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Magnetic resonance imaging (MRI) brain tumor segmentation is a crucial task for clinical treatment. However, it is challenging owing to variations in type, size, and location of tumors. In addition, anatomical variation in individuals, intensity non‐uniformity, and noises adversely affect brain tumor segmentation. To address these challenges, an automatic region‐based brain tumor segmentation approach is presented in this paper which combines fuzzy shape prior term and deep learning. We define a new energy function in which an Adaptively Regularized Kernel‐Based Fuzzy C‐Means (ARKFCM) Clustering algorithm is utilized for inferring the shape of the tumor to be embedded into the level set method. In this way, some shortcomings of traditional level set methods such as contour leakage and shrinkage have been eliminated. Moreover, a fully automated method is achieved by using U‐Net to obtain the initial contour, reducing sensitivity to initial contour selection. The proposed method is validated on the BraTS 2017 benchmark dataset for brain tumor segmentation. Average values of Dice, Jaccard, Sensitivity and specificity are 0.93 ± 0.03, 0.86 ± 0.06, 0.95 ± 0.04, and 0.99 ± 0.003, respectively. Experimental results indicate that the proposed method outperforms the other state‐of‐the‐art methods in brain tumor segmentation. [ABSTRACT FROM AUTHOR]

The Social Spider Algorithm (SSA) was introduced based on the information-sharing foraging strategy of spiders to solve the continuous optimization problems. SSA was shown to have better performance than the other state-of-the-art meta-heuristic algorithms in terms of best-achieved fitness values, scalability, reliability, and convergence speed. By preserving all strengths and outstanding performance of SSA, we propose a novel algorithm named Discrete Social Spider Algorithm (DSSA), for solving discrete optimization problems by making some modifications to the calculation of distance function, construction of follow position, the movement method, and the fitness function of the original SSA. DSSA is employed to solve the symmetric and asymmetric traveling salesman problems. To prove the effectiveness of DSSA, TSPLIB benchmarks are used, and the results have been compared to the results obtained by six different optimization methods: discrete bat algorithm (IBA), genetic algorithm (GA), an island-based distributed genetic algorithm (IDGA), evolutionary simulated annealing (ESA), discrete imperialist competitive algorithm (DICA) and a discrete firefly algorithm (DFA). The simulation results demonstrate that DSSA outperforms the other techniques. The experimental results show that our method is better than other evolutionary algorithms for solving the TSP problems. DSSA can also be used for any other discrete optimization problem, such as routing problems. [ABSTRACT FROM AUTHOR]

This paper presents and evaluates a compact Signed-Digit (SD) encoding algorithm which is an efficient class of the large integer encoding algorithms. The compact SD algorithm results in a series of digits which show the number of consecutive zero bits. Using the proof-of-concept code, we proved that the optimal range for the limit on the number of consecutive zero bits in each digit and average Hamming weight ofn-bit integers in the compact SD representation aretoandn/3, respectively. In the modular multiplication algorithm, the compact SD is applied to the multiplier. The compact SD modular multiplication processes consecutive zero bits and followed nonzero digits in one clock cycle. Implementation results on Xilinx Virtex 5 FPGA show that the compact SD modular multiplication outperforms previous modified modular multiplication algorithms in terms of throughput and area × time complexity. [ABSTRACT FROM AUTHOR]

This paper presents and evaluates an advance hybrid key management architecture for supervisory control and data acquisition (SCADA) networks (HSKMA), which supports all three types of communications: unicast, multicast, and broadcast. The HSKMA is based on the elliptic curve cryptography and symmetric cryptography. While the elliptic curve cryptography is used for communication between master station unit (MSU) and sub-MSUs, the symmetric cryptographic algorithm is used for communication between sub-MSUs and slave stations that have limited computational resources. Our analysis shows that the HSKMA has the following distinctive advantages: 1) it supports the security requirement such as availability, forward security, and backward security, 2) it supports the required speed in the MODBUS implementation, and 3) it is suitable for the environments that have limited computational resources. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a graphene nanoribbon FET (GNRFET) with locally embedded Stone–Wales (SW) defects near its drain contact. The simulation procedure is preformed via the self-consistent solution of the full 3-D Schrödinger and Poisson equations. Localized states induced by the SW defects are able to reduce ambipolar conduction and provide higher ON–OFF ratio and attenuated kink effect. Causing outgoing carriers decelerated in the channel, the use of such defected region in the GNRFET yields less vulnerability to hot-carrier degradation than its conventional counterpart. Our proposed structure also enhances the device transconductance, making it more appealing in high-frequency applications. [ABSTRACT FROM AUTHOR]

