In this study, the effect of atomically flat Si(100) surface on Hf-based Metal-Oxide-Nitride-Oxide-Silicon (MONOS) structure was investigated. After the atomically flat Si(100) surface formation by annealing at 1050/60min in Ar/4%H2 ambient, HfO2(O)/HfN1.0(N)/HfO2(O) structure with thickness of 10/3/2nm, respectively, was in-situ deposited by electron cyclotron resonance (ECR) plasma sputtering. The memory window (MW) of Al/HfO2/HfN1.0/HfO2/p-Si(100) diodes was increased from 1.0V to 2.5V by flattening of Si(100) surface. The program and erase (P/E) voltage/time were set as 10V/5s and -8V/5s, respectively. Furthermore, it was found that the gate current density after the 103P/E cycles was decreased one order of magnitude by flattening of Si(100) surface in Ar/4.0%H2 ambient.

High frame rate and ultra-low delay matching system plays an increasingly important role in human-machine interactive applications which call for higher frame rate and lower delay for a better experience. The large amount of processing data and the complex computation in a local feature based matching system, make it difficult to achieve a high process speed and ultra-low delay matching with limited resource. Aiming at a matching system with the process speed of more than 1000 fps and with the delay of less than 1 ms/frame, this paper puts forward a local binary feature based matching system with field-programmable gate array (FPGA). Pixel selection based 4-1-4 parallel matching and intensity directed symmetry are proposed for the implementation of this system. To design a basic framework with the high process speed and ultra-low delay using limited resource, pixel selection based 4-1-4 parallel matching is proposed, which makes it possible to use only one-thread resource consumption to achieve a four-thread processing. Assumes that the orientation of the keypoint will bisect the patch best and will point to the region with high intensity, intensity directed symmetry is proposed to calculate the keypoint orientation in a hardware friendly way, which is an important part for a rotation-robust matching system. Software experiment result shows that the proposed keypoint orientation calculation method achieves almost the same performance with the state-of-art intensity centroid orientation calculation method in a matching system. Hardware experiment result shows that the designed image process core supports to process VGA (640×480) videos at a process speed of 1306 fps and with a delay of 0.8083 ms/frame.

We present a human point of gaze estimation system using corneal surface reflection and omnidirectional image taken by spherical panorama cameras, which becomes popular recent years. Our system enables to find where a user is looking at only from an eye image in a 360° surrounding scene image, thus, does not need gaze mapping from partial scene images to a whole scene image that are necessary in conventional eye gaze tracking system. We first generate multiple perspective scene images from an omnidirectional (equirectangular) image and perform registration between the corneal reflection and perspective images using a corneal reflection-scene image registration technique. We then compute the point of gaze using a corneal imaging technique leveraged by a 3D eye model, and project the point to an omnidirectional image. The 3D eye pose is estimate by using the particle-filter-based tracking algorithm. In experiments, we evaluated the accuracy of the 3D eye pose estimation, robustness of registration and accuracy of PoG estimations using two indoor and five outdoor scenes, and found that gaze mapping error was 5.546 [deg] on average.

A logo is a symbolic presentation that is designed not only to identify a product manufacturer but also to attract the attention of shoppers. Shoe logos are a challenging subject for automatic extraction and recognition using image analysis techniques because they have characteristics that distinguish them from those of other products; that is, there is much within-class variation in the appearance of shoe logos. In this paper, we propose an automatic extraction and recognition method for shoe logos with a wide variety of appearance using a limited number of training samples. The proposed method employs maximally stable extremal regions for the initial region extraction, an iterative algorithm for region grouping, and gradient features and a support vector machine for logo recognition. The results of performance evaluation experiments using a logo dataset that consists of a wide variety of appearances show that the proposed method achieves promising performance for both logo extraction and recognition.

