A new code for parameter estimation in searches for gravitational waves from known pulsars

We describe the consistency testing of a new code for gravitational wave signal parameter estimation in known pulsar searches. The code uses an implementation of nested sampling to explore the likelihood volume. Using fake signals and simulated noise we compare this to a previous code that calculated the signal parameter posterior distributions on both a grid and using a crude Markov chain Monte Carlo (MCMC) method. We define a new parameterisation of two orientation angles of neutron stars used in the signal model (the initial phase and polarisation angle), which breaks a degeneracy between them and allows more efficient exploration of those parameters. Finally, we briefly describe potential areas for further study and the uses of this code in the future.Comment: Accepted for proceedings of Amaldi 9 meetin

Multi-dimensional modulation codes for fading channel

Some new codes are presented which have good performance on Rician fading channel with small decoding complexities. A new M-way partition chain is proposed for the L x MPSK (L less than or equal to M) signal set which maximizes the intra-set distance of each subset at each partition level. Based on this partition chain, a class of asymptotical optimum codes was found. For M = 4, these codes have both large symbol distances and product distances. Multi-level coding scheme allows to construct a code by hand such that the code meets some desired parameters, e.g., symbol distance, product distance, etc. In design of a multi-level code, all factors were considered which affect the performance and complexity of the code, such as, the decoding scheme, decoding complexity, and performance under the decoding scheme, e.g., if the multi-stage decoding scheme is used, the performance degradation due to the suboptimum decoding is taken into consideration. The performance for most of the presented codes was simulated on Rayleigh fading channel, and the results show that these codes have good performance with small decoding complexities

Toolpaths Programming in an Intelligent Step-NC Manufacturing Context

The current language for CNC programming is G-code which dates from the beginning of the eighties with the norm ISO 6983. With the new technologies, G-code becomes obsolete. It presents drawbacks that create a rupture in the numerical chain at the manufacturing step. A new standard, STEP-NC, aims to overtake these lacks. A STEP-NC file includes all the information for manufacturing, as geometry description of the entities, workplan, machining strategies, tools, etc. For rough pocket milling, the ISO norms propose different kind of classical strategies as bidirectional, parallel or spiral contour, etc. This paper describes a new way of toolpath programming by the repetition of a pattern all along a guide curve. It presents several advantages as building fastness and easiness. The integration of pattern strategies in STEP-NC standard is an other step for the development of these strategies but also for the enrichment of STEP-NC possibilities. A complete STEP-NC numerical chain was built, integrating these pattern strategies. The implementation of this approach of building pattern strategies was made by the development of tools for the complete manufacturing cycle, from the CAD file to the machined part. Several application cases were experimented on machine tool to validate this approach and the efficiency of the developped tools

PyECLOUD and build-up simulations at CERN

PyECLOUD is a newly developed code for the simulation of the electron cloud (EC) build-up in particle accelerators. Almost entirely written in Python, it is mostly based on the physical models already used in the ECLOUD code but, thanks to the implementation of new optimized algorithms, it exhibits a significantly improved performance in accuracy, speed, reliability and flexibility. Such new features of PyECLOUD have been already broadly exploited to study EC observations in the Large Hadron Collider (LHC) and its injector chain as well as for the extrapolation to high luminosity upgrade scenarios.Comment: 6 pages, contribution to the Joint INFN-CERN-EuCARD-AccNet Workshop on Electron-Cloud Effects: ECLOUD'12; 5-9 Jun 2012, La Biodola, Isola d'Elba, Ital

Internet of things security implementation using blockchain for wireless technology

