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[Display omitted] In this study, hollow Fe 3 O 4 /Fe@C nanocube wave absorbers with different reduction degrees are designed based on the Fe(II)/Fe(III) ion engineering strategy, among which the Fe 3 O 4 @C has the RL min as low as −119.9 dB at 2.3 mm and achieves extremely wide effective absorption bandwidth of 11.4 GHz spanning low-frequency band of 2.8∼7.2 GHz and high-frequency band of 11.0∼18 GHz at 5.0 mm. • A novel ion-engineering and heat treatment process was used to obtain Fe 3 O 4 /Fe@C. • Fe 3 O 4 /Fe@C nanoassemblies have a special structure of hollow core–shell nanocube. • The RL min value of Fe 3 O 4 @C is as high as − 119.9 dB at a thin thickness of 2.3 mm. • Fe 3 O 4 @C achieves an ultra-wideband of 11.4 GHz across high and low frequency bands. Rationally constructing hollow structures with heterogeneous interface is usually an effective strategy to regulate the electromagnetic response behavior for lightweight and strong absorption, but achieving low-frequency and broadband absorption is a major challenge. This work adopts a novel Fe(II)/Fe(III) ions regulation strategy to design and synthesize hollow Fe(OH) X (x = 2, 3) nanocubes, which addresses the disadvantages of time-consuming or using etchant. Subsequently, a unique hollow Fe 3 O 4 /Fe@C nanoboxes with adjustable magnetic composition and uniformly coated shell have been successfully synthesized by in-situ carbonization with the assistance of phenolic resin and hydrogen thermal reduction. Notably, the different magnetic components induce the magnetic coupling assembly and play a crucial role in determining its electromagnetic parameters, whereas Fe 3 O 4 contributes to more dipole polarization and stronger low-frequency response characteristics. For Fe 3 O 4 @C hollow nanoboxes, the minimum reflection loss (RL min) is as low as –119.9 dB at 2.3 mm, and extremely wide effective absorption bandwidth (EAB) of 11.4 GHz is achieved spanning low-frequency band of 2.8 ∼ 7.2 GHz and high-frequency band of 11.0 ∼ 18 GHz at 5.0 mm. Surprisingly, the Fe 3 O 4 @C also has satisfactory EAB 20 (RL＜ –20 dB) reaching 7.1 GHz (14.9 ∼ 18 GHz) at a thin thickness of 1.8 mm. The RL min of other hollow nanoboxes is also below –30 dB, and the EAB is greater than 9 GHz. This study provides a competitive candidate for efficient microwave absorption in complex frequency bands, especially low-frequency bands. [ABSTRACT FROM AUTHOR]

At present, to solve the threat of electromagnetic wave (EMW) radiation pollution to human health, intelligent control and information security, tremendous efforts have been made to manufacture EMW absorbing materials. For ideal microwave absorption materials (MAMs), it is generally necessary not only to pursue strong microwave absorption (MA) over wide effective absorption bandwidth (EAB), but also to take into account the requirements of light weight, thin matching thickness and chemical stability characteristics. It has been found that magnetite (Fe 3 O 4) is the most promising MAM to absorb and dissipate EMW among various absorbers, because of its good mechanical and chemical stability, controllable morphology, high Curie temperature, easy preparation, economy and excellent magnetic properties. However, the application performance of Fe 3 O 4 absorber with single composition is limited by its easy agglomeration, eddy current, high density, and impedance mismatch. In addition, achieving efficient MA metrics with low absorber loading remains a huge challenge. To overcome these limitations, conjugation with dielectric carbon-based materials and special structural designs have been extensively explored as viable solutions to optimize the microwave absorption performance (MAP) of Fe 3 O 4. This paper reviews the recent research progress of Fe 3 O 4 /carbon MAMs, and then the influence of dimensions and structures regulations on the MAPs are introduced in detail. Finally, the current existing problems and future development direction of Fe 3 O 4 /carbon composites in the field of MA are also presented. This paper reviews the recent research progress of Fe 3 O 4 /carbon composite absorbers, and then the influence of dimensions and structures on the microwave absorption properties were introduced in detail. [Display omitted] • Mechanisms behind the microwave absorption of Fe 3 O 4 /C composites are interpreted. • Different dimensions and structures of Fe 3 O 4 /C absorbers are reviewed in detail. • Challenges and future directions of Fe 3 O 4 /C absorbers are put forward. [ABSTRACT FROM AUTHOR]