Predicting the service performance of Internet applications is important in service selection, especially for video services. In order to design a predictor for forecasting video service performance in third-party application, two famous service providers in China, Iqiyi and Letv, are monitored and analyzed. The study highlights that the measured performance in the observation period is time-series data, and it has strong autocorrelation, which means it is predictable. In order to combine the temporal information and map the measured data to a proper feature space, the authors propose a predictor based on a Conditional Restricted Boltzmann Machine (CRBM), which can capture the potential temporal relationship of the historical information. Meanwhile, the measured data of different sources are combined to enhance the training process, which can enlarge the training size and avoid the over-fit problem. Experiments show that combining the measured results from different resolutions for a video can raise prediction performance, and the CRBM algorithm shows better prediction ability and more stable performance than the baseline algorithms.

In wireless communication systems, OFDM technology is a communication method that can yield high data rates. However, OFDM systems suffer high PAPR values due to the use of many of subcarriers. The SLM and the PTS technique were proposed to solve the PAPR problem in OFDM systems. However, these approaches have the disadvantage of having high complexity. This paper proposes a method which has lower complexity than the conventional PTS method but has less performance degradation.

This paper addresses the issue of text matching for plagiarism detection. This task aims at identifying the matching plagiarism segments in a pair of suspicious document and its plagiarism source document. All the time, heuristic-based methods are mainly utilized to resolve this problem. But the heuristics rely on the experts' experiences and fail to integrate more features to detect the high obfuscation plagiarism matches. In this paper, a statistical machine learning approach, named the Ranking-based Text Matching Approach for Plagiarism Detection, is proposed to deal with the issues of high obfuscation plagiarism detection. The plagiarism text matching is formalized as a ranking problem, and a pairwise learning to rank algorithm is exploited to identify the most probable plagiarism matches for a given suspicious segment. Especially, the Meteor evaluation metrics of machine translation are subsumed by the proposed method to capture the lexical and semantic text similarity. The proposed method is evaluated on PAN12 and PAN13 text alignment corpus of plagiarism detection and compared to the methods achieved the best performance in PAN12, PAN13 and PAN14. Experimental results demonstrate that the proposed method achieves statistically significantly better performance than the baseline methods in all twelve document collections belonging to five different plagiarism categories. Especially at the PAN12 Artificial-high Obfuscation sub-corpus and PAN13 Summary Obfuscation plagiarism sub-corpus, the main evaluation metrics PlagDet of the proposed method are even 22% and 43% relative improvements than the baselines. Moreover, the efficiency of the proposed method is also better than that of baseline methods.

We experimentally demonstrate transistor operation in a vertical p+-MoS2/n-HfS2 van der Waals (vdW) heterostructure configuration for the first time. The HfS2/MoS2 heterojunction transistor exhibits an ON/OFF ratio of 104 and a maximum drain current of 20 nA. These values are comparable with the corresponding reported values for vdW heterojunction TFETs. Moreover, we study the effect of atmospheric exposure on the subthreshold slope (SS) of the HfS2/MoS2 transistor. Unpassivated and passivated devices are compared in terms of their SS values and IDS-VGS hysteresis. While the unpassivated HfS2/MoS2 heterojunction transistor exhibits a minimum SS value of 2000 mV/dec, the same device passivated with a 20-nm-thick HfO2 film exhibits a significantly lower SS value of 700 mV/dec. HfO2 passivation protects the device from contamination caused by atmospheric moisture and oxygen and also reduces the effect of surface traps. We believe that our findings will contribute to the practical realization of HfS2-based vdW heterojunction TFETs.

In this study, the effect of nitrogen-doped (N-doped) LaB6 bottom-contact electrodes and interfacial layer (IL) on n-type pentacene-based organic field-effect transistor (OFET) was investigated. The scaled OFET was fabricated by using photolithography for bottom-contact electrodes. A 20-nm-thick N-doped LaB6 bottom-contact electrodes were formed on SiO2/n+-Si(100) substrate by RF sputtering followed by the surface treatment with sulfuric acid and hydrogen peroxide mixture (SPM) followed by diluted hydrofluoric acid (DHF; 1% HF) at room temperature (RT). Then, a 1.2-nm-thick N-doped LaB6 IL was deposited at RT. Finally, a 10-nm-thick pentacene film was deposited at 100°C followed by the Al back-gate electrode formation by using thermal evaporation. The current of electron injection was observed in the air due to the effect of surface treatment and N-doped LaB6 IL.

