Aligned and non-aligned double JPEG detection using convolutional neural networks

Due to the wide diffusion of JPEG coding standard, the image forensic community has devoted significant attention to the development of double JPEG (DJPEG) compression detectors through the years. The ability of detecting whether an image has been compressed twice provides paramount information toward image authenticity assessment. Given the trend recently gained by convolutional neural networks (CNN) in many computer vision tasks, in this paper we propose to use CNNs for aligned and non-aligned double JPEG compression detection. In particular, we explore the capability of CNNs to capture DJPEG artifacts directly from images. Results show that the proposed CNN-based detectors achieve good performance even with small size images (i.e., 64 × 64), outperforming state-of-the-art solutions, especially in the non-aligned case. Besides, good results are also achieved in the commonly-recognized challenging case in which the first quality factor is larger than the second one.     

Numerical analysis on the LDMOS with a double epi-layer and trench electrodes

We proposed a new lateral double-diffused MOS (LDMOS) structure employing a double p/n epitaxial layer, which is formed on p⁻ substrates. Trenched gate and drain are also employed to obtain uniform and high drift current density. The breakdown voltage and the specific on-resistance of the proposed LDMOS are numerically calculated by using a two-dimensional (2D) device simulator, Medici. The n⁻ drift region and upper p⁻ region of the proposed LDMOS are fully depleted in off-states employing the RESURF technique. The simulation results show that the breakdown voltage is 142 V and specific on-resistance is 183 mΩ mm² when the cell pitch of the LDMOS is 7.5 μm. The proposed LDMOS shows better trade-off characteristics than the previous results.     

Phase-change memory technology with self-aligned μTrench cell architecture for 90 nm node and beyond

A novel self-aligned μTrench-based cell architecture for phase change memory (PCM) process is presented. The low programming current and the good dimensional control of the sub-lithographic features achieved with the μTrench structure are combined with a self-aligned patterning strategy that simplify the integration process in term of alignment tolerances and of number of critical masks. The proposed architecture has been integrated in a 90 nm 128 Mb vehicle based on a pnp bipolar junction transistor for the array selection. The good active and leakage currents achieved by the purposely optimized selecting transistors combined with programming currents of 300 μA of the storage element and good distributions measured on the 128 Mb array demonstrate the suitability of the proposed architecture for the production of high-density PCM arrays at 90 nm and beyond.     

Highly efficient green phosphorescent organic light emitting diodes with simple structure

A series of simple structures is investigated for realization of the highly efficient green phosphorescent organic light emitting diodes with relatively low voltage operation. All the devices were fabricated with mixed host system by using 1,1-bis[(di-4-tolylamino)phenyl]cyclohexane (TAPC) and 1,3,5-tri(p-pyrid-3-yl-phenyl)benzene (TpPyPB) which were known to be hole and electron type host materials due to their great hole and electron mobilities [μ_h(TAPC): 1 × 10^?2 cm²/V s and μ_e(TpPyPB): 7.9 × 10^?3 cm²/V s] [1]. The optimized device with thin TAPC (5–10 nm) as an anode buffer layer showed relatively high current and power efficiency with low roll-off characteristic up to 10,000 cd/m². The performances of the devices; with buffer layer were compared to those of simple devices with single layer and three layers. Very interestingly, the double layer device with TAPC buffer layer showed better current and power efficiency behavior compared to that of three layer device with both hole and electron buffer layers (TAPC, TpPyPB, respectively).     

Fabrication of novel double microlens using two step soft lithography

A novel method to fabricate double layer microlens array is proposed where the second smaller microlens are imprinted on the first larger microlens by using soft lithography twice. Key step to implement this method is to imprint micron-size structures on convex surface using nano-imprinting technology. It is required to prepare thin polydimethylsiloxane (PDMS) mold for the second soft lithography and thus different thickness of PDMS molds have been tested. It is found that 870 μm thick mold is good for fine duplication and durability. We have successfully fabricated the first microlens hemisphere of 51 μm diameter and the second microlens of 3 μm diameter on top of the first. The double microlens array shows more focused light spot when viewed through optical microscope.     