In recent years, the capacity of cellular networks has hardly kept pace with the dramatic explosion of cellular traffic from emerging mobile applications. To address this issue, a number of studies have been proposed to offload the cellular traffic using delay-tolerant networks (DTNs) opportunistically formed by mobile devices. These offloading schemes rely on the assumption of small-size content, which can be entirely transmitted over a single DTN contact. However, such an assumption, which was probably valid in the past, can no longer hold with the increasing popularity of large-size multimedia contents in the future. In this paper, we propose a novel contact-duration-aware offloading scheme called Coff, which consists of several designs that are specially tailored for DTNs. First, we use content fragmentation to utilize short contacts. Second, we adopt network coding to achieve a near-optimum dissemination. Finally, we design a greedy load allocation (GLA) algorithm to achieve no less than (\mbox1-\mbox1/e) of the optimum. Extensive simulations on both synthetic and real-world traces show that Coff is more efficient than the baselines, which extend from state-of-art DTN-based offloading schemes with content fragmentation and network coding. [ABSTRACT FROM AUTHOR]

Identifying the owners of online devices on the Internet can enable numerous network security applications. For example, fast and accurate Owner Name Entity Recognition (ONER) of websites is critical to find influenced owners in light of new security threats. In this situation, as a specific task of Multimodal Named Entity Recognition (MNER), ONER is essential and helpful for network security. Currently, most of the existing MNER models only use texts and images, so they cannot effectively utilize the multimodal data of devices to achieve ONER accurately and fast. In order to improve performance and training speed simultaneously, the paper proposes a framework MFMCA: Multiscale Features and Multimodal Co-Attention. MFMCA is based on a two-step gated co-attention with fewer transformer blocks and simultaneously uses texts, images, and domains. Also, MFMCA extracts multiscale image features to get a fine-grained hint for ONER. Moreover, due to the lack of MNER datasets, the paper manually labels a multimodal dataset containing texts, images, and domains for MNER research. The experiments show that MFMCA achieves 0.8211 F1 scores on the recognition of owner entities, which is competitive compared with 0.8288, the best performance of existing state-of-the-art MNER models. However, MFMCA saves about 34% training time on the proposed dataset. • This paper raises the problem of Owner Name Entity Recognition of websites. • This paper constructs a manually labelled multimodal dataset, containing about 15,000 samples. • This paper designs a two-step gated co-attention to improve the performance of ONER. • The results show the competitive performance of our method with less cost time. • This paper builds multiscale image features to realize feature alignment well. [ABSTRACT FROM AUTHOR]

Accurate eye localization plays a key role in many face analysis related applications. In this paper, we propose a novel statistic-based eye localization framework with a group of trained filter arrays called multi-channel correlation filter bank (MCCFB). Each filter array in the bank suits to a different face condition, thus combining these filter arrays can locate eyes more precisely in the conditions of variable poses, appearances and illuminations when comparing to single filter based or filter array based methods. To demonstrate the performance of our framework, we compare MCCFB with other statistic-based eye localization methods, experimental results show superiority of our method in detection ratio, localization accuracy and robustness. [ABSTRACT FROM AUTHOR]

Underwater sensor networks are envisioned to enable a wide range of underwater applications such as pollution monitoring, offshore exploration, and oil/gas spill monitoring. Such applications require precise location information as otherwise the sensed data might be meaningless. On the other hand, security and privacy are critical issues as underwater sensor networks are typically deployed in harsh environments. Nevertheless, most underwater localization schemes are vulnerable to many attacks and suffer from potential privacy violations as they are designed for benign environments. However, a localization scheme that does not consider security and privacy could lead to serious consequences, especially in critical applications such as military monitoring. In this article, we discuss the security and privacy issues in underwater localization, and investigate the techniques that can provide security and preserve node privacy in underwater sensor networks. [ABSTRACT FROM PUBLISHER]

Fingerprint positioning can take advantage of existing WLAN to achieve indoor locations, which has been widely studied. We analyzed the corresponding positions distribution of similar fingerprints, and then found that the fuzzy similarity between fingerprints is the root cause of the larger errors existing. According to clusters distribution feature of corresponding positions of the similar fingerprints, we proposed a K-Means+ clustering algorithm to achieve fine-grained fingerprint positioning. Due to the K-Means+ algorithm failing to locate the positions of outliers, we also designed a linear sequence matching algorithm to improve the outliers positioning, and reduce the impact of fuzzy similarity. Experimental results illustrate that our algorithm can get a maximum positioning error less than 5 m, which outperforms other algorithms. Meanwhile, all the positioning errors over 4 m in our algorithm are less than 2%. The positioning accuracy has been improved significantly. [ABSTRACT FROM AUTHOR]