Description:
In this paper, we propose a five-step approach to detect obfuscated malware by investigating the structural and behavioural features of API calls. We have developed a fully automated system to disassemble and extract API call features effectively from executables. Using n-gram statistical analysis of binary content, we are able to classify if an executable file is malicious or benign. Our experimental results with a dataset of 242 malwares and 72 benign files have shown a promising accuracy of 96.5% for the unigram model. We also provide a preliminary analysis by our approach using support vector machine (SVM) and by varying n-values from 1 to 5, we have analysed the performance that include accuracy, false positives and false negatives. By applying SVM, we propose to train the classifier and derive an optimum n-gram model for detecting both known and unknown malware efficiently.
Description:
The goal of this paper is to solve the post buckling phenomena of a large deformed elastic beam by a canonical dual mixed finite element method (CD-FEM). The total potential energy of this beam is a nonconvex functional which can be used to model both pre-and post-buckling problems. Different types of dual stress interpolations are used in order to verify the triality theory. Applications are illustrated with different boundary conditions and external loads by using semi-definite programming (SDP) algorithm. The results show that the global minimum of the total potential energy is stable buckled configuration, the local maximum solution leads to the unbuckled state, and both of these two solutions are numerically stable. While the local minimum is unstable buckled configuration and very sensitive to both stress interpolations and the external loads.
Description:
The goal of this paper is to solve the post buckling phenomena of a large deformed elastic beam by a canonical dual mixed finite element method (CD-FEM). The total potential energy of this beam is a nonconvex functional which can be used to model both pre-and post-buckling problems. Different types of dual stress interpolations are used in order to verify the triality theory. Applications are illustrated with different boundary conditions and external loads by using semi-definite programming (SDP) algorithm. The results show that the global minimum of the total potential energy is stable buckled configuration, the local maximum solution leads to the unbuckled state, and both of these two solutions are numerically stable. While the local minimum is unstable buckled configuration and very sensitive to both stress interpolations and the external loads.
Description:
Distributed video coding (DVC) aims at achieving low-complexity encoding in contrast to the existing video coding standards' high complexity encoding. According to the Wyner-Ziv theorem this can be achieved, under certain conditions, by independent encoding of the frames while resorting to joint decoding. However, the performance of a Wyner-Ziv coding scheme significantly depends on its knowledge about the spatio-temporal correlation of the video. Unfortunately, correlation statistics in a video widely varies both along the spatial and temporal directions. Therefore, we argue that in a feedback free transform domain DVC scheme the decoder will fail to recover all the transform coefficients with a nonzero probability. Thus, we suggest to integrate a recovery method with the decoder that aims at recovering the undecoded coefficients by exploiting the spatio-temporal correlation of the video. Besides, we extend and modify a recovery scheme, recently proposed in the context of images, for DVC so that it exploits both spatial and temporal correlations in recovering the undecoded coefficients. The essential idea of this scheme is to formulate the recovery problem as a linear optimization problem which can be solved efficiently using linear programming. Our simulation results demonstrated that the proposed scheme can significantly improve the PSNR and visual quality of the erroneous video frames produced by a DVC decoder.
Description:
Frequency Response Analysis (FRA) has become a reliable tool to detect mechanical deformation within power transformers. Many researchers have investigated the impact of various mechanical winding and core deformations on transformer FRA signature using either simulation analysis or practical testing to establish a standard code for FRA signature interpretation. None of them however, have given attention to the impact of power transformer insulating oil degradation on the transformer FRA signature. This paper investigates the effect of insulating mineral oil degradation on power transformer FRA signature. In this regard, the physical geometrical dimension of a single-phase transformer filled with insulating mineral oil is simulated using three dimensional finite element analysis to emulate the real transformer operation. Transformer FRA signature is measured and analysed with various health conditions of the insulating oil. Results show that, insulating oil degradation has a significant impact on the transformer FRA signature.
