This paper focuses on power-area trade-off axis to memory systems. Compared with the power-performance-area trade-off application on the traditional high performance cache, this paper focuses on the edge processing environment which is becoming more and more important in the Internet of Things (IoT) era. A new power-oriented trade-off is proposed for on-chip cache architecture. As a case study, this paper exploits a good energy efficiency of Standard-Cell Memory (SCM) operating in a near-threshold voltage region and a good area efficiency of Static Random Access Memory (SRAM). A hybrid 2-level on-chip cache structure is first introduced as a replacement of 6T-SRAM cache as L0 cache to save the energy consumption. This paper proposes a method for finding the best capacity combination for SCM and SRAM, which minimizes the energy consumption of the hybrid cache under a specific cache area constraint. The simulation result using a 65-nm process technology shows that up to 80% energy consumption is reduced without increasing the die area by replacing the conventional SRAM instruction cache with the hybrid 2-level cache. The result shows that energy consumption can be reduced if the area constraint for the proposed hybrid cache system is less than the area which is equivalent to a 8kB SRAM. If the target operating frequency is less than 100MHz, energy reduction can be achieved, which implies that the proposed cache system is suitable for low-power systems where a moderate processing speed is required.

We propose two secret sharing schemes realizing general access structures, which are based on unauthorized subsets. In the proposed schemes, shares are generated by Tassa's (k,n)-hierarchical threshold scheme instead of Shamir's (k,n)-threshold scheme. Consequently, the proposed schemes can reduce the number of shares distributed to each participant.

We propose a method that detects vehicles from in-vehicle monocular camera images captured during nighttime driving. Detecting vehicles from their shape is difficult at night; however, many vehicle detection methods focusing on light have been proposed. We detect bright spots by appropriate binarization based on the characteristics of vehicle lights such as brightness and color. Also, as the detected bright spots include lights other than vehicles, we need to distinguish the vehicle lights from other bright spots. Therefore, the bright spots were distinguished using Random Forest, a multiclass classification machine-learning algorithm. The features of bright spots not associated with vehicles were effectively utilized in the vehicle detection in our proposed method. More precisely vehicle detection is performed by giving weights to the results of the Random Forest based on the features of vehicle bright spots and the features of bright spots not related to the vehicle. Our proposed method was applied to nighttime images and confirmed effectiveness.

In secret sharing schemes for general access structures, an important issue is the number of shares distributed to each participant. However, in general, the existing schemes are impractical in this respect when the size of the access structure is very large. In 2015, a secret sharing scheme that can reduce the number of shares distributed to specified participants was proposed (the scheme A of T15). In this scheme, we can select a subset of participants and reduce the number of shares distributed to any participant who belongs to the selected subset though this scheme cannot reduce the number of shares distributed to every participant. In other words, this scheme cannot reduce the number of shares distributed to each participant who does not belong to the selected subset. In this paper, we modify the scheme A of T15 and propose a new secret sharing scheme realizing general access structures. The proposed scheme can reduce the number of shares distributed to each participant who does not belong to the selected subset as well. That is, the proposed scheme is more efficient than the scheme A of T15.

In this paper, we propose a new dynamic load balancing scheme according to load threshold adjustment and incentives mechanism. The proposed scheme adjusts the load threshold of a node by comparing it with a mean threshold of adjacent nodes, thereby increasing the threshold evenly. We also assign the incentives and penalties to each node through a comparison of the mean threshold of all the nodes in order to increase autonomous load balancing participation.

This paper presents an ultra-low-power class-AB bulk-driven operational transconductance amplifier operating in the subthreshold region. Employing the partial positive feedback in current mirrors, the effective transconductance and output voltage swing are enhanced considerably without additional power consumption and layout area. Both traditional and proposed OTAs are designed and simulated for a 180 nm CMOS process. They dissipate an ultra low power of 192 nW. The proposed OTA features not only a DC gain enhancement of 14 dB but also a slew rate improvement of 200%. In addition, the improved gain leads to a 5.3 times wider unity-gain bandwidth than that of the traditional OTA.

