Diamond turning of soft semiconductors to obtain nanometric mirror surfaces

Diamond cutting is a viable alternative to grinding and polishing in the fabrication of high-quality soft semiconductors. Investigation of indentation provides useful information for understanding the practical diamond cutting process of brittle materials. Cutting forces and temperatures were analysed using a Kistler dynamometer and an infrared technique. A zero rake angle cutting tool was found to be most efficient, partly because the effective rake is really a strong negative rake brought about by the peculiar configuration of very low feeds and depths of cut. This is explained by means of the comparison of the force distribution between conventional turning and ultraprecision machining. Atomic force microscopy and scanning electron microscopy were used to study the surfaces. Zinc sulfide gave subnanometric surfaces (0.88 m) and zinc selenide gave Ra values of 2.91 nm

A Survey of Adversarial Machine Learning in Cyber Warfare

The changing nature of warfare has seen a paradigm shift from the conventional to asymmetric, contactless warfare such as information and cyber warfare. Excessive dependence on information and communication technologies, cloud infrastructures, big data analytics, data-mining and automation in decision making poses grave threats to business and economy in adversarial environments. Adversarial machine learning is a fast growing area of research which studies the design of Machine Learning algorithms that are robust in adversarial environments. This paper presents a comprehensive survey of this emerging area and the various techniques of adversary modelling. We explore the threat models for Machine Learning systems and describe the various techniques to attack and defend them. We present privacy issues in these models and describe a cyber-warfare test-bed to test the effectiveness of the various attack-defence strategies and conclude with some open problems in this area of research.

Adoption of Integrated Pest Management Practices in Paddy and Cotton: A Case Study in Haryana and Punjab

The study has examined the adoption of IPM practices on cotton in Punjab and on paddy in Haryana and has assessed the impact of key socio-economic and institutional factors on IPM adoption. The Poisson count regression models have been used to analyze technology adoption. The awareness generation about technology through formal crop-specific IPM training provided by the farmers’ field schools has been found extremely effective in wider adoption of IPM in the study areas. Hence, investment in IPM education through these programmes will have long-term beneficial impact. Regarding effectiveness of extension services, the study has not shown (frequency of meeting extension personnel) any statistically significant impact on IPM adoption rates. Mixed evidence has been observed about the relationship between farm-size and adoption of IPM practices. In the case of paddy, a negative relationship has been observed, while the cotton has shown a positive relationship. The study has concluded that a higher gross value of crops does not appear to have a positive impact on IPM technology adoption in cotton.Crop Production/Industries,

Automated code extraction from packed android applications.

Software packing is a method employed by malicious applications to hide their original intent. Extracting the original intent of an application from its application bundle, whether to perform a security analysis on it, to search for security flaws(or bugs) or simply for educational purposes is a key requirement for the security community. With the fluidity provided by the Android app store coupled with a complete application-framework based environment for a malicious user to employ as an attack space, it is of great importance to examine Android applications and extract their intent. For basic applications, simple reverse engineering tools can be used to extract a semantic view of the application very close to the original source code of the application. However for applications, which have been deliberately packaged/packed in such a way that their original intent cannot be extracted by simply reverse-engineering them, we need a more intricate procedure to extract enough information to be able to reproduce the original intent of the application. These applications are packaged such that the actual code is hidden/encrypted and only during run-time is the actual code unpacked and executed. To unpack such applications, we present DroidUnpack, a tool based on dynamic program analysis, which is able to extract the original intent of the application, generically. DroidUnpack is designed by exploiting some fundamental features of the Android Runtime which cannot be mutated by a malicious user to unpack the application. We also attempts to alleviate tedious manual analysis required by a user to analyze different types of packed applications, by providing a generalized tool which is able to unpack android applications, regardless of the packing technique used