MOCAST 2021

The 10th International Conference on Modern Circuit and System Technologies on Electronics and Communications (MOCAST 2021) will take place in Thessaloniki, Greece, from July 5th to July 7th, 2021. The MOCAST technical program includes all aspects of circuit and system technologies, from modeling to design, verification, implementation, and application. This Special Issue presents extended versions of top-ranking papers in the conference. The topics of MOCAST include:Analog/RF and mixed signal circuits;Digital circuits and systems design;Nonlinear circuits and systems;Device and circuit modeling;High-performance embedded systems;Systems and applications;Sensors and systems;Machine learning and AI applications;Communication; Network systems;Power management;Imagers, MEMS, medical, and displays;Radiation front ends (nuclear and space application);Education in circuits, systems, and communications

Microwave Indices from Active and Passive Sensors for Remote Sensing Applications

Past research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth’s surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices

Information Analysis for Steganography and Steganalysis in 3D Polygonal Meshes

Information hiding, which embeds a watermark/message over a cover signal, has recently found extensive applications in, for example, copyright protection, content authentication and covert communication. It has been widely considered as an appealing technology to complement conventional cryptographic processes in the field of multimedia security by embedding information into the signal being protected. Generally, information hiding can be classified into two categories: steganography and watermarking. While steganography attempts to embed as much information as possible into a cover signal, watermarking tries to emphasize the robustness of the embedded information at the expense of embedding capacity. In contrast to information hiding, steganalysis aims at detecting whether a given medium has hidden message in it, and, if possible, recover that hidden message. It can be used to measure the security performance of information hiding techniques, meaning a steganalysis resistant steganographic/watermarking method should be imperceptible not only to Human Vision Systems (HVS), but also to intelligent analysis. As yet, 3D information hiding and steganalysis has received relatively less attention compared to image information hiding, despite the proliferation of 3D computer graphics models which are fairly promising information carriers. This thesis focuses on this relatively neglected research area and has the following primary objectives: 1) to investigate the trade-off between embedding capacity and distortion by considering the correlation between spatial and normal/curvature noise in triangle meshes; 2) to design satisfactory 3D steganographic algorithms, taking into account this trade-off; 3) to design robust 3D watermarking algorithms; 4) to propose a steganalysis framework for detecting the existence of the hidden information in 3D models and introduce a universal 3D steganalytic method under this framework. %and demonstrate the performance of the proposed steganalysis by testing it against six well-known 3D steganographic/watermarking methods. The thesis is organized as follows. Chapter 1 describes in detail the background relating to information hiding and steganalysis, as well as the research problems this thesis will be studying. Chapter 2 conducts a survey on the previous information hiding techniques for digital images, 3D models and other medium and also on image steganalysis algorithms. Motivated by the observation that the knowledge of the spatial accuracy of the mesh vertices does not easily translate into information related to the accuracy of other visually important mesh attributes such as normals, Chapters 3 and 4 investigate the impact of modifying vertex coordinates of 3D triangle models on the mesh normals. Chapter 3 presents the results of an empirical investigation, whereas Chapter 4 presents the results of a theoretical study. Based on these results, a high-capacity 3D steganographic algorithm capable of controlling embedding distortion is also presented in Chapter 4. In addition to normal information, several mesh interrogation, processing and rendering algorithms make direct or indirect use of curvature information. Motivated by this, Chapter 5 studies the relation between Discrete Gaussian Curvature (DGC) degradation and vertex coordinate modifications. Chapter 6 proposes a robust watermarking algorithm for 3D polygonal models, based on modifying the histogram of the distances from the model vertices to a point in 3D space. That point is determined by applying Principal Component Analysis (PCA) to the cover model. The use of PCA makes the watermarking method robust against common 3D operations, such as rotation, translation and vertex reordering. In addition, Chapter 6 develops a 3D specific steganalytic algorithm to detect the existence of the hidden messages embedded by one well-known watermarking method. By contrast, the focus of Chapter 7 will be on developing a 3D watermarking algorithm that is resistant to mesh editing or deformation attacks that change the global shape of the mesh. By adopting a framework which has been successfully developed for image steganalysis, Chapter 8 designs a 3D steganalysis method to detect the existence of messages hidden in 3D models with existing steganographic and watermarking algorithms. The efficiency of this steganalytic algorithm has been evaluated on five state-of-the-art 3D watermarking/steganographic methods. Moreover, being a universal steganalytic algorithm can be used as a benchmark for measuring the anti-steganalysis performance of other existing and most importantly future watermarking/steganographic algorithms. Chapter 9 concludes this thesis and also suggests some potential directions for future work