We report the control of threshold voltage (Vth) for low voltage (5V) operation in OFET by using double gate dielectric layers composed of poly (vinyl cinnamate) and SiO2. We succeeded in realizing a driving voltage of -5V and Vth shift by c.a. 1.0V. And programmed Vth was almost unchanged for 104s, where the relative change of Vth remains more than 99%.

This study proposes a multiple-output differential-input operational transconductance amplifier-C (MODI OTA-C) filter with an impedance scaler to detect cardiac activity. A ladder-type fifth-orderButterworth low-pass filter with a large time constant and low noise is implemented to reduce coefficient sensitivity and address signal distortion. Moreover, linearized MODI OTA structures with reduced transconductance and impedance scaler circuits for noise reduction are used to achieve a wide dynamic range (DR). The OTA-based circuit is operated in the subthreshold region at a supply voltage of 1 V to reduce the power consumption of the wearable device in long-term use. Experimental results of the filter with a bandwidth of 250 Hz reveal that DR is 57.6 dB, and the harmonic distortion components are below -59 dB. The power consumption of the filter, which is fabricated through a TSMC 0.18 µm CMOS process, is lower than 390 nW, and the active area is 0.135 mm2.

In this paper, we review a super-steep subthreshold slope (SS) (<1 mV/dec) body-tied (BT) silicon on insulator (SOI) metal oxide semiconductor field effect transistor (MOSFET) fabricated with 0.15 µm SOI technology and discuss the possibility of its use in ultralow voltage applications. The mechanism of the super-steep SS in the BT SOI MOSFET was investigated with technology computer-aided design simulation. The gate length/width and Si thickness optimizations promise further reductions in operation voltage, as well as improvement of the ION/IOFF ratio. In addition, we demonstrated control of the threshold voltage and hysteresis characteristics using the substrate and body bias in the BT SOI MOSFET.

The energy of a threshold circuit C is defined to be the maximum number of gates outputting ones for an input assignment, where the maximum is taken over all the input assignments. In this paper, we study computational power of threshold circuits of energy at most two. We present several results showing that the computational power of threshold circuits of energy one and the counterpart of energy two are remarkably different. In particular, we give an explicit function which requires an exponential size for threshold circuits of energy one, but is computable by a threshold circuit of size just two and energy two. We also consider MOD functions and Generalized Inner Product functions, and show that these functions also require exponential size for threshold circuits of energy one, but are computable by threshold circuits of substantially less size and energy two.

The concept of threshold public key encryption (TPKE) with the special property called key re-splittability (re-splittable TPKE, for short) was introduced by Hanaoka et al. (CT-RSA 2012), and used as one of the building blocks for constructing their proxy re-encryption scheme. In a re-splittable TPKE scheme, a secret key can be split into a set of secret key shares not only once, but also multiple times, and the security of the TPKE scheme is guaranteed as long as the number of corrupted secret key shares under the same splitting is smaller than the threshold. In this paper, we show several new constructions of a re-splittable TPKE scheme by extending the previous (ordinary) TPKE schemes. All of our proposed schemes are based on discrete logarithm (DL)-type assumptions. Therefore, our results suggest that key re-splittability is a very natural property for DL-type TPKE schemes.

We present an explicit construction of a MAJn-2 °MAJn-2 circuit computing MAJn for every odd n≥7. This gives a partial solution to an open problem by Kulikov and Podolskii (Proc. of STACS 2017, Article No.49).