In this paper, we have investigated the PdEr-silicide formation utilizing a developed PdEr-alloy target for sputtering, and evaluated the contact resistivity of PdEr-silicide layer formed on n-Si(100) by dopant segregation process for the first time. Pd2Si and ErSi2 have same hexagonal structure, while the Schottky barrier height for electron (Φbn) is different as 0.75 eV and 0.28 eV, respectively. A 20 nm-thick PdEr-alloy layer was deposited on the n-Si(100) substrates utilizing a developed PdEr-alloy target by the RF magnetron sputtering at room temperature. Then, 10 nm-thick TiN encapsulating layer was in-situ deposited at room temperature. Next, silicidation was carried out by the RTA at 500 for 5 min in N2/4.9%H2 followed by the selective etching. From the J-V characteristics of fabricated Schottky diode, qΦbn was reduced from 0.75 eV of Pd2Si to 0.43 eV of PdEr-silicide. Furthermore, 4.0x10-8Ωcm2 was extracted for the PdEr-silicide to n-Si(100) by the dopant segregation process.

Nuclear power plants require in-vessel inspections for soundness checks and preventive maintenance. One inspection procedure is visual testing (VT), which is based on video images of an underwater camera in a nuclear reactor. However, a lot of noise is superimposed on VT images due to radiation exposure. We propose a technique for improving the quality of those images by image processing that reduces radiation noise and enhances signals. Real-time video processing was achieved by applying the proposed technique with a parallel processing unit. Improving the clarity of VT images will lead to reducing the burden on inspectors.

Engineers and researchers have recently paid attention to Blockchain. Blockchain is a fault-tolerant distributed ledger without administrators. Blockchain is originally derived from cryptocurrency, but it is possible to be applied to other industries. Transferring digital asset is called a transaction. Blockchain holds all transactions, so the total amount of Blockchain data will increase as time proceeds. On the other hand, the number of Internet of Things (IoT) products has been increasing. It is difficult for IoT products to hold all Blockchain data because of their storage capacity. Therefore, they access Blockchain data via servers that have Blockchain data. However, if a lot of IoT products access Blockchain network via servers, server overloads will occur. Thus, it is useful to reduce workloads and improve throughput. In this paper, we propose a caching technique using a Field Programmable Gate Array-based (FPGA) Network Interface Card (NIC) which possesses four 10Gigabit Ethernet (10GbE) interfaces. The proposed system can reduce server overloads, because the FPGA NIC instead of the server responds to requests from IoT products if cache hits. We implemented the proposed hardware cache to achieve high throughput on NetFPGA-10G board. We counted the number of requests that the server or the FPGA NIC processed as an evaluation. As a result, the throughput improved by on average 1.97 times when hitting the cache.

The concept of Gaussian integer sequence pair is generalized from a single Gaussian integer sequence. In this letter, by adopting cyclic difference set pairs, a new construction method for perfect Gaussian integer sequence pairs is presented. Furthermore, the necessary and sufficient conditions for constructing perfect Gaussian integer sequence pairs are given. Through the research in this paper, a large number of perfect Gaussian integer sequence pairs can be obtained, which can greatly extend the existence of perfect sequence pairs.

This letter considers a legitimate proactive eavesdropping scenario, where a half-duplex legitimate monitor hires a third-party jammer for jamming the suspicious communication to improve the eavesdropping performance. The interaction between the third-party jammer and the monitor is modeled as a Stackelberg game, where the jammer moves first and sets the price for jamming the suspicious communication, and then the legitimate monitor moves subsequently and determines the requested transmit power of the jamming signals. We derive the optimal jamming price and the optimal jamming transmit power. It is shown that the proposed price-based proactive eavesdropping scheme is effective in improving the successful eavesdropping probability compared to the case without jamming. It is also shown that the proposed scheme outperforms the existing full-duplex scheme when the residual self-interference cannot be neglected.