Sixteenth NASTRAN (R) Users' Colloquium

These are the proceedings of the Sixteenth NASTRAN Users' Colloquium held in Arlington, Virginia from 25 to 29 April, 1988. Technical papers contributed by participants review general application of finite element methodology and the specific application of the NASA Structural Analysis System (NASTRAN) to a variety of static and dynamic structural problems

Power Analysis Attacks on Keccak

Side Channel Attacks (SCA) exploit weaknesses in implementations of cryptographic functions resulting from unintended inputs and outputs such as operation timing, electromagnetic radiation, thermal/acoustic emanations, and power consumption to break cryptographic systems with no known weaknesses in the algorithm’s mathematical structure. Power Analysis Attack (PAA) is a type of SCA that exploits the relationship between the power consumption and secret key (secret part of input to some cryptographic process) information during the cryptographic device normal operation. PAA can be further divided into three categories: Simple Power Analysis (SPA), Differential Power Analysis (DPA) and Correlation Power Analysis (CPA). PAA was first introduced in 1998 and mostly focused on symmetric-key block cipher Data Encryption Standard (DES). Most recently this technique has been applied to cryptographic hash functions. Keccak is built on sponge construction, and it provides a new Message Authentication Code (MAC) function called MAC-Keccak. The focus of this thesis is to apply the power analysis attacks that use CPA technique to extract the key from the MAC-Keccak. So far there are attacks of physical hardware implementations of MAC-Keccak using FPGA development board, but there has been no side channel vulnerability assessment of the hardware implementations using simulated power consumption waveforms. Compared to physical power extraction, circuit simulation significantly reduces the complexity of mounting a power attack, provides quicker feedback during the implementation/study of a cryptographic device, and that ultimately reduces the cost of testing and experimentation. An attack framework was developed and applied to the Keccak high speed core hardware design from the SHA-3 competition, using gate-level circuit simulation. The framework is written in a modular fashion to be flexible to attack both simulated and physical power traces of AES, MAC-Keccak, and future crypto systems. The Keccak hardware design is synthesized with the Synopsys 130-nm CMOS standard cell library. Simulated instantaneous power consumption waveforms are generated with Synopsys PrimeTime PX. 1-bit, 2-bit, 4-bit, 8-bit, and 16-bit CPA selection function key guess size attacks are performed on the waveforms to compare/analyze the optimization and computation effort/performance of successful key extraction on MAC-Keccak using 40 byte key size that fits the whole bottom plane of the 3D Keccak state. The research shows the larger the selection function key guess size used, the better the signal-noise-ratio (SNR), therefore requiring fewer numbers of traces needed to be applied to retrieve the key but suffer from higher computation effort time. Compared to larger selection function key guess size, smaller key guess size has lower SNR that requires higher number of applied traces for successful key extraction and utilizes less computational effort time. The research also explores and analyzes the attempted method of attacking the second plane of the 3D Keccak state where the key expands beyond 40 bytes using the successful approach against the bottom plane