A novel deep learning framework for double JPEG compression detection of small size blocks

Double JPEG compression detection plays a vital role in multimedia forensics, to find out whether a JPEG image is authentic or manipulated. However, it still remains to be a challenging task in the case when the quality factor of the first compression is much higher than that of the second compression, as well as in the case when the targeted image blocks are quite small. In this work, we present a novel end-to-end deep learning framework taking raw DCT coefficients as input to distinguish between single and double compressed images, which performs superior in the above two cases. Our proposed framework can be divided into two stages. In the first stage, we adopt an auxiliary DCT layer with sixty-four 8 × 8 DCT kernels. Using a specific layer to extract DCT coefficients instead of extracting them directly from JPEG bitstream allows our proposed framework to work even if the double compressed images are stored in spatial domain, e.g. in PGM, TIFF or other bitmap formats. The second stage is a deep neural network with multiple convolutional blocks to extract more effective features. We have conducted extensive experiments on three different image datasets. The experimental results demonstrate the superiority of our framework when compared with other state-of-the-art double JPEG compression detection methods either hand-crafted or learned using deep networks in the literature, especially in the two cases mentioned above. Furthermore, our proposed framework can detect triple and even multiple JPEG compressed images, which is scarce in the literature as far as we know.     

22 nm silicon nanowire gas sensor fabricated by trilayer nanoimprint and wet etching

In this work, we demonstrate the fabrication of silicon nanowires down to 22 nm wide using trilayer nanoimprint lithography and wet etching. Using the same template prepared by E-beam lithography (EBL), nanowires with top width of 22 nm and 75 nm are fabricated on boron-doped top silicon layer of SOI substrate. The two samples are tested in 250 ppm NO₂ ambient for gas detection. The 22 nm wide one shows a much higher relative sensitivity than the 75 nm wide one. The simulation which calculates the carrier density by solving Poisson equation was carried out and the results well explain the sensitivity disparity between the two samples.     

Polypyrrole/reduced graphene oxide coated fabric electrodes for supercapacitor application

Flexible and wearable energy storage devices are strongly demanded to power smart textiles. Herein, reduced graphene oxide (RGO) and polypyrrole (PPy) were deposited on cotton fabric via thermal reduction of GO and chemical polymerization of pyrrole to prepare textile-based electrodes for supercapacitor application. The obtained PPy–RGO-fabric retained good flexibility of textile and was highly conductive, with the conductivity of 1.2 S cm⁻¹. The PPy–RGO-fabric supercapacitor showed a specific capacitance of 336 F g⁻¹ and an energy density of 21.1 Wh kg⁻¹ at a current density of 0.6 mA cm⁻². The RGO sheets served as conductor and framework under the PPy layer, which could facilitate electron transfer between RGO and PPy and restrict the swelling and shrinking of PPy, thus resulting in improved electrochemical properties respect to the PPy-fabric device.     

An NTF-enhanced incremental ΣΔ modulator using a SAR quantizer

In this paper, a noise transfer function (NTF) enhanced incremental sigma-delta (ΣΔ) modulator is presented. It employs a charge redistribution successive approximation register (SAR) analog-to-digital converter (ADC) in an error-feedback scheme to achieve an extra noise-shaping order. Using a multi-bit SAR quantizer not only improves the stability and power consumption but also facilitates the realization of both the adder situated in front of the quantizer and the whole error-feedback loop. As a design example, a multiplexed 2nd-order modulator based on the proposed architecture is simulated in TSMC 90 nm CMOS technology using Spectre with a 1 V single power supply. The simulation results show a signal-to-noise and distortion ratio (SNDR) of 85.3 dB within a signal bandwidth of 20 kHz (1 kHz/channel) at 5 MHz sampling frequency. The power consumption for each channel is 8.6 µW.     

Efficient architecture of variable size HEVC 2D-DCT for FPGA platforms

This study presents a design of two-dimensional (2D) discrete cosine transform (DCT) hardware architecture dedicated for High Efficiency Video Coding (HEVC) in field programmable gate array (FPGA) platforms. The proposed methodology efficiently proceeds 2D-DCT computation to fit internal components and characteristics of FPGA resources. A four-stage circuit architecture is developed to implement the proposed methodology. This architecture supports variable size of DCT computation, including 4 × 4, 8 × 8, 16 × 16, and 32 × 32. The proposed architecture has been implemented in System Verilog and synthesized in various FPGA platforms. Compared with existing related works in literature, this proposed architecture demonstrates significant advantages in hardware cost and performance improvement. The proposed architecture is able to sustain 4 K@30 fps ultra high definition (UHD) TV real-time encoding applications with a reduction of 31–64% in hardware cost.     

