Electromagnetic analysis (EMA) against public-key cryptographic software on an embedded OS is presented in this paper. First, we propose a method for finding an observation point for EMA, where the EM radiation caused by cryptographic operations can be observed with low noise. The basic idea is to find specific EM radiation patterns produced by cryptographic operations given specific input pattern. During the operations, we scan the surface of the target device(s) with a micro magnetic probe. The scan is optimized in advanced using another compatible device that has the same central processing unit (CPU) and OS as the target device. We demonstrate the validity of the proposed EMAs through some EMA experiments with two types of RSA software on an embedded OS platform. The two types of RSA software have different implementations for modular multiplication algorithms: one is a typical and ready-made implementation using BigInteger class on Java standard library, and another is a custom-made implementation based on the Montgomery multiplication algorithm. We conduct experiments of chosen-message EMA using our scanning method, and show such EMAs successfully reveal the secret key of RSA software even under the noisy condition of the embedded OS platform. We also discuss some countermeasures against the above EMAs.

In this paper, we propose a method for reconstructing 3D sequential patterns from multiple images without knowing exact image correspondences and without calibrating linear camera sensitivity parameters on intensity. The sequential pattern is defined as a series of colored 3D points. We assume that the series of the points are obtained in multiple images, but the correspondence of individual points is not known among multiple images. For reconstructing sequential patterns, we consider a camera projection model which combines geometric and photometric information of objects. Furthermore, we consider camera projections in the frequency space. By considering the multi-view relationship on the new projection model, we show that the 3D sequential patterns can be reconstructed without knowing exact correspondence of individual image points in the sequential patterns; moreover, the recovered 3D patterns do not suffer from changes in linear camera sensitivity parameters. The efficiency of the proposed method is tested using real images.

Breast cancer is a serious disease across the world, and it is one of the largest causes of cancer death for women. The traditional diagnosis is not only time consuming but also easily affected. Hence, artificial intelligence (AI), especially neural networks, has been widely used to assist to detect cancer. However, in recent years, the computational ability of a neuron has attracted more and more attention. The main computational capacity of a neuron is located in the dendrites. In this paper, a novel neuron model with dendritic nonlinearity (NMDN) is proposed to classify breast cancer in the Wisconsin Breast Cancer Database (WBCD). In NMDN, the dendrites possess nonlinearity when realizing the excitatory synapses, inhibitory synapses, constant-1 synapses and constant-0 synapses instead of being simply weighted. Furthermore, the nonlinear interaction among the synapses on a dendrite is defined as a product of the synaptic inputs. The soma adds all of the products of the branches to produce an output. A back-propagation-based learning algorithm is introduced to train the NMDN. The performance of the NMDN is compared with classic back propagation neural networks (BPNNs). Simulation results indicate that NMDN possesses superior capability in terms of the accuracy, convergence rate, stability and area under the ROC curve (AUC). Moreover, regarding ROC, for continuum values, the existing 0-connections branches after evolving can be eliminated from the dendrite morphology to release computational load, but with no influence on the performance of classification. The results disclose that the computational ability of the neuron has been undervalued, and the proposed NMDN can be an interesting choice for medical researchers in further research.

In this letter, high quality speech reconstruction approaches from Mel-frequency cepstral coefficients (MFCC) are presented. Taking into account of the nonnegative and sparse properties of the speech power spectrum, an alternating direction method of multipliers (ADMM) based nonnegative l2 norm (NL2) and weighted nonnegative l2 norm (NWL2) minimization approach is proposed to cope with the under-determined nature of the reconstruction problem. The phase spectrum is recovered by the well-known LSE-ISTFTM algorithm. Experimental results demonstrate that the NL2 and NWL2 approach substantially achieves better quality for reconstructed speech than the conventional l2 norm minimization approach, it sounds very close to the original speech when using the high-resolution MFCC, the PESQ score reaches 4.0.

RF under sampling is more suitable for Satellite receiver systems in comparison to terrestrial systems. In conventional RF under sampling the minimum sampling frequency (fs) should be atleast twice the system bandwidth; therefore for a system with a wide bandwidth, a relatively high fs is necessary. In this paper we propose a direct RF under sampling reception method that halves fs. The proposed f's is achieved by folding in band noise in half. A method of adapting f's for the reception of signals in different channels is also proposed; this ensures that the SNR is not degraded for any channel. To evaluate the proposed technique's performance and compare it to the conventional case a 3 channel, 1 GHz band test receiver and it's key device (i.e. S/H circuit) are developed. Using SNR and EVM as performance indexes, the performance of the proposed technique has been evaluated and compared to that of the conventional technique. The evaluation results show that the proposed technique can achieve the same performance as conventional RF under sampling for all 3 channels, using only half of the sampling frequency of the conventional technique.