Neuromorphic Engineering Editors' Pick 2021

This collection showcases well-received spontaneous articles from the past couple of years, which have been specially handpicked by our Chief Editors, Profs. André van Schaik and Bernabé Linares-Barranco. The work presented here highlights the broad diversity of research performed across the section and aims to put a spotlight on the main areas of interest. All research presented here displays strong advances in theory, experiment, and methodology with applications to compelling problems. This collection aims to further support Frontiers’ strong community by recognizing highly deserving authors

Design and resource management of reconfigurable multiprocessors for data-parallel applications

FPGA (Field-Programmable Gate Array)-based custom reconfigurable computing machines have established themselves as low-cost and low-risk alternatives to ASIC (Application-Specific Integrated Circuit) implementations and general-purpose microprocessors in accelerating a wide range of computation-intensive applications. Most often they are Application Specific Programmable Circuiits (ASPCs), which are developer programmable instead of user programmable. The major disadvantages of ASPCs are minimal programmability, and significant time and energy overheads caused by required hardware reconfiguration when the problem size outnumbers the available reconfigurable resources; these problems are expected to become more serious with increases in the FPGA chip size. On the other hand, dominant high-performance computing systems, such as PC clusters and SMPs (Symmetric Multiprocessors), suffer from high communication latencies and/or scalability problems. This research introduces low-cost, user-programmable and reconfigurable MultiProcessor-on-a-Programmable-Chip (MPoPC) systems for high-performance, low-cost computing. It also proposes a relevant resource management framework that deals with performance, power consumption and energy issues. These semi-customized systems reduce significantly runtime device reconfiguration by employing userprogrammable processing elements that are reusable for different tasks in large, complex applications. For the sake of illustration, two different types of MPoPCs with hardware FPUs (floating-point units) are designed and implemented for credible performance evaluation and modeling: the coarse-grain MIMD (Multiple-Instruction, Multiple-Data) CG-MPoPC machine based on a processor IP (Intellectual Property) core and the mixed-mode (MIMD, SIMD or M-SIMD) variant-grain HERA (HEterogeneous Reconfigurable Architecture) machine. In addition to alleviating the above difficulties, MPoPCs can offer several performance and energy advantages to our data-parallel applications when compared to ASPCs; they are simpler and more scalable, and have less verification time and cost. Various common computation-intensive benchmark algorithms, such as matrix-matrix multiplication (MMM) and LU factorization, are studied and their parallel solutions are shown for the two MPoPCs. The performance is evaluated with large sparse real-world matrices primarily from power engineering. We expect even further performance gains on MPoPCs in the near future by employing ever improving FPGAs. The innovative nature of this work has the potential to guide research in this arising field of high-performance, low-cost reconfigurable computing. The largest advantage of reconfigurable logic lies in its large degree of hardware customization and reconfiguration which allows reusing the resources to match the computation and communication needs of applications. Therefore, a major effort in the presented design methodology for mixed-mode MPoPCs, like HERA, is devoted to effective resource management. A two-phase approach is applied. A mixed-mode weighted Task Flow Graph (w-TFG) is first constructed for any given application, where tasks are classified according to their most appropriate computing mode (e.g., SIMD or MIMD). At compile time, an architecture is customized and synthesized for the TFG using an Integer Linear Programming (ILP) formulation and a parameterized hardware component library. Various run-time scheduling schemes with different performanceenergy objectives are proposed. A system-level energy model for HERA, which is based on low-level implementation data and run-time statistics, is proposed to guide performance-energy trade-off decisions. A parallel power flow analysis technique based on Newton\u27s method is proposed and employed to verify the methodology

Aeronautical Engineering: A continuing bibliography with indexes, supplement 185

This bibliography lists 462 reports, articles and other documents introduced into the NASA scientific and technical information system in February 1985. Aerodynamics, aeronautical engineering, aircraft design, aircraft stability and control, geophysics, social sciences, and space sciences are some of the areas covered

