Know2Look: Commonsense Knowledge for Visual Search

With the rise in popularity of social media, images accompanied by contextual text form a huge section of the web. However, search and retrieval of documents are still largely dependent on solely textual cues. Although visual cues have started to gain focus, the imperfection in object/scene detection do not lead to significantly improved results. We hypothesize that the use of background commonsense knowledge on query terms can significantly aid in retrieval of documents with associated images. To this end we deploy three different modalities - text, visual cues, and commonsense knowledge pertaining to the query - as a recipe for efficient search and retrieval

Gradient Coding from Cyclic MDS Codes and Expander Graphs

Gradient coding is a technique for straggler mitigation in distributed learning. In this paper we design novel gradient codes using tools from classical coding theory, namely, cyclic MDS codes, which compare favorably with existing solutions, both in the applicable range of parameters and in the complexity of the involved algorithms. Second, we introduce an approximate variant of the gradient coding problem, in which we settle for approximate gradient computation instead of the exact one. This approach enables graceful degradation, i.e., the $\ell_2$ error of the approximate gradient is a decreasing function of the number of stragglers. Our main result is that normalized adjacency matrices of expander graphs yield excellent approximate gradient codes, which enable significantly less computation compared to exact gradient coding, and guarantee faster convergence than trivial solutions under standard assumptions. We experimentally test our approach on Amazon EC2, and show that the generalization error of approximate gradient coding is very close to the full gradient while requiring significantly less computation from the workers

Generic Black-Box End-to-End Attack Against State of the Art API Call Based Malware Classifiers

In this paper, we present a black-box attack against API call based machine learning malware classifiers, focusing on generating adversarial sequences combining API calls and static features (e.g., printable strings) that will be misclassified by the classifier without affecting the malware functionality. We show that this attack is effective against many classifiers due to the transferability principle between RNN variants, feed forward DNNs, and traditional machine learning classifiers such as SVM. We also implement GADGET, a software framework to convert any malware binary to a binary undetected by malware classifiers, using the proposed attack, without access to the malware source code.Comment: Accepted as a conference paper at RAID 201

Sequential nature of damage annealing and activation in implanted GaAs

Rapid thermal processing of implanted GaAs reveals a definitive sequence in the damage annealing and the electrical activation of ions. Removal of implantation-induced damage and restoration of GaAs crystallinity occurs first. Irrespective of implanted species, at this stage the GaAs is n-type and highly resistive with almost ideal values of electron mobility. Electrical activation is achieved next when, in a narrow anneal temperature window, the material becomes n- or p-type, or remains semi-insulating, commensurate to the chemical nature of the implanted ion. Such a two-step sequence in the electrical doping of GaAs by ion implantation may be unique of GaAs and other compound semiconductors

Acid-catalysed Hydrolysis of N-Phenyl-n-butyrohydroxamic Acid

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N-p-Chlorophenyl-2-thenohydroxamic Acid a Sensitive Reagent for Spectrophotometric Determination of Vanadium

The solvent extraction and spectrophotometric determination of vanadium(V) with N-p-chlorophenyl-2-thenohydroxamic acid (CPTHA) is described. The absorption spectrum of the vanadium(V)- CPTHA extracts in chloroform, from 4 mol/dm3 hydrochloric acid has its absorbance maximum at 530 nm; the reagent being colourless does not absorb at this wavelength. The coloured system obeys Beer\u27s law over a wide range. The molar absorptivity in terms of vanadium is 5500 dm3 mo1-1 cm-1 at 530 nm. The optimum acid range for quantitative extraction of the chelate is 3 to 9 mol/dm3 hydrochloric acid. The method is free from the interference of iron(III) and several other alloying elements which are often associated with vanadium. The method has been successfully used for determination of vanadium in BCS steels

Extractive Spectrophotometric Determination of Vanadium(V) with N-p-Chlorophenyl-2-naphthohydroxamic Acid and Investigation of Its Solid Complex

A simple, selective and sensitive method for the extractive spectrophotometric determination of vanadium(V) using N-p-chlorophenyl- 2-naphthohydroxamic acid (CP-2-NHA) is described. Vanadium( V) is quantitatively extracted from 3-8.4 M HCl as a violet complex with CP-2-NHA into chloroform. Beer\u27s law is applicable in the concentration range 34 and 224 fig of vanadium(V) per 25 ml of chloroform extract. The Sandell sensitivity of the system is 0.0089 μg/cm2 at 530 nm. The method has been satisfactorily employed for the determination of vanadium in steel. The solid complex, VOCI (C11H11N02Cl)2, was prepared and characterised by melting point, elemental analysis, visible and infrared spectra

Extractive Spectrophotometric Determination of Vanadium(V) with N-p-Chlorophenyl-2-naphthohydroxamic Acid and Investigation of Its Solid Complex

A simple, selective and sensitive method for the extractive spectrophotometric determination of vanadium(V) using N-p-chlorophenyl- 2-naphthohydroxamic acid (CP-2-NHA) is described. Vanadium( V) is quantitatively extracted from 3-8.4 M HCl as a violet complex with CP-2-NHA into chloroform. Beer\u27s law is applicable in the concentration range 34 and 224 fig of vanadium(V) per 25 ml of chloroform extract. The Sandell sensitivity of the system is 0.0089 μg/cm2 at 530 nm. The method has been satisfactorily employed for the determination of vanadium in steel. The solid complex, VOCI (C11H11N02Cl)2, was prepared and characterised by melting point, elemental analysis, visible and infrared spectra