A two-handed distance control method is proposed for precisely and efficiently manipulating a virtual 3D object by hand in an immersive virtual reality environment. The proposed method enhances direct manipulation by hand and is used to precisely control and efficiently adjust the position of an object and the viewpoint using the distance between the two hands. The two-handed method is evaluated and compared with the previously proposed one-handed speed control method, which adjusts the position of an object in accordance with the speed of one hand. The results from experimental evaluation show that two-handed methods, which make position and viewpoint adjustments, are the best among six combinations of control and adjustment methods.

Time redundancy is sometimes an only option for enhancing circuit reliability when the circuit area is severely restricted. In this paper, a time-redundant error-correction scheme, which is particularly suitable for coarse-grained reconfigurable arrays (CGRAs), is proposed. It judges the correctness of the executions by comparing the results of two identical runs. Once a mismatch is found, the second run is terminated immediately to start the third run, under the assumption that the errors tend to persist in many applications, for selecting the correct result in the three runs. The circuit area and reliability of the proposed method is compared with a straightforward implementation of time-redundancy and a selective triple modular redundancy (TMR). A case study on a CGRA revealed that the area of the proposed method is 1% larger than that of the implementation for the selective TMR. The study also shows the proposed scheme is up to 2.6x more reliable than the full-TMR when the persistent error is predominant.

In deep-submicron era, interconnection delays are not negligible even in high-level synthesis and regular-distributed-register architectures (RDR architectures) have been proposed to cope with this problem. In this paper, we propose a high-level synthesis algorithm using operation chainings which reduces the overall latency targeting RDR architectures. Our algorithm consists of three steps: The first step enumerates candidate operations for chaining. The second step introduces maximal chaining distance (MCD), which gives the maximal allowable inter-island distance on RDR architecture between chaining candidate operations. The last step performs list-scheduling and binding simultaneously based on the results of the two preceding steps. Our algorithm enumerates feasible chaining candidates and selects the best ones for RDR architecture. Experimental results show that our proposed algorithm reduces the latency by up to 40.0% compared to the original approach, and by up to 25.0% compared to a conventional approach. Our algorithm also reduces the number of registers and the number of multiplexers compared to the conventional approaches in some cases.

In this paper, we propose Affine Combination Lattice Algorithm (ACLA) as a new lattice-based adaptive notch filtering algorithm. The ACLA makes use of the affine combination of Regalia's Simplified Lattice Algorithm (SLA) and Lattice Gradient Algorithm (LGA). It is proved that the ACLA has faster convergence speed than the conventional lattice-based algorithms. We conduct this proof by means of theoretical analysis of the mean update term. Specifically, we show that the mean update term of the ACLA is always larger than that of the conventional algorithms. Simulation examples demonstrate the validity of this analytical result and the utility of the ACLA. In addition, we also derive the step-size bound for the ACLA. Furthermore, we show that this step-size bound is characterized by the gradient of the mean update term.

Motion estimation (ME) is a key encoding component of almost all modern video coding standards. ME contributes significantly to video coding efficiency, but, it also consumes the most power of any component in a video encoder. In this paper, an ME processor with 3D stacked memory architecture is proposed to reduce memory and core power consumption. First, a memory die is designed and stacked with ME die. By adding face-to-face (F2F) pads and through-silicon-via (TSV) definitions, 2D electronic design automation (EDA) tools can be extended to support the proposed 3D stacking architecture. Moreover, a special memory controller is applied to control data transmission and timing between the memory die and the ME processor die. Finally, a 3D physical design is completed for the entire system. This design includes TSV/F2F placement, floor plan optimization, and power network generation. Compared to 2D technology, the number of input/output (IO) pins is reduced by 77%. After optimizing the floor plan of the processor die and memory die, the routing wire lengths are reduced by 13.4% and 50%, respectively. The stacking static random access memory contributes the most power reduction in this work. The simulation results show that the design can support real-time 720p @ 60fps encoding at 8MHz using less than 65mW in power, which is much better compared to the state-of-the-art ME processor.

