Amelioration of mechanical brittleness in hyperbranched polymer. 1. Macroscopic evaluation by dynamic viscoelastic relaxation

Hyperbranched poly(ether ketone)-b-linear poly(ether ketone)-b-hyperbranched poly(ether ketone) (HLHPEK) triblock copolymers with two different block compositions were prepared as an approach to improve the mechanical brittleness of hyperbranched poly(ether ketone) (HPEK). From the time-temperature superposition of dynamic shear moduli, G′(ω) and G″(ω), of HPEK and two HLHPEKs, it was investigated that the junction points between G′(ω) and G″(ω) shifted to the higher frequencies and the rubbery plateau region spread wider over the reduced frequency axis as the linear blocks were introduced and their compositions were increased. Such changes in viscoelastic response were consequences of increase in the amount of chain entanglements additionally formed by the linear blocks. In order to verify the effect of the linear block incorporation on amelioration of the mechanical brittleness, the degree of brittleness and its improvement were evaluated from the temperature dependence of the shift factors, a_Ts, experimentally obtained during the superposition of the dynamic moduli and of the average viscoelastic relaxation times, τ_HNs, determined with empirical Havriliak-Negami distribution function. From the nonlinear curve fittings of the a_Ts and the τ_HNs by the Vogel-Tamman-Fulcher equation, the degree of brittleness for HPEK and HLHPEK triblock copolymers were quantified as values of the material parameter D, an indicative of deviation from the linear Arrhenius behavior and a measure of fragility of the given material. The tendency of increasing D values with the linear block compositions confirmed substantial improvement of the mechanical brittleness in the HLHPEK triblock copolymers compared to HPEK. Therefore, the approach to copolymerize HPEK with its chemically analogous linear counterpart was verified to be an effective strategy to impart molecular entanglements and hence ameliorate the mechanical brittleness on the basis of macroscopic rheological evaluation.     

Correlation of vapor-liquid equilibria for binary mixtures with free energy-based equation of state mixing rules: Carbon dioxide with alcohols, hydrocarbons, and several other compounds

The correlation of vapor-liquid equilibrium data for high-pressure carbon dioxide systems is of interest in a number of industrial applications, including supercritical extraction. Here, we consider the correlation of data for 12 binary systems of carbon dioxide separately with alcohols, with hydrocarbons, and with acetone, benzene, and water. The Wong-Sandler (W-S) and modified Huron — Vidal first order (MHV1) free energy-based equation of state mixing rules (the W-S and MHV1 models) were used in the calculations. Both combined equation of state+free energy models generally resulted in good correlations of the experimental data over wide ranges of temperature and pressure with temperature — independent parameters. However, for the carbon dioxide+water system, the W-S model produced an 11% average absolute deviation in pressure, while no parameter that resulted in an AAD in pressure of less than 20% could be found for the MHV1 model.     

Conceptual and basic designs of the Mobile Harbor crane based on topology and shape optimization

The Mobile Harbor (MH) has been recently proposed as a novel maritime cargo transfer system that can move to a container ship anchored in the deep sea and handle containers directly at sea with the aid of a stabilized MH crane. Because this system operates under at-sea conditions, the MH crane must be designed to support an inertia load and wind force, as well as its self-weight. The wave-induced motions of the MH, e.g. rolling, pitching, and heaving, generate a significant amount of inertia load, which has not been considered in the design of conventional quayside cranes installed on stable ground. Wind force is also a critical design factor due to the higher wind velocity in the open sea. In addition to the aforementioned structural rigidity, mass minimization is also important in the structural design of MH cranes because it reduces the overturning moment and therefore enhances ship stability. In this paper, the sensitivities of the design-dependent loads (i.e. self-weight, inertia load, and wind force) are derived with respect to the design variables, and then a topology optimization is conducted with the derived sensitivities in order to obtain a conceptual design. Then, the conceptual design is elaborated into a three-dimensional basic design through shape optimization with design regulations for offshore cranes. Through the integrated design process with the topology and shape optimizations, a conceptual and basic design is successfully obtained for the MH crane.     

Effect of reaction kinetics of polymer electrolyte on the ion‐conductive behavior for poly(oligo oxyethylene methacrylate)–LiTFSI mixtures

The effect of the reaction kinetics on the ionic conductivity for a comblike‐type polyether (MEO) electrolyte with lithium bis(trifluoromethane sulfonyl)imide (LiTFSI) was characterized by DSC, complex impedance measurements, and ¹H pulse NMR spectroscopy. The ionic conductivity of these electrolytes was affected by the reaction condition of the methacrylate monomer and revealed by the glass transition temperature (T_g), spin–spin relaxation time (T₂), steric effects of the terminal groups, and the number of charge carriers indicated by the VTF kinetic parameter. In this system, the electrolytes prepared by the reaction heating rate of 10°C/min of MEO–H and 15°C/min of MEO–CH₃ showed maximum ionic conductivity, σ_i, two to three times higher in magnitude than that of the σ_i of the others at room temperature. As experimental results, the reaction kinetic rate affected the degree of conversion, the ionic conductivity, and the relaxation behaviors of polyether electrolytes. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 2149–2156, 2003     

Synthesis of nanodispersed oxides of vanadium, titanium, molybdenum, and tungsten on mesoporous silica using atomic layer deposition

