Scale-invariant template matching using histogram of dominant gradients

This paper presents a histogram-based template matching method that copes with the large scale difference between target and template images. Most of the previous template matching methods are sensitive to the scale difference between target and template images because the features extracted from the images are changed according to the scale of the images. To overcome this limitation, we introduce the concept of dominant gradients and describe an image as the feature that is tolerant to scale changes. To this end, we first extract the dominant gradients of a template image and represent the template image as the grids of histograms of the dominant gradients. Then, the arbitrary regions of a target image with various locations and scales are matched with the template image via histogram matching. Experimental results show that the proposed method is more robust to scale difference than previous template matching techniques.     

Tuning of vertically-aligned carbon nanotube diameter and areal density through catalyst pre-treatment

By controlling the timing and duration of hydrogen exposure in a fixed thermal process, we tuned the diameters of carbon nanotubes (CNTs) within a vertically aligned film by a factor of 2, and tuned the areal densities by an order of magnitude. The CNT structure is correlated with the catalyst morphology, suggesting that while chemical reduction of the catalyst layer is required for growth, prolonged H2 exposure not only reduces the iron oxide and enables agglomeration of the Fe film, but also leads to catalyst coarsening. Control of this coarsening process allows tuning of CNT characteristics.     

Oxygen barrier properties of polyketone/EVOH blend films and their resistance to moisture

Polyketone (PK) has excellent chemical and mechanical properties, but its use in food packaging is limited due to its oxygen barrier properties being insufficient for high-barrier film applications. To improve its oxygen barrier properties, PK has been blended with ethylene vinyl alcohol copolymer (EVOH), which is one of the highest oxygen barrier polymers in use today. The oxygen barrier properties under both dry and humid conditions, as well as the mechanical properties of PK/EVOH blend films were investigated in this study. These novel PK/EVOH blend films exhibited unusually low oxygen permeability values from 0.3 to 0.16 cc 20 μm m⁻² day⁻¹ atm⁻¹ with increasing EVOH content from 30 to 70 wt%, which are even lower than those of the ideal laminar model that expresses the theoretical minimum permeability values attainable for blended barrier films. These high oxygen barrier properties of PK/EVOH blend films can conceivably be attributed to the combination of two dominant effects: a tortuous diffusion path through the EVOH domains in the PK matrix and hydrogen bonding interactions between PK and EVOH. Furthermore, in high-humidity environments with retorting, the PK/EVOH blend films exhibited superior resistance to moisture over EVOH. Immediately after the retorting test, the oxygen permeability of the high-barrier PK/EVOH blend films with an EVOH content of 30–40 wt% increased by less than 3× the pre-retorting value, as opposed to 74× for EVOH. In addition, PK/EVOH blend films displayed superior stretching characteristics, with a breaking strain of over 300%, which are valuable for flexible packaging applications.     

Defeating traffic analysis via differential privacy: a case study on streaming traffic

In this paper, we explore the adaption of techniques previously used in the domains of adversarial machine learning and differential privacy to mitigate the ML-powered analysis of streaming traffic. Our findings are twofold. First, constructing adversarial samples effectively confounds an adversary with a predetermined classifier but is less effective when the adversary can adapt to the defense by using alternative classifiers or training the classifier with adversarial samples. Second, differential-privacy guarantees are very effective against such statistical-inference-based traffic analysis, while remaining agnostic to the machine learning classifiers used by the adversary. We propose three mechanisms for enforcing differential privacy for encrypted streaming traffic and evaluate their security and utility. Our empirical implementation and evaluation suggest that the proposed statistical privacy approaches are promising solutions in the underlying scenarios

     

Modeling and optimization of a reluctance accelerator using DOE-based response surface methodology

This paper introduces experiment-based modeling and optimization of a reduced-scale Electromagnetic launcher (EML) using the Design of experiments (DOE) technique. Response surface models describing the velocity and kinetic energy of the launched projectile were developed using the Box–Behnken method with design variable transforms, and an Analysis of variance (ANOVA) was conducted to refine the models by removing statistically insignificant terms. A bi-objective optimization problem with the maximum velocity and maximum kinetic energy as objects was considered, and a Pareto front was obtained using the generated response surfaces as the solution of the problem. Verification tests on the optimal design points were conducted to demonstrate the validity of the developed models.

     

An Efficient Type Codec for Point Data in Lightweight Applications Scene Representation (LASeR)

Recently, MPEG has opened activity to standardize scene representation for lightweight applications such as in mobile phones. The standard is named lightweight applications scene representation (LASeR) and can be applied to improve and make efficient rich media applications and services on mobile devices. In this standard, we proposed an efficient type codec for point data to maximize the bit efficiency of LASeR. In this paper, we describe the new method and the test results of the proposed scheme.     

Preparation of PE/MWNT nanocomposites by In-situ metallocene polymerization

We prepared polyethylene (PE) / multiwall carbon nanotube (MWNT) nanocomposites with various weight fractions using in situ metallocene polymerization. This polymerization method consists of attaching a metallocene catalyst complex on the surface of MWNT and being polymerized from that. All the procedures of polymerization made progress with one-pot process. The polymerized PE/MWNT nanocomposites showed uniform dispersion of MWNT in the PE matrix. The degree of dispersion has been characterized by means of scanning electron microscopy (SEM), and wide-angle X-ray diffraction (WAXD). Electrical conductivity and thermal conductivity were investigated.     

Multifunctional Materials Strategies for Enhanced Safety of Wireless,Skin-Interfaced Bioelectronic Devices

Many recently developed classes of wireless, skin-interfaced bioelectronic devices rely on conventional thermoset silicone elastomer materials, such as poly(dimethylsiloxane) (PDMS), as soft encapsulating structures around collections of electronic components, radio frequency antennas and, commonly, rechargeable batteries. In optimized layouts and device designs, these materials provide attractive features, most prominently in their gentle, noninvasive interfaces to the skin even at regions of high curvature and large natural deformations. Past studies, however, overlook opportunities for developing variants of these materials for multimodal means to enhance the safety of the devices against failure modes that range from mechanical damage to thermal runaway. This study presents a self-healing PDMS dynamic covalent matrix embedded with chemistries that provide thermochromism, mechanochromism, strain-adaptive stiffening, and thermal insulation, as a collection of attributes relevant to safety. Demonstrations of this materials system and associated encapsulation strategy involve a wireless, skin-interfaced device that captures mechanoacoustic signatures of health status. The concepts introduced here can apply immediately to many other related bioelectronic devices.