization behavior were investigated by a combination of Fourier transform infrared (FTIR) spectroscopy, wide angle X-ray diffraction (WAXD), and differential scanning calorimetry (DSC). The characterization of FTIR spectroscopy proves that the longer helical conformation sequences of the propylene–ethylene random (PER) samples decrease, whereas the shorter helical conformation sequences increase with the increase in ethylene units content. The increase of the shorter helical conformation sequences is favorable for the formation of the γ-phase in the crystals. A group of broad endothermic peaks can be seen clearly in the DSC curves of PER copolymers, which may be associated with the melting of mixtures of the α- and γ-forms in the crystals. The melting point, crystallization temperature, and crystallinity degree of the PER copolymers decrease with the increase in ethylene units contents. Three typical melting peaks of the PER copolymers crystallized isothermally between 80°C and 130°C were observed. The two higher melting peaks result from melting of the α- and γ-phase in the crystals, whereas the materials crystallized on quenching give the lowest peak. The WAXD results confirm that the PER copolymers crystallize from the melt, as mixtures of α and γ forms, in a wide temperature range. The critical number ζ_lim of the crystallizable units for the α-form increases with the increase in crystallization temperature for PER copolymers, which is favorable for the formation of the γ phases. The amount of γ-form increases with the increase in crystallization temperature at the expense of its α component, then reaches a maximum value at the crystallization temperature of 115°C, and finally decreases with further increase in the crystallization temperature.     

Pre-exponential factor for non-isothermal crystallization of glassy Se85− x Te15Sb x (0 ≤ x ≤ 10) alloys

We report observations of the Meyer–Neldel rule for the non-isothermal crystallization of glassy Se_{85? x} Te₁₅Sb _x (x =?0, 2, 4, 6, 8, 10) alloys. We found a strong co-relation between the pre-exponential factor K ₀ of the rate constant K(T) for crystallization and the activation energy of crystallization E _c. This indicates the presence of a compensation effect for the non-isothermal crystallization process in this glassy system. The composition dependence of the crystallization temperature T _c and the activation energy for crystallization E _c is discussed.     

Design of high T g Zr-based metallic glasses using atomistic simulation and experiment

In this paper, we systematically investigate local atomic structures of Zr_100?x Al _x (0???x???72) alloys using molecular dynamics simulations. Radial distribution functions of Zr-Al configurations at 300 K indicate that Zr-Al metallic glasses form only when the Al atomic concentration is larger than 32%. Voronoi polyhedral analysis shows that Zr₄₀Al₆₀ has the highest fraction of ?0,0,12,0? icosahedra around Al atoms, which are characteristic of amorphous microstructures. Variations of thermal expansion coefficient and heat capacity of Zr_100?x Al _x (40???x???72) metallic glasses as a function of temperature from 1100 to 800?K reveal that Zr₄₀Al₆₀ has the highest transition temperature of 1008?K. To confirm the simulation results, Zr-Al metallic glasses were fabricated using co-sputtering deposition; differential scanning calorimetry testing suggests the highest crystallisation-onset temperature of above 920?K is within Zr_100?x Al _x where 43?<?x?<?61. The experimental finding is in a good agreement with the simulation predictions.     

In-situ and ex-situ study of crystallization behaviour of magnetron sputtered Ni63Zr37 amorphous thin film

ABSTRACT

The stages of crystallization of magnetron sputter-deposited Ni₆₃Zr₃₇ film with mostly amorphous structure have been investigated by differential scanning calorimetry (DSC) and in-situ annealing at 300°C by use of heating stage on a high-resolution transmission electron microscope (HRTEM). These results have been further confirmed by grazing incidence X-ray diffraction analyses of thin film specimens annealed ex-situ at 300°C for various durations. The temperature for crystallization found by DSC has been found to increase from 371°C to 434°C with an increase in heating rate from 3°C/min to 10°C/min, and the apparent activation energy for amorphous to crystalline transformation has been found as ～260.2?kJ/mol from the Kissinger plot. Studies on HRTEM using in-situ heating stage have shown the crystallization to occur on annealing at 300°C for ～10?min. Crystallization at a temperature lower than that found by DSC is attributed to structural relaxation with reduction of free volume due to thermal activation. It has been observed that Ni₃Zr forms first due to its large negative enthalpy of formation, and is followed by the formation of Ni-rich solid solution (Ni_ss) grains. HRTEM studies have shown grain rotation with the formation of partial dislocations at Ni₃Zr-Ni_ss interfaces as well as twinning followed by detwinning with dislocation formation in the Ni_ss matrix possibly to reduce the interfacial energy.