Digital watermarking provides a feasible way for copyright protection of multimedia. The major disadvantage of the existing methods is their limited resistance to both extensive geometric distortions and watermark-estimation attack (WEA). In view of this fact, this paper aims to propose a robust image watermarking scheme that can withstand geometric distortions and WEA simultaneously. Our scheme is mainly composed of two components: (i) mesh generation and embedding for resisting geometric distortions; and (ii) construction of hash-based content-dependent watermark (CDW) for resisting WEA. Extensive experimental results obtained from standard benchmark confirm the ability of our method in improving robustness.

Fashion is a reflection of the society of a period. Given that New York City is one of the world's fashion capitals, understanding its change in fashion becomes a way to know the society and the times. To keep up with fashion trends, it is important to know what's "in" and what's "out" for a season. Though the fashion trends have been analyzed by fashion designers and fashion analysts for a long time, this issue has been ignored in multimedia science. In this paper, we present a novel algorithm that automatically discovers visual style elements representing fashion trends for a certain season. The visual style elements are discovered based on the stylistic coherent and unique characteristics. The experimental results demonstrate the effectiveness of our proposed method through a large number of catwalk show videos.

Positive photoresist was characterized by Fourier transform infrared (FTIR) spectroscopy after high dose, high power ion implantation. The concentration of individual components in the resist such as the photosensitizer and organic C--H bonds were determined independently by examining the integrated absorbances at the corresponding infrared absorption peaks: 2040-2200 cm 1 for the sensitizer, and 2820-2995 cm 1 for the stretch of C--H bonds. Degradation of the sensitizer was found to be largely due to the elevated wafer temperature which is dependent on the heat generated by the ion implant and the cooling mechanism of the implanter. The thickness of the carbonized layer can be estimated by the loss of C--H bonds, which is in agreement with SEM results. A study of the implanted resist which was subjected to an oxygen plasma shows that the increased ashing resistance is due to the formation of the carbonized layer. The carbonized layer also reduces the degradation of the sensitizer in the implanted resist when exposed to an oxygen plasma.Over the years, photoresist has been used extensively as an ion implant mask in semiconductor device fabrication. For most practical applications, the ion dose ranges from 1.0Ell to 1.0El5 ions/cm 2. In this range the photoresist mask provides the advantages of process simplicity, effective masking, and ease of removal after implant. At higher dose levels, however, the optical density of the resist increases substantially and the films become more difficult to strip. Okuyama et al.(1) attributed the change to the "graphitization" of resist. In their report, they presented experimental data from the measurements of scratch resistance, optical density, and gas chromatography and showed similarities between high dose ion-implanted photoresist and disordered graphite. They concluded that physical ion bombardment during implant is responsible for the graphitization of the resist, which breaks chemical bonds within the resist. As a result, hydrogen, oxygen, and nitrogen atoms are lost from the base polymer chains and consequently the resist becomes richer in carbon.Later, Smith (2) proposed a model which related the thickness of the carbonized layer to ion dose and ion range within the photoresist. He suggested that there is a critical dose at which the original concentration of hydrogen within the carbonized layer is completely depleted. Below the critical dose, fractional carbonization exists and the thickness of the carbonized layer is determined by the ion range. Above the critical dose, the thickness of the carbonized layer can be estimated from the gas evolved from the resist and should slowly increase with dose. However, application of the model to estimate the thickness of the carbonized layer is limited, since the ion range within the resist will change toward that of amorphous carbon, as the carbonization proceeds.Another concern when using photoresist as an implant mask is the wafer temperature. Wafers can rise in temperature if the heat generated by the ion implant is not di...

In this paper, a preliminary baseball player behavior classification system is proposed. By using multiple IoT sensors and cameras, the proposed method accurately recognizes many of baseball players’ behaviors by analyzing signals from heterogeneous sensors. The contribution of this paper is threefold: (i) signals from a depth camera and from multiple inertial sensors are obtained and segmented, (ii) the time-variant skeleton vector projection from the depth camera and the statistical features extracted from the inertial sensors are used as features, and (iii) a deep learning-based scheme is proposed for training behavior classifiers. The experimental results demonstrate that the proposed deep learning behavior system achieves an accuracy of greater than 95% compared to the proposed dataset.

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