Blockchain is a new security system which group many data into a block or so called classifying the data into a block. The block can have many types and each of them content data and security code. By using a decentralize mechanism, one security code protect all the data. That could happen at the server. In this research, a network of wireless sensor technology is proposed. The transmission of sensor data is via the Internet of things (Internet of Thing) technology. As many data transmitted, they have to classified and group them into a block. All the blocks are then send to the central processing unit, like a microcontroller. The block of data is then processed, identified and encrypted before send over the internet network. At the receiver, a GUI or Apps is developed to open and view the data. The Apps or GUI have an encrypted data or security code. User must key in the password before they can view the data. The password used by the end user at the Apps or GUI must be equivalent to the one encrypted at the sensor nodes. This is to satisfy the decentralized concept used in the Blockchain. To demonstrate the Blockchain technology applied to the wireless sensor network, a MATLAB Simulink function is used. The expected results should show a number of block of data in cryptography manner and chain together. The two set of data. Both have the data encrypted using hash. The black dots indicate the data has been encrypted whereas the white dot indicate indicates the data is not encrypted. The half white and half black indicates the data is in progress of encrypted. All this data should arrange in cryptography order and chain together in a vertical line. A protocol called block and chain group the data into the block and then chain then. The data appears in the blocks and send over the network. As seen in the simulation results, the yellow color represents the user data. This data has a default amplitude as 1 or 5. The data is chained and blocked to produce the Blockchain waveform Keywords: Blockchain, Internet of things, Wireless Sensor Network and MATLAB Simulin

Spatially Coupled LDPC Codes Constructed from Protographs

In this paper, we construct protograph-based spatially coupled low-density parity-check (SC-LDPC) codes by coupling together a series of L disjoint, or uncoupled, LDPC code Tanner graphs into a single coupled chain. By varying L, we obtain a flexible family of code ensembles with varying rates and frame lengths that can share the same encoding and decoding architecture for arbitrary L. We demonstrate that the resulting codes combine the best features of optimized irregular and regular codes in one design: capacity approaching iterative belief propagation (BP) decoding thresholds and linear growth of minimum distance with block length. In particular, we show that, for sufficiently large L, the BP thresholds on both the binary erasure channel (BEC) and the binary-input additive white Gaussian noise channel (AWGNC) saturate to a particular value significantly better than the BP decoding threshold and numerically indistinguishable from the optimal maximum a-posteriori (MAP) decoding threshold of the uncoupled LDPC code. When all variable nodes in the coupled chain have degree greater than two, asymptotically the error probability converges at least doubly exponentially with decoding iterations and we obtain sequences of asymptotically good LDPC codes with fast convergence rates and BP thresholds close to the Shannon limit. Further, the gap to capacity decreases as the density of the graph increases, opening up a new way to construct capacity achieving codes on memoryless binary-input symmetric-output (MBS) channels with low-complexity BP decoding.Comment: Submitted to the IEEE Transactions on Information Theor

Are Lock-Free Concurrent Algorithms Practically Wait-Free?

Lock-free concurrent algorithms guarantee that some concurrent operation will always make progress in a finite number of steps. Yet programmers prefer to treat concurrent code as if it were wait-free, guaranteeing that all operations always make progress. Unfortunately, designing wait-free algorithms is generally a very complex task, and the resulting algorithms are not always efficient. While obtaining efficient wait-free algorithms has been a long-time goal for the theory community, most non-blocking commercial code is only lock-free. This paper suggests a simple solution to this problem. We show that, for a large class of lock- free algorithms, under scheduling conditions which approximate those found in commercial hardware architectures, lock-free algorithms behave as if they are wait-free. In other words, programmers can keep on designing simple lock-free algorithms instead of complex wait-free ones, and in practice, they will get wait-free progress. Our main contribution is a new way of analyzing a general class of lock-free algorithms under a stochastic scheduler. Our analysis relates the individual performance of processes with the global performance of the system using Markov chain lifting between a complex per-process chain and a simpler system progress chain. We show that lock-free algorithms are not only wait-free with probability 1, but that in fact a general subset of lock-free algorithms can be closely bounded in terms of the average number of steps required until an operation completes. To the best of our knowledge, this is the first attempt to analyze progress conditions, typically stated in relation to a worst case adversary, in a stochastic model capturing their expected asymptotic behavior.Comment: 25 page