Energy efficient mining on a quantum-enabled blockchain using light

We outline a quantum-enabled blockchain architecture based on a consortium of quantum servers. The network is hybridised, utilising digital systems for sharing and processing classical information combined with a fibre--optic infrastructure and quantum devices for transmitting and processing quantum information. We deliver an energy efficient interactive mining protocol enacted between clients and servers which uses quantum information encoded in light and removes the need for trust in network infrastructure. Instead, clients on the network need only trust the transparent network code, and that their devices adhere to the rules of quantum physics. To demonstrate the energy efficiency of the mining protocol, we elaborate upon the results of two previous experiments (one performed over 1km of optical fibre) as applied to this work. Finally, we address some key vulnerabilities, explore open questions, and observe forward--compatibility with the quantum internet and quantum computing technologies.Comment: 25 pages, 5 figure

Fingerprinting Smart Devices Through Embedded Acoustic Components

The widespread use of smart devices gives rise to both security and privacy concerns. Fingerprinting smart devices can assist in authenticating physical devices, but it can also jeopardize privacy by allowing remote identification without user awareness. We propose a novel fingerprinting approach that uses the microphones and speakers of smart phones to uniquely identify an individual device. During fabrication, subtle imperfections arise in device microphones and speakers which induce anomalies in produced and received sounds. We exploit this observation to fingerprint smart devices through playback and recording of audio samples. We use audio-metric tools to analyze and explore different acoustic features and analyze their ability to successfully fingerprint smart devices. Our experiments show that it is even possible to fingerprint devices that have the same vendor and model; we were able to accurately distinguish over 93% of all recorded audio clips from 15 different units of the same model. Our study identifies the prominent acoustic features capable of fingerprinting devices with high success rate and examines the effect of background noise and other variables on fingerprinting accuracy

Effect of a Polywell geometry on a CMOS Photodiode Array

The effect of a polywell geometry hybridized with a stacked gradient poly-homojunction architecture, on the response of a CMOs compatible photodiode array was simulated. Crosstalk and sensitivity improved compared to the polywell geometry alone, for both back and front illuminatio

Optimal load shedding for microgrids with unlimited DGs

Recent years, increasing trends on electrical supply demand, make us to search for the new alternative in supplying the electrical power. A study in micro grid system with embedded Distribution Generations (DGs) to the system is rapidly increasing. Micro grid system basically is design either operate in islanding mode or interconnect with the main grid system. In any condition, the system must have reliable power supply and operating at low transmission power loss. During the emergency state such as outages of power due to electrical or mechanical faults in the system, it is important for the system to shed any load in order to maintain the system stability and security. In order to reduce the transmission loss, it is very important to calculate best size of the DGs as well as to find the best positions in locating the DG itself.. Analytical Hierarchy Process (AHP) has been applied to find and calculate the load shedding priorities based on decision alternatives which have been made. The main objective of this project is to optimize the load shedding in the micro grid system with unlimited DG’s by applied optimization technique Gravitational Search Algorithm (GSA). The technique is used to optimize the placement and sizing of DGs, as well as to optimal the load shedding. Several load shedding schemes have been proposed and studied in this project such as load shedding with fixed priority index, without priority index and with dynamic priority index. The proposed technique was tested on the IEEE 69 Test Bus Distribution system

A major electronics upgrade for the H.E.S.S. Cherenkov telescopes 1-4

The High Energy Stereoscopic System (H.E.S.S.) is an array of imaging atmospheric Cherenkov telescopes (IACTs) located in the Khomas Highland in Namibia. It consists of four 12-m telescopes (CT1-4), which started operations in 2003, and a 28-m diameter one (CT5), which was brought online in 2012. It is the only IACT system featuring telescopes of different sizes, which provides sensitivity for gamma rays across a very wide energy range, from ~30 GeV up to ~100 TeV. Since the camera electronics of CT1-4 are much older than the one of CT5, an upgrade is being carried out; first deployment was in 2015, full operation is planned for 2016. The goals of this upgrade are threefold: reducing the dead time of the cameras, improving the overall performance of the array and reducing the system failure rate related to aging. Upon completion, the upgrade will assure the continuous operation of H.E.S.S. at its full sensitivity until and possibly beyond the advent of CTA. In the design of the new components, several CTA concepts and technologies were used and are thus being evaluated in the field: The upgraded read-out electronics is based on the NECTAR readout chips; the new camera front- and back-end control subsystems are based on an FPGA and an embedded ARM computer; the communication between subsystems is based on standard Ethernet technologies. These hardware solutions offer good performance, robustness and flexibility. The design of the new cameras is reported here.Comment: Proceedings of the 34th International Cosmic Ray Conference, 30 July- 6 August, 2015, The Hague, The Netherland

An optimized method towards formal verification of mixed signals using differential fed neural network over FFNN

Today, the semiconductor industries are rapidly usinganalog and mixed signals to achieve cost-effective solutions on a System on Chip (SoC) design.  The SoC device is a part of analog, digital and essential mixed-signal models/circuits merged on a semiconductor device, which provides the platform to build modern retail/consumer electronics appliances with smart technology. In order to evaluate the mixed signals, the conventional approaches are not effective with respect to its performance, time and manufacturing cost. Thus, the recent researches were much interested in formal verification technique as it provides the evidence of conscious algorithms in a system. The demand for formal verification in the SoC designs in the context of software and hardware platform is high because of its cost and accuracy. Thus, the paper introduces atechnique of formal verification for mixed signals by using training models of the Differential fed neural network (DFNN) over feedforward neural network (FFNN). The formal verification is performed through equivalence checking by using recently adopted designs as reference designs. The outcomes of the verification techniques suggests that DFNN based technique improves the training accuracy and optimizes the hardware resources like area, power than the FFNN based technique