Developing Smart Grids Based on GPRS and ZigBee Technologies Using Queueing Modeling–Based Optimization Algorithm

Smart metering systems have become widespread around the world. RF mesh communication systems have contributed to the creation of smarter and more reliable power systems. This paper presents an algorithm for positioning GPRS concentrators to attain delay constraints for a ZigBee‐based mesh network. The proposed algorithm determines the number and placement of concentrators using integer linear programming and a queueing model for the given mesh network. The solutions given by the proposed algorithm are validated by verifying the communication network performance through simulations.     

A Custom Instruction Approach for Hardware and Software Implementations of Finite Field Arithmetic over \mathbb{F}_{{2^{{163}} }} using Gaussian Normal Bases

This paper presents a comprehensive analysis of the design of custom instructions in a reconfigurable hardware platform dedicated to accelerate arithmetic operations in the binary field $\mathbb{F}_{{2^{{163}} }} $ , using a Gaussian normal basis representation. The resulting platform is capable of running real applications, thus allowing a precise measurement of the execution overheads, and a fair comparison of the hardware and software speedups at several implementation levels. By using this approach, we determine which field operations (e.g., multiplication) are better suited to constrained environments, and which ones provide an enhanced performance in general-purpose systems. Experimental results reveal that by using our fastest field multiplier implemented as a custom instruction in a combined hardware/software approach, we accelerate point multiplication (the fundamental operation in Elliptic Curve Cryptography) over 126 times.     

Self-organizing continuous attractor networks and path integration: one-dimensional models of head direction cells

Some neurons encode information about the orientation or position of an animal, and can maintain their response properties in the absence of visual input. Examples include head direction cells in rats and primates, place cells in rats and spatial view cells in primates. 'Continuous attractor' neural networks model these continuous physical spaces by using recurrent collateral connections between the neurons which reflect the distance between the neurons in the state space (e.g. head direction space) of the animal. These networks maintain a localized packet of neuronal activity representing the current state of the animal. We show how the synaptic connections in a one-dimensional continuous attractor network (of for example head direction cells) could be self-organized by associative learning. We also show how the activity packet could be moved from one location to another by idiothetic (self-motion) inputs, for example vestibular or proprioceptive, and how the synaptic connections could self-organize to implement this. The models described use 'trace' associative synaptic learning rules that utilize a form of temporal average of recent cell activity to associate the firing of rotation cells with the recent change in the representation of the head direction in the continuous attractor. We also show how a nonlinear neuronal activation function that could be implemented by NMDA receptors could contribute to the stability of the activity packet that represents the current state of the animal.     

Quantum-inspired design of resilient substitution boxes: From coding to hardware implementation

S-boxes constitute a cornerstone component in symmetric-key cryptographic algorithms, such as DES and AES encryption systems. In block ciphers, they are typically used to obscure the relationship between the plaintext and the ciphertext. Non-linear and non-correlated S-boxes are the most secure against linear and differential cryptanalysis. In this paper, we focus on a twofold objective: first, we evolve regular S-boxes with high non-linearity and low auto-correlation properties; then automatically generate evolvable hardware for the obtained S-box. Targeting the former, we use a quantum-inspired evolutionary algorithm to optimize regularity, non-linearity and auto-correlation, which constitute the three main desired properties in resilient S-boxes. Pursuing the latter, we exploit the same algorithm to automatically generate the evolvable hardware designs of substitution boxes that minimize hardware space and encryption/decryption time, which form the two main hardware characteristics. We compare our results against existing and well-known designs, which were produced by using conventional methods as well as through genetic algorithm. We will show that our approach provides higher quality S-boxes coding as well as circuits.     

Energetic and exergetic analyses of a dual-fuel diesel engine

The aim of this work is to investigate theoretically and experimentally the performance characteristics of a commercial diesel engine when operating in dual form: natural gas and diesel. The experimental facility (thermal system) is composed of a diesel engine coupled to an electronic generator with measuring sensor for temperature and pressure, air, natural gas and diesel flow meters, gas transducers, gas analyzer and power absorption system, constituted by an electric charge bank and its controlling system. For energetic and exergetic analysis of such dual engine, a mathematical model based on the thermodynamics concepts was developed. Numerical and experimental results concerning the effect of air conditions, the type and quantity of fuel used and the exhaustion gases over the engine performance and environmental impact are presented and analyzed. In this work, the diesel engine operated with powers ranging from 10 to 150 kW and replacement rates from 60% to 85%.     