Description:
Digital image processing (DIP) technique has been growing rapidly as an essential tool to interpret various image features for many applications of science and engineering. Condition monitoring and diagnosis are considered the main areas that relay on DIP. Frequency response analysis (FRA) technique has become a popular and reliable diagnostic tool in detecting various winding deformations within power transformers. However, interpretation of FRA signatures still requires high expertise because of its reliance on graphical analysis. This paper presents a new technique for the interpretation of transformers FRA signatures. The proposed technique relies on incorporating both magnitude and angle of the FRA signature in one polar plot, which is manipulated to extract some unique features using DIP techniques. The proposed technique can assess in identifying and quantifying various winding deformation within power transformers. The proposed technique is easy to implement in any frequency response analyser.
Description:
The transmission, storage and analysis of electrocardiogram (ECG) data in real-time is essential for remote patient monitoring with wearable ECG devices and mobile ECG contexts. However, this remains a challenge to achieve within the processing power and the storage capacity of mobile devices. ECG reduction algorithms have an important role to play in reducing the processing requirements for mobile devices, however many existing ECG reduction and compression algorithms are computationally expensive to execute in mobile devices and have not been designed for real-time computation and incremental data arrival. In this paper, we describe a computationally naive, yet effective, algorithm that achieves high ECG reduction rates while maintaining key diagnostic features including PR, QRS, ST, QT and RR intervals. While reduction does not enable ECG waves to be reproduced, the ability to transmit key indicators (diagnostic features) using minimal computational resources, is particularly useful in mobile health contexts involving power constrained sensors and devices. Results of the proposed reduction algorithm indicate that the proposed algorithm outperforms other ECG reduction algorithms at a reduction/compression ratio (CR) of 5:1. If power or processing capacity is low, the algorithm can readily switch to a compression ratio of up to 10: 1 while still maintaining an error rate below 10%.
Description:
The transmission, storage and analysis of electrocardiogram (ECG) data in real-time is essential for remote patient monitoring with wearable ECG devices and mobile ECG contexts. However, this remains a challenge to achieve within the processing power and the storage capacity of mobile devices. ECG reduction algorithms have an important role to play in reducing the processing requirements for mobile devices, however many existing ECG reduction and compression algorithms are computationally expensive to execute in mobile devices and have not been designed for real-time computation and incremental data arrival. In this paper, we describe a computationally naive, yet effective, algorithm that achieves high ECG reduction rates while maintaining key diagnostic features including PR, QRS, ST, QT and RR intervals. While reduction does not enable ECG waves to be reproduced, the ability to transmit key indicators (diagnostic features) using minimal computational resources, is particularly useful in mobile health contexts involving power constrained sensors and devices. Results of the proposed reduction algorithm indicate that the proposed algorithm outperforms other ECG reduction algorithms at a reduction/compression ratio (CR) of 5:1. If power or processing capacity is low, the algorithm can readily switch to a compression ratio of up to 10: 1 while still maintaining an error rate below 10%.
Description:
This paper presents a proposed adaptive technique for nonholonomic wheeled mobile robot (NWMR) using the sliding-mode control (SMC) method. The proposed control system based on the backstepping kinematic controller and PI sliding mode dynamic control. With an adaptive fuzzy logic to adjust adaptation gain of SMC for trajectory tracking control of nonholonomic mobile robot. Parametric and nonparametric uncertainties of mobile robot can be solved by using the proposed control which take advantages of stability and robustness in sliding mode control. The adaptation gain of SMC is adjusted by using Mamdani type inference system with adaptive tuning algorithm, which improves the adaptability for uncertainness and eliminate input chattering of the SMC. The stability and convergence of the control system are proved using Lypanouve criteria, and the comparison of the proposed controller with the other controllers ensures the validity and superiority of my own controller
Description:
Power transformer is an important asset within the electrical power system network. Frequency Response Analysis (FRA) has been developing in popularity in recent years as a tool to detect mechanical deformation of power transformers winding. Since the FRA has been relying on graphical analysis, it calls for an expert person to analyze the results to detect the type of the fault and its location. There are no reliable guidelines for FRA signature in the event that a failure occurs in service and the impact can be far reaching. The concept of FRA has been successfully used as a diagnostic technique to detect the winding deformation, core and clamping structure for the power transformers. This paper investigated the impact of the forced and free winding buckling based on the variation of the electrical parameters to show how these faults vary the FRA signature.