In this paper, a multilevel thresholding color image segmentation method is proposed using a modified Artificial Bee Colony(ABC) algorithm. In this work, in order to improve the local search ability of ABC algorithm, Krill Herd algorithm is incorporated into its onlooker bees phase. The proposed algorithm is named as Krill herd-inspired modified Artificial Bee Colony algorithm (KABC algorithm). Experiment results verify the robustness of KABC algorithm, as well as its improvement in optimizing accuracy and convergence speed. In this work, KABC algorithm is used to solve the problem of multilevel thresholding for color image segmentation. To deal with luminance variation, rather than using gray scale histogram, a HSV space-based pre-processing method is proposed to obtain 1D feature vector. KABC algorithm is then applied to find thresholds of the feature vector. At last, an additional local search around the quasi-optimal solutions is employed to improve segmentation accuracy. In this stage, we use a modified objective function which combines Structural Similarity Index Matrix (SSIM) with Kapur's entropy. The pre-processing method, the global optimization with KABC algorithm and the local optimization stage form the whole color image segmentation method. Experiment results show enhance in accuracy of segmentation with the proposed method.

Automatic detection of heart cycle abnormalities in a long duration of ECG data is a crucial technique for diagnosing an early stage of heart diseases. Concretely, Paroxysmal stage of Atrial Fibrillation rhythms (ParAF) must be discriminated from Normal Sinus rhythms (NS). The both of waveforms in ECG data are very similar, and thus it is difficult to completely detect the Paroxysmal stage of Atrial Fibrillation rhythms. Previous studies have tried to solve this issue and some of them achieved the discrimination with a high degree of accuracy. However, the accuracies of them do not reach 100%. In addition, no research has achieved it in a long duration, e.g. 12 hours, of ECG data. In this study, a new mechanism to tackle with these issues is proposed: “Door-to-Door” algorithm is introduced to accurately and quickly detect significant peaks of heart cycle in 12 hours of ECG data and to discriminate obvious ParAF rhythms from NS rhythms. In addition, a quantitative method using Artificial Neural Network (ANN), which discriminates unobvious ParAF rhythms from NS rhythms, is investigated. As the result of Door-to-Door algorithm performance evaluation, it was revealed that Door-to-Door algorithm achieves the accuracy of 100% in detecting the significant peaks of heart cycle in 17 NS ECG data. In addition, it was verified that ANN-based method achieves the accuracy of 100% in discriminating the Paroxysmal stage of 15 Atrial Fibrillation data from 17 NS data. Furthermore, it was confirmed that the computational time to perform the proposed mechanism is less than the half of the previous study. From these achievements, it is concluded that the proposed mechanism can practically be used to diagnose early stage of heart diseases.

New deblocking artifact, or blocking artifact reduction, algorithms based on nonlinear adaptive soft-threshold anisotropic filter in wavelet are proposed. Our deblocking algorithm uses soft-threshold, adaptive wavelet direction, adaptive anisotropic filter, and estimation. The novelties of this paper are an adaptive soft-threshold for deblocking artifact and an optimal intersection of confidence intervals (OICI) method in deblocking artifact estimation. The soft-threshold values are adaptable to different thresholds of flat area, texture area, and blocking artifact. The OICI is a reconstruction technique of estimated deblocking artifact which improves acceptable quality level of estimated deblocking artifact and reduces execution time of deblocking artifact estimation compared to the other methods. Our adaptive OICI method outperforms other adaptive deblocking artifact methods. Our estimated deblocking artifact algorithms have up to 98% of MSE improvement, up to 89% of RMSE improvement, and up to 99% of MAE improvement. We also got up to 77.98% reduction of computational time of deblocking artifact estimations, compared to other methods. We have estimated shift and add algorithms by using Euler++(E++) and Runge-Kutta of order 4++ (RK4++) algorithms which iterate one step an ordinary differential equation integration method. Experimental results showed that our E++ and RK4++ algorithms could reduce computational time in terms of shift and add, and RK4++ algorithm is superior to E++ algorithm.

