The UAV mobile crowd sensing problem is a new research area due to the flexibility and low-cost advantage of UAVs. Current research rarely considers the task assignment and path planning problem simultaneously. In thi...
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Nowadays the famous search engine companies are all providing the keyword web search capabilities. No one provides the high accurate & efficient user-requirements-oriented information Services. The task-focused ma...
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Due to the strong attacking ability, fast speed, simple implementation and other characteristics, differential fault analysis has become an important method to evaluate the security of cryptosystem in the Internet of ...
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Due to the strong attacking ability, fast speed, simple implementation and other characteristics, differential fault analysis has become an important method to evaluate the security of cryptosystem in the Internet of Things. As one of the AES finalists, the Serpent is a 128-bit Substitution-Permutation Network(SPN) cryptosystem. It has 32 rounds with the variable key length between 0 and 256 bits, which is flexible to provide security in the Internet of Things. On the basis of the byte-oriented model and the differential analysis, we propose an effective differential fault attack on the Serpent cryptosystem. Mathematical analysis and simulating experiment show that the attack could recover its secret key by introducing 48 faulty ciphertexts. The result in this study describes that the Serpent is vulnerable to differential fault analysis in detail. It will be beneficial to the analysis of the same type of other iterated cryptosystems.
A UV-activated room temperature chemiresistive gas sensor based on ZnO nanocrystals film was fabricated. Its gas sensing properties under various conditions were also investigated in detail. The results shed new insig...
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A UV-activated room temperature chemiresistive gas sensor based on ZnO nanocrystals film was fabricated. Its gas sensing properties under various conditions were also investigated in detail. The results shed new insight into the adsorption behaviors of gas molecules on the surface of ZnO nanocrystals under UV irradiation. The chemisorbed oxygen species(O^-2(ads)(hv)) induced by UV light govern the adsorption and desorption ways of other gas molecules on the surface of ZnO nanocrystals, which is dependent on the electron affinity of gas molecules. Gas molecules with higher electron affinity than oxygen molecules can be adsorbed on the surface by the competitive adsorption way, extracting electrons from the surface. Gas molecules with lower electron affinity than oxygen molecules are attracted by the adsorbed O^-2(ads)(hv)layer, releasing electrons to the surface. These processes can influence the gas sensing properties of the sensor. Our findings will pave the way for the fundamental understanding and design of UV-activated gas sensor in the future.
Learning analytics is a rapidly evolving research discipline that uses theinsights generated from data analysis to support learners as well as optimize boththe learning process and environment. This paper studied stud...
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Learning analytics is a rapidly evolving research discipline that uses theinsights generated from data analysis to support learners as well as optimize boththe learning process and environment. This paper studied students’ engagementlevel of the Learning Management System (LMS) via a learning analytics tool,student’s approach in managing their studies and possible learning analytic methods to analyze student data. Moreover, extensive systematic literature review(SLR) was employed for the selection, sorting and exclusion of articles fromdiverse renowned sources. The findings show that most of the engagement inLMS are driven by educators. Additionally, we have discussed the factors inLMS, causes of low engagement and ways of increasing engagement factorsvia the Learning Analytics approach. Nevertheless, apart from recognizing theLearning Analytics approach as being a successful method and technique for analyzing the LMS data, this research further highlighted the possibility of mergingthe learning analytics technique with the LMS engagement in every institution asbeing a direction for future research.
Geophysical problems often involve Lagrangian particles that follow surrounding flows and record information about the system, such as the pressure and temperature path recorded in metamorphic rocks. These Lagrangian ...