In this letter, a novel transmission scheme is proposed to eliminate the polarization dependent loss (PDL) effect in dual-polarized satellite systems. In fact, the PDL effect is the key problem that limits the performance of the systems based on the PM technique, while it is naturally eliminated in the proposed scheme since we transmit the two components of the polarized signal in turn in two symbol periods. Moreover, a simple and effective detection method based on the signal's power is proposed to distinguish the polarization characteristic of the transmit antenna. In addition, there is no requirement on the channel state information at the transmitter, which is popular in satellite systems. Finally, superiorities are validated by the theoretical analysis and simulation results in the dual-polarized satellite systems.

Video surveillance from airborne platforms can suffer from many sources of blur, like vibration, low-end optics, uneven lighting conditions, etc. Many different algorithms have been developed in the past that aim to recover the deblurred image but often incur substantial CPU-time, which is not always available on-board. This paper shows how a “strap-on” quasi-Newton method can accelerate the convergence of existing iterative methods with little extra overhead while keeping the performance of the original algorithm, thus paving the way for (near) real-time applications using on-board processing.

Hard-type oscillators for ultrahigh frequency applications were proposed based on resonant tunneling diodes (RTDs) and a HEMT trigger circuit. The hard-type oscillators initiate oscillation only after external excitation. This is advantageous for suppressing the spurious oscillation in the bias line, which is one of the most significant problems in the RTD oscillators. We first investigated a series-connected circuit of a resistor and an RTD for constructing a hard-type oscillator. We carried out circuit simulation using the practical device parameters. It was demonstrated that the stable oscillation can be obtained for such oscillators. Next, we proposed to use series-connected RTDs for the gain block of the hard-type oscillators. The series circuits of RTDs show the negative differential resistance in very narrow regions, or no regions at all, which makes impossible to use such circuits for the conventional soft-type oscillators. However, with the trigger circuit, they can be used for hard-type oscillators. We confirmed the oscillation and the bias stability of these oscillators, and also demonstrated that the voltage swing can be easily increased by increasing the number of RTDs connected in series. This is promising method to overcome the power restriction of the RTD oscillators.

A novel Doppler spread estimation scheme is proposed for an orthogonal frequency division multiplexing (OFDM) system with a Rayleigh fading channel. The proposal develops a composite power spectral density (PSD) function by averaging the multiple PSD functions computed with multiple sets of the channel frequency response (CFR) coefficients. The Doppler spread is estimated by finding the maximum location of the composite PSD quantities larger than a threshold value given by a fixed fraction of the maximum composite PSD quantity. It is shown by simulation that the proposed scheme performs better than three conventional Doppler spread estimation schemes not only in isotropic scattering environments, but also in nonisotropic scattering environments. Moreover, the proposed scheme is shown to perform well in some Rician channel environments if the Rician K-factor is small.

In this paper, we propose a method to generate a three-dimensional (3D) thermal map and RGB + thermal (RGB-T) images of a scene from thermal-infrared and RGB images. The scene images are acquired by moving both a RGB camera and an thermal-infrared camera mounted on a stereo rig. Before capturing the scene with those cameras, we estimate their respective intrinsic parameters and their relative pose. Then, we reconstruct the 3D structures of the scene by using Direct Sparse Odometry (DSO) using the RGB images. In order to superimpose thermal information onto each point generated from DSO, we propose a method for estimating the scale of the point cloud corresponding to the extrinsic parameters between both cameras by matching depth images recovered from the RGB camera and the thermal-infrared camera based on mutual information. We also generate RGB-T images using the 3D structure of the scene and Delaunay triangulation. We do not rely on depth cameras and, therefore, our technique is not limited to scenes within the measurement range of the depth cameras. To demonstrate this technique, we generate 3D thermal maps and RGB-T images for both indoor and outdoor scenes.