We investigate the device performance of heterojunction graphene nanoribbons tunneling field-effect transistors as a function of the doping concentrations based on the non-equilibrium Green's function. We observe ...
We investigate the device performance of heterojunction graphene nanoribbons tunneling field-effect transistors as a function of the doping concentrations based on the non-equilibrium Green's function. We observe that variation in source doping changes the OFF-non-equilibrium Green's functionstate currents (I OFF ), the ON-state currents (I ON ) and the subthreshold slope (SS) significantly while variation in drain doping changes mainly the I OFF . Additionally, low SS and large I ON /I OFF ratio can be achieved by applying proper asymmetric source-drain doping.
Some wafer fabrication processes are repeated processes, e.g. atomic layer deposition (ALD) process. For such processes, the wafers need to visit some processing modules for a number of times, which complicates the cy...
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In this work exciton spin state degeneracy of InAs quantum dots (QDs) have been shown to be lifted by applying a magnetic field. A strong coupling between a QD exciton spin state and a photonic crystal cavity was demo...
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In this work exciton spin state degeneracy of InAs quantum dots (QDs) have been shown to be lifted by applying a magnetic field. A strong coupling between a QD exciton spin state and a photonic crystal cavity was demonstrated as well as two QDs and the cavity. Applying a magnetic field to the QD-cavity system not only serves as a method for tuning QD emission frequency, but also opens the possibility of exploring the interactions between a cavity and multi-level quantum emitter systems.
It is well known that the ground state energy of many-particle Hamiltonians involving only 2-body interactions can be obtained using constrained optimizations over density matrices which arise from reducing an N-parti...
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It is well known that the ground state energy of many-particle Hamiltonians involving only 2-body interactions can be obtained using constrained optimizations over density matrices which arise from reducing an N-particle state. While determining which 2-particle density matrices are “N-representable” is a computationally hard problem, all known extreme N-representable 2-particle reduced density matrices arise from a unique N-particle preimage, satisfying a conjecture established in 1972. We present explicit counterexamples to this conjecture through giving Hamiltonians with 2-body interactions which have degenerate ground states that cannot be distinguished by any 2-body operator. We relate the existence of such counterexamples to quantum error correction codes and topologically ordered spin systems.
An appropriate and understandable data visualization is a key feature for the usability of a data mining system. The proper visualization methods for data exploration increase the whole acceptability of the system and...
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Finding a global optimum of an unknown system has attracted a great deal of interest in many engineering problems. In this settings, meta-heuristics are very common as efficient approaches for solving complex real-wor...
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Finding a global optimum of an unknown system has attracted a great deal of interest in many engineering problems. In this settings, meta-heuristics are very common as efficient approaches for solving complex real-world problems in global continuous optimization problems (GCOPs) as they can approximate solutions without considering mathematical constraints such as differentiability. In this study, we propose a method based on tabu search (TS) and Nelder-Mead (NM) search strategy in application to GCOPs. To increase the robustness of the proposed method, we add a new phase, referred to as partitioning phase, before diversification which is realized by the TS. The TS is improved and then followed by the NM search strategy. The partitioning phase aims at distributing initial random solutions in the search space. By doing this, we increase the robustness of the method. The TS has an interesting ability of covering a wide solution space by promoting the search far away from the current solution and consecutively decreasing the possibility of trapping in local minima. The neighbour search-strategy of the TS is improved to accelerate the speed of finding the near optimum solution. Instead of just generating random neighbours around the current solution, we generate some neighbours in the direction of the previous move as well as some neighbours in the previous best crown. When certain criteria are reached for the diversification of the search space, the NM search strategy is carried out with the focus on the intensification of the solution found in the diversification phase. We assess the performance of the algorithm for a range of standard test functions available in the literature and compare the obtained results with those available in the literature. There are two main advantages of the proposed method;first, it can apply to any GCOP without considering any constraints and secondly, it shows better performance (in terms of function evaluation, success rate, and average
Cache replacement policy plays an important role in guaranteeing the availability of cache blocks, reducing miss rates, and improving applications' overall performance. However, recent research efforts on improvin...
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Deadlock control is an important research issue in automated manufacturing systems that have a high degree of resource sharing and concurrency. Since minimal siphons are closely tied with deadlocks in Petri net models...
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Automated detection and diagnosis of small lesions in breast MRI represents a challenge for the traditional computer-aided diagnosis (CAD) systems. The goal of the present research was to compare and determine the opt...
Automated detection and diagnosis of small lesions in breast MRI represents a challenge for the traditional computer-aided diagnosis (CAD) systems. The goal of the present research was to compare and determine the optimal feature sets describing the morphology and the enhancement kinetic features for a set of small lesions and to determine their diagnostic performance. For each of the small lesions, we extracted morphological and dynamical features describing both global and local shape, and kinetics behavior. In this paper, we compare the performance of each extracted feature set for the differential diagnosis of enhancing lesions in breast MRI. Based on several simulation results, we determined the optimal feature number and tested different classification techniques. The results suggest that the computerized analysis system based on spatiotemporal features has the potential to increase the diagnostic accuracy of MRI mammography for small lesions and can be used as a basis for computer-aided diagnosis of breast cancer with MR mammography.
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