Inter-BSs virtual private network for privacy and security enhanced 60 GHz radio-over-fiber system

A novel inter-basestations (inter-BSs) based virtual private network (VPN) for the privacy and security enhanced 60 GHz radio-over-fiber (RoF) system using optical code-division multiplexing (OCDM) is proposed and demonstrated experimentally. By establishing inter-BSs VPN overlaying the network structure of a 60 GHz RoF system, the express and private paths for the communication of end-users under different BSs can be offered. In order to effectively establish the inter-BSs VPN, the OCDM encoding/decoding technology is employed in the RoF system. In each BS, a 58 GHz millimeter-wave (MMW) is used as the inter-BSs VPN channel, while a 60 GHz MMW is used as the common central station (CS)–BSs communication channel. The optical carriers used for the downlink, uplink and VPN link transmissions are all simultaneously generated in a lightwave-centralized CS, by utilizing four-wave mixing (FWM) effect in a semiconductor optical amplifier (SOA). The obtained results properly verify the feasibility of our proposed configuration of the inter-BSs VPN in the 60 GHz RoF system.     

A high performance 5 stage pipeline architecture for the H.264/AVC deblocking filter

Exploiting specific properties of the algorithm, a high-throughput pipelined architecture is introduced to implement the H.264/AVC deblocking filter. The architecture was synthesized in 0.18 μm technology and the clock frequency and area are 400 MHz and 16.8 Kgates, respectively. Also, it is able to filter 217 and 55 Frames per second (Fps) for Full- and Ultra-HD videos, respectively. The introduced architecture outperforms similar ones in terms of frequency (1.8× up to 4×), throughput, (1.5× up to 3.8×), and Fps. Moreover, extensions to support different sample bit-depths and chroma formats are included. Also, experimental results for different FPGA families are offered.     

Optimal-correlation-based reconstruction for distributed compressed video sensing

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient joint reconstruction by leveraging more realistic signal models is still an open challenge. In this paper, we present a novel optimal-correlation-based reconstruction method for compressively sampled videos from multiple measurement vectors. In our method, the sparsity is mainly exploited through inter-signal correlations rather than the traditional frequency transform, wherein the optimization is not only over the signal space to satisfy data consistency but also over all possible linear correlation models to achieve minimum-l₁-norm correlation noise. Additionally, a two-phase Bregman iterative based algorithm is outlined for solving the optimization problem. Simulation results show that our proposal can achieve an improved reconstruction performance in comparison to the conventional approaches, and especially, offer a 0.7–9.9 dB gain in the average PSNR for DCVS.     

Flexible,plastic transistor-based chemical sensors

Flexible, plastic chemical sensors were fabricated using a thin polymer gate dielectric layer and polymer electrodes patterned via selective wetting directly on the surface of the organic semiconductor film. Low-voltage transistors based on DDFTTF with PEDOT:PSS electrodes had a mobility as high as 0.05 cm²/Vs with an on–off ratio of 1.2 × 10⁴ on ITO/PET substrates. These devices demonstrated stable operation in water with sensor characteristics similar to those reported on rigid silicon substrates, with sub-ppm detection for cysteine and 2,4,6-trinitrobenzene (TNB).     

Injection locking phase rotator for Outphasing transmitter

This paper presents a novel technique of implementing the amplitude information into out-phase mapping, which is a necessary block of the high-efficiency Outphasing transmitter architecture. The proposed technique is based on using injection locking ring oscillator and switching-based control circuit to implement phase rotator. The technique is compatible with digital implementation using DSP. Since, Outphasing transmitters use switching power amplifiers, this implementation is suitable for an all-digital and adjustable transmitter implementation. The modulator system is designed using UMC130 nm CMOS technology; and is simulated at 1.8 GHz operation frequency, as it is commonly used in multiple mobile applications requiring high power levels. Simulation shows an out-phasing error of 0.41° rms, across the whole input amplitude sweep of 45 dB. The power consumption of the single phase rotator is 1.5 mW from 1.2 V supply.     