Modular exponentiation with a large modulus and exponent is a fundamental operation in many public-key cryptosystems. This operation is usually accomplished by repeating modular multiplications. Montgomery modular multiplication has been widely used to relax the quotient determination. The carry–save adder has been employed to reduce the critical path. This paper presents and evaluates a new and efficient Montgomery modular multiplication architecture based on a new digit serial computation. The proposed architecture relaxes the high-radix partial multiplication to a binary multiplication. It also performs several multiplications of consecutive zero bits in one clock cycle instead of several clock cycles. Moreover, the right-to-left and left-to-right modular exponentiation architectures have been modified to use the proposed modular multiplication architecture as its structural unit. We provide the implementation results on a Xilinx Virtex 5 FPGA demonstrating that the total computation time and throughput rate of the proposed architectures outperform most results so far in the literatures. [ABSTRACT FROM AUTHOR]

Modular exponentiation is an important operation in public-key cryptography. The Common-Multiplicand-Multiplication (CMM) modular exponentiation is an efficient exponentiation algorithm. This paper presents a novel method for speeding up the CMM modular exponentiation algorithm based on a Modified Montgomery Modular Multiplication (M4) algorithm. The M4 algorithm uses a new multi bit scan-multi bit shift technique by employing a modified encoding algorithm. In the M4 algorithm, three operations (the zero chain multiplication, the required additions and the nonzero digit multiplication) are relaxed to a multi bit shift and one binary addition in only one clock cycle. Our computational complexity analysis shows that the average number of required multiplication steps (clock cycles) is considerably reduced in comparison with other CMM modular exponentiation algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we present theoretical definitions and physical backgrounds of turn-on voltage, saturation voltage and transition slope in graphene-based variable-barrier transistors (barristors). We show that they are three main characteristics parameters of the device and are of the key factors in determining whether barristor is applicable for the future nanoelectronics. Furthermore, because of the importance of physical modeling of semiconductor devices, we address this issue and develop physical expressions, in closed form, for these characteristics. We also investigate the conformity of the functional dependence of our models and their results variations regarding to the device parameters with the reports of the previous works. Finally, we physically discuss how the variation of the device parameters, such as bias condition and doping density, can influence the aforesaid main characteristics of barristor. [ABSTRACT FROM PUBLISHER]

A novel carbon nanotube field-effect transistor with stepwise doping profile channel (SDC-CNTFET) is introduced for short-channel effects (SCEs) improvement. In SDC-CNTFET, the channel is divided into five sections of equal length. Impurity concentration was reduced from 0.8 nm-1 to zero from the source side to the drain side of the channel, with stepwise profile. The devices have been simulated by the self-consistent solution of two-dimensional (2D) Poisson-Schrödinger equations, within the nonequilibrium Green's function (NEGF) formalism. We demonstrate that the proposed structure for CNTFETs shows considerable improvement in device performance focusing on leakage current and ON-OFF current ratio. In addition, the investigation of SCEs for the proposed structure shows the improved drain-induced barrier lowering (DIBL) and subthreshold swing (SS). Moreover, we will prove that the proposed structure has acceptable performance at different values of channel impurity concentration in terms of delay and power-delay product (PDP). All these investigations introduce SDC-CNTFET as a more reliable device structure in short-channel regime. [ABSTRACT FROM AUTHOR]