A cryptosystem with noncommutative platform groups

Neural Computing and Applications - This paper presents a new public key cryptosystem that uses noncommutative groups as platform group. The underlying hard problem of the proposed cryptosystem is...     

Personality Detection Using Context Based Emotions in Cognitive Agents

Detection of personality using emotions is a research domain in artificial intelligence. At present, some agents can keep the human’s profile for interaction and adapts themselves according to their preferences. However, the effective method for interaction is to detect the person’s personality by understanding the emotions and context of the subject. The idea behind adding personality in cognitive agents begins an attempt to maximize adaptability on the basis of behavior. In our daily life, humans socially interact with each other by analyzing the emotions and context of interaction from audio or visual input. This paper presents a conceptual personality model in cognitive agents that can determine personality and behavior based on some text input, using the context subjectivity of the given data and emotions obtained from a particular situation/context. The proposed work consists of Jumbo Chatbot, which can chat with humans. In this social interaction, the chatbot predicts human personality by understanding the emotions and context of interactive humans. Currently, the Jumbo chatbot is using the BFI technique to interact with a human. The accuracy of proposed work varies and improve through getting more experiences of interaction.     

Diamond-graphite nanorods produced by microwave plasma chemical vapor deposition

One dimensional C–C nanostructure, diamond–graphite nanorods, was synthesized by the argon rich microwave plasma chemical vapor deposition method. The nanostructures were characterized by scanning electron microscopy and transmission electron microscopy techniques. The diamond nanorods (DNRs) consist of single-crystalline diamond cores of 2–5 nm in diameter and several tens of nanometer in length. The DNRs are encapsulated in a graphitic shell of variable thickness. Raman and X-ray diffraction spectra also indicated the coexistence of diamond and graphite phases in the film. The addition of nitrogen is considered to be helpful for the highly efficient formation of graphite shell. The high content of methane in the gas mixture in the presence of argon rich environment is suggested to be responsible for the one dimensional growth.     

Deep introspective SLAM: deep reinforcement learning based approach to avoid tracking failure in visual SLAM

Autonomous Robots - Reliable and consistent tracking is essential to realize the dream of power-on-and-go autonomy in mobile robots. Our investigation with state-of-the-art visual navigation and...     

Mechanical properties of epoxy composites with low content of diamond particles

Diamond‐epoxy composites reinforced with low content of submicron diamond powder 0.1, 0.4, 0.7, and 1.0 wt % were synthesized. As received diamond powder was acid treated to purify and functionalize diamond particles. Fourier Transform Infrared Spectroscopy was utilized to study the moieties attached to the diamond particles. The trace elemental analysis of impurities in diamond powder before and after acid treatment was performed using ion beam techniques. The mechanical properties of the epoxy matrix were enhanced with the addition of purified and functionalized diamond powder. The Dynamical mechanical analysis results revealed that storage modulus of the prepared composites has been increased by ～ 100% with diamond loading of 0.7 wt %. The Vickers's hardness of the diamond‐epoxy composite was ～ 39% higher than that of pure epoxy for the loading of 1.0 wt % diamond powder. Mechanisms responsible for the enhancement of the mechanical properties are discussed. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013