Accurate mobile malware detection and classification in the cloud.

As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis.

Quantitative measurement of phase variation amplitude of ultrasonic diffraction grating based on diffraction spectral analysis.

A new method based on diffraction spectral analysis is proposed for the quantitative measurement of the phase variation amplitude of an ultrasonic diffraction grating. For a traveling wave, the phase variation amplitude of the grating depends on the intensity of the zeroth- and first-order diffraction waves. By contrast, for a standing wave, this amplitude depends on the intensity of the zeroth-, first-, and second-order diffraction waves.

Weighted target interval stochastic control methods with global optimization and their applications in individualizing therapy.

Several improvements on the target interval stochastic control (TISC) method are addressed for individualizing therapy. In particular, a global optimization control strategy is implemented to obtain the optimal dosage regimen, and weighting functions are introduced to balance the drug efficacy and the risk of toxicity. Since general guidance is often lacking in the determination of a weighting function, we introduce a systematic approach, i.

Sampling schedule design towards optimal drug monitoring for individualizing therapy.

We study the individualization of therapy by simultaneously taking into account the design of sampling schedule and optimal therapeutic drug monitoring. The sampling schedule design in this work is to determine the number of samples, the sampling times, the switching time from the loading to the maintenance period, and the drug dosages. A closed-loop control policy is employed to determine the sampling schedule, and an advanced stochastic global optimization algorithm, which integrates the stochastic approximation and simulated annealing techniques, is implemented to search the optimal sampling schedule.

Weighted two-band target entropy minimization for the reconstruction of pure component mass spectra: simulation studies and the application to real systems.

A method is proposed, on the basis of a recently developed algorithm--Band Target Entropy Minimization (BTEM)--to reconstruct mass spectra of pure components from mixture spectra. This method is particular useful in dealing with spectral data with discrete features (like mass spectra). Compared to the original BTEM, which has been applied to differentiable spectroscopies such as Fourier-transfer infrared spectroscopy (FTIR), ultraviolet (UV), Raman, and nuclear magnetic resonance (NMR), the latest modifications were obtained through: (1) Reformulating the objective function using the peak heights instead of their derivatives; (2) weighting the abstract vector VT to reduce the effect of noise; (3) using a two-peak targeting strategy (tBTEM) to deal with strongly overlapping peaks; and (4) using exhaustive search to locate all the component spectra.