Cosmology with Planck: an all-sky temperature and polarisation analysis

Cosmology is now a precision science. The temperature anisotropies in the cosmic microwave background (CMB) have been exquisitely mapped by many experiments over the last decade. The Planck satellite was launched in 2009, observed the sky in temperature and polarisation, and released the nominal mission temperature data to the public in 2013. Planck has shed new light on CMB polarisation anisotropies and the polarisation signal from our own galaxy, and knowledge of the galactic emission forms a central part of this analysis presented in this thesis. I first introduce the background cosmology and review what we know about CMB temperature and polarisation anisotropies, including their mathematical formulation and representation on the sphere. I review our knowledge of the origin of galactic polarised foregrounds, particularly electron synchrotron and thermal dust emission. I then describe the generation of polarised CMB maps from an input cosmological model, and the generation of CMB polarised foregrounds using a variety of methods to create full-sky maps of the microwave sky at the Planck observing frequencies between 30 and 353 GHz. I develop a parametric fitting maximum-likelihood polarised component separation routine with correlated foreground parameters to extract the CMB and associated foregrounds to a high precision, and show that my method can reliably recover a primordial $\textit{B}$-mode polarisation signal at $\textit{r}$ = 0.1 at multiple map resolutions. I then test the sky model against the full mission Planck data to examine how accurately the foregrounds are simulated, and find that along the galactic plane the simulations are accurate, but at high latitudes the agreement worsens. I also compare the polarisation morphology to that seen in the WMAP data and find a tension between Planck and WMAP. I present an analysis of the dx8 polarisation data in terms of polarised amplitudes and orientations, and investigate a variety of foreground separation routines to get a feel for the reliability of the data. Significant systematic issues are found and I conclude that in their current state, the polarisation data are not reliable enough for precise cosmology. Finally I develop a Fisher matrix analysis of the temperature power spectrum using the full mission covariance matrix to explore the parameter space around a CosmoMC simulation, and extract the principal components for different models. I use this to explore a strange oscillation in the power spectrum and conclude that it is a statistical fluke, a conclusion confirmed in a recent data release. I close by offering extensions to the work and a look into the future of the field

Computational Intelligence and Complexity Measures for Chaotic Information Processing

This dissertation investigates the application of computational intelligence methods in the analysis of nonlinear chaotic systems in the framework of many known and newly designed complex systems. Parallel comparisons are made between these methods. This provides insight into the difficult challenges facing nonlinear systems characterization and aids in developing a generalized algorithm in computing algorithmic complexity measures, Lyapunov exponents, information dimension and topological entropy. These metrics are implemented to characterize the dynamic patterns of discrete and continuous systems. These metrics make it possible to distinguish order from disorder in these systems. Steps required for computing Lyapunov exponents with a reorthonormalization method and a group theory approach are formalized. Procedures for implementing computational algorithms are designed and numerical results for each system are presented. The advance-time sampling technique is designed to overcome the scarcity of phase space samples and the buffer overflow problem in algorithmic complexity measure estimation in slow dynamics feedback-controlled systems. It is proved analytically and tested numerically that for a quasiperiodic system like a Fibonacci map, complexity grows logarithmically with the evolutionary length of the data block. It is concluded that a normalized algorithmic complexity measure can be used as a system classifier. This quantity turns out to be one for random sequences and a non-zero value less than one for chaotic sequences. For periodic and quasi-periodic responses, as data strings grow their normalized complexity approaches zero, while a faster deceasing rate is observed for periodic responses. Algorithmic complexity analysis is performed on a class of certain rate convolutional encoders. The degree of diffusion in random-like patterns is measured. Simulation evidence indicates that algorithmic complexity associated with a particular class of 1/n-rate code increases with the increase of the encoder constraint length. This occurs in parallel with the increase of error correcting capacity of the decoder. Comparing groups of rate-1/n convolutional encoders, it is observed that as the encoder rate decreases from 1/2 to 1/7, the encoded data sequence manifests smaller algorithmic complexity with a larger free distance value