The advantages of the atomic layer deposition (ALD) method for preparation of tungsten, vanadium, titanium, and molybdenum oxide catalyst supported on mesoporous silica are discussed, with emphasis on the importance of synthesis conditions on dispersion, structure and activity of the resulting materials. A suite of complementary techniques such as DRS-UV/Vis, BET, ¹H-NMR, XRD, and TEM were used to study the structural properties of the supported metal oxides, and probe reactions such as 2-butanol dehydration and ethanol partial oxidation were used to demonstrate the potential advantages of the ALD-prepared catalysts. Specifically, highly dispersed oxides of titanium, molybdenum, and tungsten oxide on mesoporous silica were synthesized using the ALD method. It is also demonstrated that attainment of high dispersions of vanadium oxide on mesoporous silica requires the presence of at least a single layer of titanium oxide due to the well-known poor interaction between vanadia and silica. The highly dispersed catalysts prepared here by ALD methods exhibited superior catalytic performance relative to those prepared using conventional incipient wetness impregnation.     

Human tracking and silhouette extraction for human–robot interaction systems

In this study, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with a pan-tilt stereo camera, so that it can assist in gesture and gait recognition in the field of Human–Robot Interaction (HRI). The proposed system consists of three modules: detection, tracking and silhouette extraction. These modules are robust to camera movements, and they work interactively in near real-time. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift-based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap was estimated in advance and then effectively incorporated into the graph-cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data, and it was shown to detect and track multiple people very well and also produce high-quality silhouettes.

Application of maximum entropy principle for reliability-based design optimization

The maximum entropy principle (MEP) is used to generate a natural probability distribution among the many possible that have the same moment conditions. The MEP can accommodate higher order moment information and therefore facilitate a higher quality PDF model. The performance of the MEP for PDF estimation is studied by using more than four moments. For the case with four moments, the results are compared with those by the Pearson system. It is observed that as accommodating higher order moment, the estimated PDF converges to the original one. A sensitivity analysis formulation of the failure probability based on the MEP is derived for reliability-based design optimization (RBDO) and the accuracy is compared with that by finite difference method (FDM). Two RBDO examples including a realistic three-dimensional wing design are solved by using the derived sensitivity formula and the MEP-based moment method. The results are compared with other methods such as TR-SQP, FAMM + Pearson system, FFMM + Pearson system in terms of accuracy and efficiency. It is also shown that an improvement in the accuracy by including more moment terms can increase numerical efficiency of optimization for the three-dimensional wing design. The moment method equipped with the MEP is found flexible and well adoptable for reliability analysis and design.     

Network Intrusion Detection in Internet of Blended Environment Using Ensemble of Heterogeneous Autoencoders (E-HAE)

Contemporary attackers, mainly motivated by financial gain, consistently devise sophisticated penetration techniques to access important information or data. The growing use of Internet of Things (IoT) technology in the contemporary convergence environment to connect to corporate networks and cloud-based applications only worsens this situation, as it facilitates multiple new attack vectors to emerge effortlessly. As such, existing intrusion detection systems suffer from performance degradation mainly because of insufficient considerations and poorly modeled detection systems. To address this problem, we designed a blended threat detection approach, considering the possible impact and dimensionality of new attack surfaces due to the aforementioned convergence. We collectively refer to the convergence of different technology sectors as the internet of blended environment. The proposed approach encompasses an ensemble of heterogeneous probabilistic autoencoders that leverage the corresponding advantages of a convolutional variational autoencoder and long short-term memory variational autoencoder. An extensive experimental analysis conducted on the TON_IoT dataset demonstrated 96.02% detection accuracy. Furthermore, performance of the proposed approach was compared with various single model (autoencoder)-based network intrusion detection approaches: autoencoder, variational autoencoder, convolutional variational autoencoder, and long short-term memory variational autoencoder. The proposed model outperformed all compared models, demonstrating F1-score improvements of 4.99%, 2.25%, 1.92%, and 3.69%, respectively.     

Nanopore Sensing in Aqueous Two‐Phase System: Simultaneous Enhancement of Signal and Translocation Time via Conformal Coating

Nanofluidic resistive pulse sensing (RPS) has been extensively used to measure the size, concentration, and surface charge of nanoparticles in electrically conducting solutions. Although various methods have been explored for improving detection performances, intrinsic problems including the extremely low particle‐to‐pore volume ratio (<0.01%) and fast nanoparticle translocation (10–1000 µs) still induce difficulties in detection, such as low signal magnitudes and short translocation times. Herein, we present an aqueous two‐phase system (ATPS) in a nanofluidic RPS for amplifying translocation signals and decreasing translocation speeds simultaneously. Two immiscible aqueous liquids build a liquid‐liquid interface inside nanopores. As particles translocate from a high‐affinity liquid phase into a lower‐affinity one, the high‐affinity liquid forms a conformal coating on the particles, which increases the effective particle size and amplifies the current‐blockage signal. The translocation time is also increased, as the ATPS interface impedes the particle translocation. For 20 nm particles, 7.92‐fold and 5.82‐fold enhancements of signal magnitude and translocation time can be achieved. To our knowledge, this is the first attempt to improve nanofluidic RPS by treating an interface of solution reservoirs for manipulating target particles rather than nanopores. This direct particle manipulation allows us to solve the two intrinsic problems all at once.