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Online criminals are focusing their attention more and more on ordinary computer users, seeking to take advantage of them through a variety of social and technological exploitation techniques. Some hackers are getting more skilled and determined. The ability to conceal their identities, keep their communications secret, keep their finances separate from their activities, and make use of private infrastructure are all areas in which cybercriminals have shown a high degree of proficiency. It is of the utmost importance to safeguard computers with surveillance systems that are able to identify complex varieties of malware. In this paper, we utilized machine learning algorithm to validate the samples from different datasets. The machine learning classifier is utilized to find the efficacy of the entire model in validating the class samples. The simulation is conducted in python to test the efficacy of the model against various class of datasets. The results show that the proposed method achieves higher degree of accuracy than the other models. [ABSTRACT FROM AUTHOR]

Cough is the major symptoms of Asthma patients. The intensity of cough can be used as a significant parameter for classifying the severity of Asthma. The purpose of this research is reliable assessment of cough events using sound processing tools to classify and predict severity of Asthma in patients. The system is trained to be selflearning and thus intelligent. In this research paper, parameters of the cough audio signal are analyzed. Finally, Nu Support Vector Classifier (NuSVC) is chosen as the predictor, due to its superb classification and feature selection ability. Finally, end result of severity of Asthma patients is predicted. However for the research purpose, the cough sound recording of Asthma training data set is created. The trained model is used for further classification and prediction of health severity. The model classified and predicted with 94% accuracy compared to previous work. [ABSTRACT FROM AUTHOR]

The research article address, the mechanical properties such as fatigue, impact strength and tribological properties of Austempered ductile iron (ADI) has been investigated. The samples of ADI iron were austenitized at 927°C for 2 hrs and later it was under austempering process for 2 hrs at a temperature range of 240°C to 400°C. Experiments under axial loading has been carried out on three different compositions (without Ni(X), 0.22 wt % Ni (X1), 0.34 wt. % Ni (X2). Fabricated test bars were converted in to as per ASTM standard samples for different tests. In order to study the influence of chunky nickel morphology studies on fatigue life and impact strength were carried out on a second set of specimens without any microstructural defect. Metallurgical analyses were performed on all the samples of heat treated samples (AF - Ausferrite, MB - Mixed bainite, M - Martensite, RA - Retained Austenite and N-Nodule) were found and compared. It was found that a mean content of 22% of chunky nickel in the microstructure (with respect to total Ni content) influence considerably the fatigue and impact strength properties of the cast iron. Moreover tribological properties of the specimens were also studied under dry sliding conditions at various sliding speed and load. The wear resistance and coefficient of friction were found to increase with increase in load and sliding speed. [ABSTRACT FROM AUTHOR]

Existing SQL Access Control Mechanisms are extremely limited. Attackers can access the sensitive information through escalating their privileges. Practical attacks against existing database are increasing nowadays by using database features such as triggers and integrity constraints. Moreover the theories behind access control mechanism lack adequate security policies and attackers capabilities. This paper addresses the three main privilege escalation attacks by using database features and its prevention methods. [ABSTRACT FROM AUTHOR]

Steering knuckle plays a vital role in automobile which connects the suspension, steering part, wheel hub and brake to the chassis. During its working, it subjected to various loading conditions. so, it requires high accuracy, quality, and durability. The main theme of this work is to access the fatigue performance of a steering knuckle. This can be performed by a detailed load analysis. Therefore, this study requires two steps. First part of the study involves modeling of the steering knuckle with the design parameters using the latest modeling software CATIA and the second part involves in fatigue analysis using ANSYS WORKBENCH. This provides us to improve the overall knowledge about the component. [ABSTRACT FROM AUTHOR]