We address a robust algorithm for the interference-plus-noise covariance matrix reconstruction (RA-INCMR) against random arbitrary steering vector mismatches (RASVMs) of the interferences, which lead to substantial degradation of the original INCMR beamformer performance. Firstly, using the worst-case performance optimization (WCPO) criteria, we model these RASVMs as uncertainty sets and then propose the RA-INCMR to obtain the robust INCM (RINCM) based on the Robust Capon Beamforming (RCB) algorithm. Finally, we substitute the RINCM back into the original WCPO beamformer problem for the sample covariance matrix to formulate the new RA-INCM-WCPO beamformer problem. Simulation results demonstrate that the performance of the proposed beamformer is much better than the original INCMR beamformer when there exist RASVMs, especially at low signal-to-noise ratio (SNR).

In this paper the amplitude probability distribution (APD) measurement method is applied to evaluate noise coupling to an antenna on an evaluation board that uses mixed RF and digital signals of an IC. We analytically investigate noise coupling path to the antenna where the correlation coefficient matches the APD curve of the evaluation board. Moreover, in order to verify the analysis results, the noise coupling path in the board is evaluated by measurements involving In-phase/Quadrature (I/Q) signals as well as electromagnetic simulations. As a result, we demonstrate that APD method is effective in evaluating a degree of noise coupling from an IC to multiple antennas on the board, and confirm that the intensity of noise coupling to each antenna is affected greatly by the board layout patterns.

In recent years, applications of complex-valued neural networks have become wide spread. Quaternions are an extension of complex numbers, and neural networks with quaternions have been proposed. Because quaternion algebra is non-commutative algebra, we can consider two orders of multiplication to calculate weighted input. However, both orders provide almost the same performance. We propose hybrid quaternionic Hopfield neural networks, which have both orders of multiplication. Using computer simulations, we show that these networks outperformed conventional quaternionic Hopfield neural networks in noise tolerance. We discuss why hybrid quaternionic Hopfield neural networks improve noise tolerance from the standpoint of rotational invariance.

The authors have been researching on reducing the power consumption of microprocessors, and developed a low-power processor called “Geyser” by applying power gating (PG) function to the individual functional units of the processor. PG function on Geyser reduces the power consumption of functional units by shutting off the power voltage of idle units. However, the energy overhead of switching the supply voltage for units on and off causes power increases. The amount of the energy overhead varies with the behavior of each functional unit which is influenced by running application, and also with the core temperature. It is therefore necessary to switch the PG function itself on or off according to the state of the processor at runtime to reduce power consumption more effectively. In this paper, the authors propose a PG control method to take the power overhead into account by the operating system (OS). In the proposed method, for achieving much power reduction, the OS calculates the power consumption of each functional unit periodically and inhibits the PG function of the unit whose energy overhead is judged too high. The method was implemented in the Linux process scheduler and evaluated. The results show that the average power consumption of the functional units is reduced by up to 17.2%.

This paper presents wireless systems for use in disaster recovery operations. The Great East Japan Earthquake of March 11, 2011 reinforced the importance of communications in, to, and between disaster areas as lifelines. It also revealed that conventional wireless systems used for disaster recovery need to be renovated to cope with technological changes and to provide their services with easier operations. To address this need we have developed new systems, which include a relay wireless system, subscriber wireless systems, business radio systems, and satellite communication systems. They will be chosen and used depending on the situations in disaster areas as well as on the required services.

In this paper, for an odd prime p and i=0,1, we investigate the cross-correlation between two decimated sequences, s(2t+i) and s(dt), where s(t) is a p-ary m-sequence of period pn-1. Here we consider two cases of ${d}$, ${d=rac{(p^m +1)^2}{2} }$ with ${n=2m}$, ${p^m equiv 1 pmod{4}}$ and ${d=rac{(p^m +1)^2}{p^e + 1}}$ with n=2m and odd m/e. The value distribution of the cross-correlation function for each case is completely determined. Also, by using these decimated sequences, two new p-ary sequence families of period ${rac{p^n -1}{2}}$ with good correlation property are constructed.