Intra mode prediction for H.266/FVC video coding based on convolutional neural network

The next-generation video compression standard H.266/Future Video Coding (FVC) provides high compression efficiency in terms of the cost of computing the optimal intra mode from 67 modes. We propose an intra mode prediction method based on a convolutional neural network (CNN). An input image set of 20 × 20 blocks is used to train the CNN; the CNN is used to predict the best classes of intra mode direction. The CNN architecture comprises two convolutional layers and a fully connected layer. Compared with the default fast search method in FVC, the proposed method can achieve a 0.033% decrease in Bjøntegaard delta bit rate (BDBR) with only a slight increase in time.     

Studies on various chip-on-film (COF) packages using ultra fine pitch two-metal layer flexible printed circuits (two-metal layer FPCs)

Various fine pitch chip-on-film (COF) packages assembled by (1) anisotropic conductive film (ACF), (2) nonconductive film (NCF), and (3) AuSn metallurgical bonding methods using fine pitch flexible printed circuits (FPCs) with two-metal layers were investigated in terms of electrical characteristics, flip chip joint properties, peel adhesion strength, heat dissipation capability, and reliability. Two-metal layer FPCs and display driver IC (DDI) chips with 35 μm, 25 μm, and 20 μm pitch were prepared. All the COF packages using two-metal layer FPCs assembled by three bonding methods showed stable flip chip joint shapes, stable bump contact resistances below 5 mΩ, good adhesion strength of more than 600 gf/cm, and enhanced heat dissipation capability compared to a conventional COF package using one-metal layer FPCs. A high temperature/humidity test (85 °C/85% RH, 1000 h) and thermal cycling test (T/C test, ?40 °C to + 125 °C, 1000 cycles) were conducted to verify the reliability of the various COF packages using two-metal layer FPCs. All the COF packages showed excellent high temperature/humidity and T/C reliability, however, electrically shorted joints were observed during reliability tests only at the ACF joints with 20 μm pitch. Therefore, for less than 20 μm pitch COF packages, NCF adhesive bonding and AuSn metallurgical bonding methods are recommended, while all the ACF and NCF adhesives bonding and AuSn metallurgical bonding methods can be applied for over 25 μm pitch COF applications. Furthermore, we were also able to demonstrate double-side COF using two-metal layer FPCs.     

Nb-doped TiO2 sol–gel films for CO sensing applications

Nb doped titania (TiO₂:Nb) multilayered films (1–10 layers) with anatase structure were obtained by the low-cost sol–gel and dipping method on microscope glass substrates, followed by thermal treatment at 450 °C for 1 h. After each layer deposition, an intermediate annealing step was performed at 300 °C for 30 min. Doping TiO₂ sol–gel films with a low amount of Nb (0.8 at%) allows obtaining an improved CO sensor able to operate under environmental atmosphere (air). It was found that the sensor sensitivity is less dependent on the film thickness but is significantly influenced by Nb doping at the optimal working temperature of 400 °C. Good recovery characteristics were obtained for a wide CO detection range, between 0 and 2000 ppm. The gas-sensing behavior of the films was correlated with the structural, chemical and morphological properties of the multi-layered structures.     

Tunable polarization maintaining fiber Bragg grating based OSNR monitor

A simple optical performance monitoring scheme based on a tunable polarization maintaining fiber Bragg grating is proposed. The proposed technique measures the in-band optical signal-to-noise-ratio through orthogonal polarization detection. The scheme is successfully demonstrated for NRZ-OOK signals at 10 Gb/s with an input dynamic range of around 20 dB. The results show that the performance of the scheme is not sensitive to the effects of chromatic dispersion.     

A reversible steganographic scheme for VQ indices based on locally adaptive coding

Achieving a high embedding capacity and low compression rate with a reversible data hiding method in the vector quantization (VQ) compressed domain is a technically challenging problem. This paper proposes a novel reversible steganographic scheme for VQ compressed images based on a locally adaptive data compression method. The proposed method embeds n secret bits into one VQ index of an index table in Hilbert-curve scan order. The experimental results show that the proposed method can achieve the different average embedding rates of 0.99, 1.68, 2.28, and 3.04 bit per index (bpi) and average compression rates of 0.45, 0.46, 0.5, and 0.56 bit per pixel (bpp) for n = 1, 2, 3, and 4, respectively. These results indicate that the proposed scheme is superior to Chang et al.’s scheme 1 [19], Yang and Lin’s scheme [21], and Chang et al.’s scheme 2 [24].