Concurrent error detection of fault-based side-channel cryptanalysis of 128-bit RC6 block cipher

Fault-based side channel cryptanalysis is very effective against symmetric and asymmetric encryption algorithms. Although straightforward hardware and time redundancy based concurrent error detection (CED) architectures can be used to thwart such attacks, they entail significant overhead (either area or performance). In this paper we investigate two systematic approaches to low-cost, low-latency CED for symmetric encryption algorithm RC6. The proposed techniques have been validated on FPGA implementations of RC6, one of the advanced encryption standard finalists.     

GRAPHICAL SOLUTION OF MULTISTAGE FLUIDIZED BED HEAT EXCHANGER

The design of multistage fluidized beds for heat exchange necessitates the solution of the mass and energy balance equations combined with the equilibrium relations for each stage. This paper presents a novel way of applying well known methodology to a different technology, one where it has not been widely applied.

In the present work a McCabe-Thiele type of graphical approach is presented for both counter-current and cross-current contacting multiple fluidized beds. The necessary equations for a multistage calciner are developed and the application of the proposed method is demonstrated. Generalized fluidized bed efficiency for counter-current and cross-current multiple fluidized bed is presented.     

Predictive models for emission of hydrogen powered car using various artificial intelligent tools

This paper investigates the use of artificial intelligent models as virtual sensors to predict relevant emissions such as carbon dioxide, carbon monoxide, unburnt hydrocarbons and oxides of nitrogen for a hydrogen powered car. The virtual sensors are developed by means of application of various Artificial Intelligent (AI) models namely; AI software built at the University of Tasmania, back-propagation neural networks with Levenberg–Marquardt algorithm, and adaptive neuro-fuzzy inference systems. These predictions are based on the study of qualitative and quantitative effects of engine process parameters such as mass airflow, engine speed, air-to-fuel ratio, exhaust gas temperature and engine power on the harmful exhaust gas emissions. All AI models show good predictive capability in estimating the emissions. However, excellent accuracy is achieved when using back-propagation neural networks with Levenberg–Marquardt algorithm in estimating emissions for various hydrogen engine operating conditions with the predicted values less than 6% of percentage average root mean square error.     

Physical solvent extraction of levulinic acid from dilute aqueous solution with 2-methyltetrahydrofuran

The results of the present investigation reveal that 2-methyltetrahydrofuran is a potential solvent for the extraction of levulinic acid from dilute aqueous solution. This conclusion is based on the relatively high values of distribution coefficient K_d (1.3-1.6) measured for the system of levulinic acid – water – 2-methyltetrahydrofuran at temperatures 298.2 K, 313.2 K, and 328.2 K, as well as encouraging performance of the continuous counter current Kühni column. The results give reason to believe, that 2-methyltetrahydrofuran can be considered for the extraction of other low molecular weight acids, such as formic or lactic acid, as well.     

Jet cup attrition testing

Jet cup attrition testing is a common method for evaluating particle attrition in fixed fluidized beds and circulating fluidized beds. An attrition index, calculated from jet cup data, is used to compare with one or more reference materials. However, this method is far from perfect despite its popularity. Results obtained at Particulate Solid Research, Inc. (PSRI) in different-sized jet cups and a 29-cm (11.5-in.) diameter fluidized bed test unit did not provide the same ranking of catalyst with respect to particle attrition. To obtain a better understanding of attrition in a jet cup, both computational fluid dynamics (CFD) and cold flow studies were performed with a 2.5-cm (1-in.) diameter Davison-type jet cup and PSRI's cylindrical 7.6-cm (3-in.) diameter jet cup. Results showed that a significant amount of material in the Davison and PSRI jet cup remained stagnant. Based on these results and additional CFD modeling, PSRI designed a new jet cup, where most of the material was hydrodynamically active. The new jet cup showed a 25% increase in attrition compared to PSRI's cylindrical jet cup under similar conditions and run times. Results were also compared to cyclone attrition data for several materials at PSRI. The new jet cup provided data that correlated with attrition results from the 29-cm (11.5-in.) diameter fluidized bed unit.     

Attacks and Defenses for JTAG

Editor's note:JTAG is a well-known standard mechanism for in-field test. Although it provides high controllability and observability, it also poses great security challenges. This article analyzes various attacks and proposes protection schemes.—Mohammad Tehranipoor, University of Connecticut     

Selectively breaking data dependences to improve the utilization of idle cycles in algorithm level re-computing data paths

Although algorithm level re-computing techniques can trade-off the fault detection capability vs. time overhead of a Concurrent Error Detection (CED) scheme, they result in 100% time overhead when the strongest CED capability is achieved. Using the idle cycles in the data path to do the re-computation can reduce this time overhead. However, dependences between operations prevent the re-computation from fully utilizing the idle cycles. Deliberately breaking some of these data dependences can further reduce the time overhead associated with algorithm level re-computing. According to the experimental results the proposed technique, it brings time overhead down to 0-60% while the associated hardware overhead is from 12% to 50% depending on the design size.     

Micro- and Nano-Technology: A Critical Design Key in Advanced Thermoelectric Cooling Systems

Advanced thermoelectric (TE) cooling technologies are now receiving more research attention, to provide cooling in advanced vehicles and residential systems to assist in increasing overall system energy efficiency and reduce the impact of greenhouse gases from leakage by current R-134a systems. This work explores the systems-related impacts, barriers, and challenges of using micro-technology solutions integrated with advances in nano-scale thermoelectric materials in advanced TE cooling systems. Integrated system-level analyses that simultaneously account for thermal energy transport into and dissipation out of the TE device, environmental effects, temperature- dependent TE and thermo-physical properties, thermal losses, and thermal and electrical contact resistances are presented, to establish accurate optimum system designs using both p-type nanocrystalline-powder-based (NPB) Bi _x Sb_2−x Te₃/n-type Bi₂Te₃-Bi₂Se₃ TE systems and conventional p-type Bi₂Te₃-Sb₂Te₃/n-type Bi₂Te₃-Bi₂Se₃ TE systems. This work established the design trends and identified optimum design regimes and metrics for these types of systems that will minimize system mass, volume, and cost to maximize their commercialization potential in vehicular and residential applications. The relationships between important design metrics, such as coefficient of performance, specific cooling capacity, and cooling heat flux requirements, upper limits, and critical differences in these metrics in p-type NPB Bi _x Sb_2−x Te₃/ n-type Bi₂Te₃-Bi₂Se₃ TE systems and p-type Bi₂Te₃-Sb₂Te₃/n-type Bi₂Te₃-Bi₂Se₃ TE systems, are explored and quantified. Finally, the work discusses the critical role that micro-technologies and nano-technologies can play in enabling miniature TE cooling systems in advanced vehicle and residential applications and gives some key relevant examples. Pacific Northwest National Laboratory—operated for the U.S. Department of Energy by Battelle Memorial Institute under contract DE-AC05-76RLO1830.