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Geophysical problems often involve Lagrangian particles that follow surrounding flows and record information about the system, such as the pressure and temperature path recorded in metamorphic rocks. These Lagrangian particles can be useful for constraining unknown parameters, such as their sources and the thermal and flow processes of the surrounding fluid. To use information about Lagrangian particles to constrain unknown parameters about the surrounding fluid in an inverse manner, we have developed a 4D-Var (four-dimensional variational) data assimilation for thermal convection in a particle-grid coupled system. Here we consider particles advected in a thermally convecting, highly viscous fluid that mimics geochemical tracers in the Earth's mantle, and estimate time series of thermal and velocity fields only from the particle records, focusing on their high traceability in the laminar flow. We present preliminary 4D-Var results using a sufficient amount of synthetic particle position and velocity data. The 4D-Var run achieves a 60-Myr time reversal of thermal convection at a horizontal wavelength of 6,000 km, without using any temperature data. For complex convection patterns, the cost function tends not to decrease well, likely indicating that the method is successful when the time reversal is much smaller than the mixing time scale, over which information about the initial particle arrangement is lost. Our framework has the potential to constrain thermal, flow, and mixing processes not only in the Earth's mantle but also in any other laminar flow containing Lagrangian particles that record useful information. We have developed a new inversion scheme for a grid-particle system for retrospective estimation of thermal and flow processes The method has successfully reconstructed thermal convection from synthetic particle positions and velocities without using temperature data Our method highlights the advantages of particle traceability in laminar flow in the conte
Energy conservation and network performance are critical issues in wireless sensor networks. The authors present a novel efficient communication topology control protocol, called quorum-based load-sharing control prot...
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In a recent paper [2002 Phys. Rev. Lett. 88 174102], Bandt and Pompe propose permutation entropy (PE) as a natural complexity measure for arbitrary time series which may be stationary or nonstationary,deterministic ...
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In a recent paper [2002 Phys. Rev. Lett. 88 174102], Bandt and Pompe propose permutation entropy (PE) as a natural complexity measure for arbitrary time series which may be stationary or nonstationary,deterministic or *** method is based on a comparison of neighbouring *** paper further develops PE,and proposes the concept of fine-grained PE (FGPE) defined by the order pattern and magnitude of the difference between neighbouring values. This measure excludes the case where vectors with a distinct appearance are mistakenly mapped onto the same permutation type,and consequently FGPE becomes more sensitive to the dynamical change of time series than does PE,according to our simulation and experimental results.
Epitaxy is the cornerstone of semiconductor technology, enabling the fabrication of single-crystal *** advancements in van der Waals(vd W) epitaxy have opened new avenues for producing wafer-scale single-crystal 2D ...
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Epitaxy is the cornerstone of semiconductor technology, enabling the fabrication of single-crystal *** advancements in van der Waals(vd W) epitaxy have opened new avenues for producing wafer-scale single-crystal 2D atomic crystals. However, when it comes to molecular crystals, the overall weak vd W force means that it is a significant challenge for small molecules to form a well-ordered structure during *** we demonstrate that the vd W epitaxy of Sb2O3molecular crystal, where the whole growth process is governed by vd W interactions, can be precisely controlled. The nucleation is deterministically modulated by epilayer–substrate interactions and unidirectional nuclei are realized through designing the lattice and symmetry matching between epilayer and substrate. Moreover, the growth and coalescence of nuclei as well as the layer-by-layer growth mode are kinetically realized via tackling the Schwoebel-Ehrlich barrier. Such precise control of vd W epitaxy enables the growth of single-crystal Sb2O3molecular film with desirable thickness. Using the ultrathin highly oriented Sb2O3film as a gate dielectric, we fabricated MoS2-based field-effect transistors that exhibit superior device performance. The results substantiate the viability of precisely managing molecule alignment in vd W epitaxy, paving the way for large-scale synthesis of single-crystal 2D molecular crystals.
Maximum likelihood (ML) and minimum relative-entropy (MRE) (minimum cross-entropy) classification of samples from an unknown probability density when the hypotheses comprise an exponential family are considered. It is...
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Maximum likelihood (ML) and minimum relative-entropy (MRE) (minimum cross-entropy) classification of samples from an unknown probability density when the hypotheses comprise an exponential family are considered. It is shown that ML and MRE lead to the same classification nde, and the result is illustrated in terms of a method for estimating covariance matrices recently developed by Burg, Luenberger, and Wenger, MRE classification applies to the general case in which it cannot be assumed that the samples were generated by one of the hypothesis densities. The common use of ML in this case is technically incorrect, but the equivalence of MRE and ML provides a theoretical justification.
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