New insights on the metabolism of ricinoleic acid in ruminants

Dairy goats were fed a total mixed ration with or without the inclusion of castor oil [40 g/kg of dry matter (DM)] to study the metabolism of ricinoleic acid (12-OH,cis-9–18:1). Ten goats, at 39.7 ± 4.0 d in milk, were individually penned and allocated at random to the 2 experimental diets. Goats were manually milked twice a day. Milk fatty acids (FA) were analyzed as methyl esters and hydroxyl groups were derivatized in trimethylsilyl ethers. Apart from ricinoleic acid, 6 FA were only detected in the milk of the castor oil group. Ricinoleic acid composed 0.3% of total FA in milk of the castor oil group, whereas the hydroxy-FA (8-OH-14:0, 10-OH-16:0, and 12-OH-18:0) and oxo-FA (8-oxo-14:0, 10-oxo-16:0, and 12-oxo-18:0) reached 7.5% of total FA in milk. We anticipate that these FA were derived from the metabolism of ricinoleic acid, although it was not clear if they were produced in the rumen or in the tissues. To confirm that, we conducted in vitro batch incubations repeated for 3 consecutive weeks with castor oil (40 g/kg of DM) and strained rumen fluid from 2 fistulated sheep. To examine the products formed over time, incubation tubes were stopped at 0, 6, 12, 24, 48, and 72 h. The results of the in vitro experiment showed that ricinoleic acid was metabolized in the rumen at a slow rate and the main products formed were 12-OH-18:0 and 12-oxo-18:0, by hydrogenation of the cis-9 double bond, followed by oxidation of the hydroxyl group, respectively. Our results suggest that the 12-OH-18:0 and 12-oxo-18:0 escape rumen and are further metabolized through partial β-oxidation in ruminant tissues. We propose that the 10-OH-16:0 and 8-OH-14:0 found in goat milk of the castor oil group are successive products of the β-oxidation of 12-OH-18:0, and the 10-oxo-16:0 and 8-oxo-14:0 are successive products of the 12-oxo-18:0 in tissues. Overall, our results indicate that ricinoleic acid is extensively metabolized in the rumen and tissues, producing mainly oxo- and hydroxy-FA that are further excreted in milk.     

Electrical Spin Injection from Ferromagnetic Nanocontacts into Nondegenerated Silicon at Low Temperatures

We present results on the magnetoresistance of the system Ni/Al₂O₃/Si/Al₂O₃/Ni fabricated in lateral nanostructures. The substrate n-type Si is a nondegenerated semiconductor with a doping level of 10¹⁵ cm^?3. The results are presented between 11 and 30 K, where the electrical resistivity of the semiconductor varies about 4 orders of magnitude. The reduction of magnetoresistance at 30 K is consistent with the standard theory for spin injection between a metal and a semiconductor. By fitting the data with $e^{ - t_{N} / L_{\mathrm{SD}}}$ , the diffusion condition, as a function of the channel length t _N , where the magnetoresistance takes place, we deduced the values of spin diffusion length L _SD and spin lifetime τ _s .     

Distinguishing nanowire and nanotube formation by the deposition current transients

ABSTRACT: High aspect ratio Ni nanowires (NWs) and nanotubes (NTs) were electrodeposited inside ordered arrays of self-assembled pores (approximately 50 nm in diameter and approximately 50 um in length) in anodic alumina templates by a potentiostatic method. The current transients monitored during each process allowed us to distinguish between NW and NT formation. The depositions were long enough for the deposited metal to reach the top of the template and form a continuous Ni film. The overfilling process was found to occur in two steps when depositing NWs and in a single step in the case of NTs. A comparative study of the morphological, structural, and magnetic properties of the Ni NWs and NTs was performed using scanning electron microscopy, X-ray diffraction, and vibrating sample magnetometry, respectively.