A digital spatial modulation method has been demonstrated for a wireless power transmission system at 5.8 GHz. Interference of electromagnetic waves, which are radiated from the dual scatterers, successfully realizes the spatial modulation. The spatial modulation is performed with a digital modulation manner by controlling capacitances embedded in one of the dual scatterers so that the interference of the scattered waves is appropriately changed. Switch MMICs based on p-HEMT technology was newly developed for the spatial modulation. Measured insertion losses of the switch MMIC are 1.0 dB and 14 dB for on and off states at 5.8 GHz, respectively. The isolation is more than 20 dB. With the switch MMIC, digital spatial modulation characteristics were experimentally demonstrated at 5.8 GHz. One-bit amplitude shift keying (ASK) for 1 MHz signal was realized at 5.8 GHz, and two levels were clearly discriminated. The modulation factor is 36%. In addition, 2-bit ASK signal was detected at 7.1 GHz.

A miniaturized patch hybrid coupler with arbitrary power ratio and impedance transformation is proposed and designed by loading a pair of asymmetric cross slots on a squared patch resonator. To obtain the arbitrary power ratio and impedance transformation, the rectangular size of stepped slot ends should be well designed to be asymmetry and thus to obtain the different inductive loadings along two current paths. Theoretically, the equivalent transmission line model is first developed to understand the physical relationship between the patch and traditional branch-line hybrids. The matching/isolation and power ratio conditions are then derived at center frequency. By following a detailed design guideline, a prototype of the hybrid with 1:2 power ratio and 1:1.3 impedance transformation is designed and fabricated at 4.2 GHz. The measured results show a good agreement with simulated results, where the measured -10 dB impedance bandwidth achieves 18% and the bandwidth of 90°±6° phase difference is about 35% in a frequency range from 3.5 GHz to 5 GHz.

This paper presents an information hiding method for DNA steganography with which a massive amount of data can be hidden in a noncoding strand. Our method maps the encrypted data to the DNA sequence using a numerical mapping table, before concealing it in the noncoding sequence using a secret key comprising sector length and the random number generator's seed. Our encoding algorithm is sector-based and reference dependent. Using modular arithmetic, we created a unique binary-base translation for every sector. By conducting a simulation study, we showed that our method could preserve amino acid information, extract hidden data without reference to the host DNA sequence, and detect the position of mutation error. Experimental results verified that our method produced higher data capacity than conventional methods, with a bpn (bit-per-nucleotide) value that ranged from approximately 1-2, depending on the selected sector length. Additionally, our novel method detected the positions of mutation errors by the presence of a parity base in each sector.

We propose a method of spread spectrum digital watermarking with quantization index modulation (QIM) and evaluate the method on the basis of IHC evaluation criteria. The spread spectrum technique can make watermarks robust by using spread codes. Since watermarks can have redundancy, messages can be decoded from a degraded stego-image. Under IHC evaluation criteria, it is necessary to decode the messages without the original image. To do so, we propose a method in which watermarks are generated by using the spread spectrum technique and are embedded by QIM. QIM is an embedding method that can decode without an original image. The IHC evaluation criteria include JPEG compression and cropping as attacks. JPEG compression is lossy compression. Therefore, errors occur in watermarks. Since watermarks in stego-images are out of synchronization due to cropping, the position of embedded watermarks may be unclear. Detecting this position is needed while decoding. Therefore, both error correction and synchronization are required for digital watermarking methods. As countermeasures against cropping, the original image is divided into segments to embed watermarks. Moreover, each segment is divided into 8×8 pixel blocks. A watermark is embedded into a DCT coefficient in a block by QIM. To synchronize in decoding, the proposed method uses the correlation between watermarks and spread codes. After synchronization, watermarks are extracted by QIM, and then, messages are estimated from the watermarks. The proposed method was evaluated on the basis of the IHC evaluation criteria. The PSNR had to be higher than 30 dB. Ten 1920×1080 rectangular regions were cropped from each stego-image, and 200-bit messages were decoded from these regions. Their BERs were calculated to assess the tolerance. As a result, the BERs were less than 1.0%, and the average PSNR was 46.70 dB. Therefore, our method achieved a high image quality when using the IHC evaluation criteria. In addition, the proposed method was also evaluated by using StirMark 4.0. As a result, we found that our method has robustness for not only JPEG compression and cropping but also additional noise and Gaussian filtering. Moreover, the method has an advantage in that detection time is small since the synchronization is processed in 8×8 pixel blocks.