Distributed Reflective Denial of Services (DRDoS) attacks have gained huge popularity and become a major factor in a number of massive cyber-attacks. Usually, the attackers launch this kind of attack with small volume of requests to generate a large volume of attack traffic aiming at the victim by using IP spoofing from legitimate hosts. There have been several approaches, such as static threshold based approach and confirmation-based approach, focusing on DRDoS attack detection at victim's side. However, these approaches have significant disadvantages: (1) they are only passive defences after the attack and (2) it is hard to trace back the attackers. To address this problem, considerable attention has been paid to the study of detecting DRDoS attack at source side. Because the existing proposals following this direction are supposed to be ineffective to deal with small volume of attack traffic, there is still a room for improvement. In this paper, we propose a novel method to detect DRDoS attack request traffic on SDN(Software Defined Network)-enabled gateways in the source side of attack traffic. Our method adjusts the sampling rate and provides a traffic-aware adaptive threshold along with the margin based on analysing observed traffic behind gateways. Experimental results show that the proposed method is a promising solution to detect DRDoS attack request in the source side.

This paper proposes an image denoising method using singular value decomposition (SVD) with block-rotation-based operations in wavelet domain. First, we decompose a noisy image to some sub-blocks, and use the single-level discrete 2-D wavelet transform to decompose each sub-block into the low-frequency image part and the high-frequency parts. Then, we use SVD and rotation-based SVD with the rank-1 approximation to filter the noise of the different high-frequency parts, and get the denoised sub-blocks. Finally, we reconstruct the sub-block from the low-frequency part and the filtered the high-frequency parts by the inverse wavelet transform, and reorganize each denoised sub-blocks to obtain the final denoised image. Experiments show the effectiveness of this method, compared with relevant methods.

We report the characterization of hysteresis in SOI-based super-steep subthreshold slope FETs, which are conventional floating body and body-tied, and newly proposed PN-body-tied structures. We found that the hysteresis widths of the PN-body-tied structures are smaller than that of the conventional floating body and body-tied structures; this means that they are feasible for switching devices. Detailed characterizations of the hysteresis widths of each device are also reported in the study, such as dependency on the gate length and the impurity concentration.

In this paper, we propose the novel low voltage CMOS current mode reference circuit. It reduces the minimum supply voltage by consisting the subthreshold two stage operational amplifier (OPAMP) which is regarded as the combination of the proportional to absolute temperature (PTAT) and the complementary to absolute temperature (CTAT) current generators. It makes possible to implement without extra OPAMP. This proposed circuit has been designed and evaluated by SPICE simulation using TSMC 65nm CMOS process with 3.3V (2.5V over-drive) transistor option. From simulation results, the line sensitivity is as good as 0.196%/V under the condition that the range of supply voltage (VDD) is wide as 0.6V to 3.0V. The temperature coefficient is 71ppm/ under the condition that the temperature range is from -40 to 125 and VDD=0.6V. The power supply rejection ratio (PSRR) is -47.7dB when VDD=0.6V and the noise frequency is 100Hz. According to comparing the proposed circuit with prior current mode circuits, we could confirm the performance of the proposed circuit is better than that of prior circuits.

By using Password-based Authenticated Key Exchange (PAKE), a server can authenticate a user who has only the same password shared with the server in advance and establish a session key with the user simultaneously. However, in the real applications, we may have a situation where a user needs to share a session key with server A, but the authentication needs to be done by a different server B that shares the password with the user. Further, to achieve higher security on the server side, it may be required to make PAKE tolerant of a server breach by having multiple authentication servers. To deal with such a situation, Abdalla et al. proposed a variant of PAKE called Gateway Threshold PAKE (GTPAKE) where a gateway corresponds to the aforementioned server A being an on-line service provider and also a potential adversary that may try to guess the passwords. However, the schemes of Abdalla et al. turned out to be vulnerable to Undetectable On-line Dictionary Attack (UDonDA). In this paper, we propose the first GTPAKE provably secure against UDonDA, and in the security analysis, we prove that our GTPAKE is secure even if an adversary breaks into parts of multiple authentication servers.