Pipelining and bypassing in a VLIW processor

This short note describes issues involved in the bypassing mechanism for a very long instruction word (VLIW) processor and its relation to the pipeline structure of the processor. The authors first describe the pipeline structure of their processor and analyze its performance and compare it to typical RISC-style pipeline structures given the context of a processor with multiple functional units. Next they study the performance effects of various bypassing schemes in terms of their effectiveness in resolving pipeline data hazards and their effect on the processor cycle time     

ECFGM: enriched control flow graph miner for unknown vicious infected code detection

Vicious codes, especially viruses, as a kind of impressive malware have caused many disasters and continue to exploit more vulnerabilities. These codes are injected inside benign programs in order to abuse their hosts and ease their propagation. The offsets of injected virus codes are unknown and their targets usually are latent until they are executed and activated, what in turn makes viruses very hard to detect. In this paper enriched control flow graph miner, ECFGM in short, is presented to detect infected files corrupted by unknown viruses. ECFGM uses enriched control flow graph model to represent the benign and vicious codes. This model has more information than traditional control flow graph (CFG) by utilizing statistical information of dependent assembly instructions and API calls. To the best of our knowledge, the presented approach in this paper, for the first time, can recognize the offset of infected code of unknown viruses in the victim files. The main contributions of this paper are two folds: first, the presented model is able to detect unknown vicious code using ECFG model with reasonable complexity and desirable accuracy. Second, our approach is resistant against metamorphic viruses which utilize dead code insertion, variable renaming and instruction reordering methods.     

Optimizing the Runoff Estimation with HEC-HMS Model Using Spatial Evapotranspiration by the SEBS Model

Most of the commonly used hydrological models do not account for the actual evapotranspiration (ETa) as a key contributor to water loss in semi-arid/arid regions. In this study, the HEC-HMS (Hydrologic Engineering Center Hydrologic Modeling System) model was calibrated, modified, and its performance in simulating runoff resulting from short-duration rainfall events was evaluated. The model modifications included integrating spatially distributed ETa, calculated using the surface energy balance system (SEBS), into the model. Evaluating the model’s performance in simulating runoff showed that the default HEC-HMS model underestimated the runoff with root mean squared error (RMSE) of 0.14 m³/s (R²?=?0.92) while incorporating SEBS ETa into the model reduced RMSE to 0.01 m³/s (R²?=?0.99). The integration of HECHMS and SEBS resulted in smaller and more realistic latent heat flux estimates translated into a lower water loss rate and a higher magnitude of runoff simulated by the HECHMS model. The difference between runoff simulations using the default and modified model translated into an average of 95,000 m³ runoff per rainfall event (equal to seasonal water requirement of ten-hectare winter wheat) that could be planned and triggered for agricultural purposes, flood harvesting, and groundwater recharge in the region. The effect of ETa on the simulated runoff volume is expected to be more pronounced during high evaporative demand periods, longer rainfall events, and larger catchments. The outcome of this study signifies the importance of implementing accurate estimates of evapotranspiration into a hydrological model.

     

Model reference adaptive impedance control in Cartesian coordinates for physical human–robot interaction

In this paper, a nonlinear model reference adaptive impedance controller is proposed and tested. The controller provides asymptotic tracking of a reference impedance model for the robot end-effector in Cartesian coordinates applicable to rehabilitation robotics or any other human–robot interactions such as haptic systems. The controller uses the parameters of a desired stable reference model which is the target impedance for the robot’s end-effector. It also considers uncertainties in the model parameters of the robot. The asymptotic tracking is proven using Lyapunov stability theorem. Moreover, the adaptation law is proposed in joint space for reducing the complexity of its calculations; however, the controller and the stability proof are all presented in Cartesian coordinates. Using simulations and experiments on a two DOFs robot, the effectiveness of the proposed controller is investigated.     

Preparation of epoxy–clay nanocomposite and investigation on its anti-corrosive behavior in epoxy coating

An epoxy–clay nanocomposite was synthesized using a quaternary ammonium-modified montmorillonite clay and diglycidyl ether of bisphenol A (DGEBA) type epoxy resin, in order to produce anti-corrosive epoxy coating. Anti-corrosive properties of the nanocomposite were investigated using salt spray and electrochemical impedance spectroscopy (EIS) methods. The results showed an improvement in the barrier and anti-corrosive characteristics of epoxy-based nanocomposite coating and a decrease in water uptake in comparison with pure epoxy coating. Wide-angle X-ray diffraction (WAXD) patterns and transmission electron microscopy (TEM) analysis showed that the interlayer spacing of clays increased after addition of epoxy resin along with applying shear force and ultrasound sonicator. The best performance of this coating was achieved at 3 and 5 wt.% clay concentration.     

Design and evaluation of a high throughput QoS-aware and congestion-aware router architecture for Network-on-Chip

This paper proposes a novel QoS-aware and congestion-aware Network-on-Chip architecture that not only enables quality-oriented network transmission and maintains a feasible implementation cost but also well balance traffic load inside the network to enhance overall throughput. By differentiating application traffic into different service classes, bandwidth allocation is managed accordingly to fulfill QoS requirements. Incorporating with congestion control scheme which consists of dynamic arbitration and adaptive routing path selection, high priority traffic is directed to less congested areas and is given preference to available resources. Simulation results show that average latency of high priority and overall traffic is improved dramatically for various traffic patterns. Cost evaluation results also show that the proposed router architecture requires negligible cost overhead but provides better performance for both advanced mesh NoC platforms.     

Dynamics of localizable entanglement in a qutrit chain with Dzyaloshinskii–Moriya interaction

Dynamics of localizable entanglement in a qutrit chain, in the presence of the Dzyaloshinskii–Moriya (DM) interaction is studied. Three distinct initial states, namely, superposition of the ground and the first excited state (SGE), a GHZ state and a superposition of qutrit coherent states (SQCS) are considered in this investigation. While the ground and the first excited state exhibit the maximum of entanglement, the latter is diminished for any superposition of the states. In both SGE and GHZ cases, localizable entanglement (LE) oscillates and its period is a decreasing function of the ratio of the strength of DM interaction and the spin coupling constant (DS ratio), but its maximum value is independent of the latter. In SQCS case, LE also oscillates in time at small values of DS ratio; its average is reduced as the strength of the DM interaction increases and gains its maximum average and the highest peaks at a specific value of the coherence parameter.     

Reactivity of perovskites on oxidative coupling of methane

Well-defined structures like ABO₃ (A = Ba, Sr, Ca; and B = Ti, Zr) perovskites were prepared by a sol-gel method which permits the formation of a crystalline structure at low-calcination temperatures (700 °C). The perovskite structures were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and Brunauer-Emmett-Teller (BET) methods and the carbonate present at the surface was determined by Fourier transform infra-red spectroscopy. Reactivity studies showed that the perovskite structures are stable under oxidative coupling of methane (OCM) conditions. The yield increases followed the sequence Ca < Sr < Ba and Zr < Ti, and a stable BaTiO₃ gives a C₂ yield of 15% at 800 °C.     

ConsilientSFL: using preferential voting system to generate combinatorial ranking metrics for spectrum-based fault localization

Spectrum-based fault localization (SFL) techniques have shown considerable effectiveness in localizing software faults. They leverage a ranking metric to automatically assign suspiciousness scores to certain entities in a given faulty program. However, for some programs, the current SFL ranking metrics lose effectiveness. In this paper, we introduce ConsilientSFL that is served to synthesize a new ranking metric for a given program, based on a customized combination of a set of given ranking metrics. ConsilientSFL can be significant since it demonstrates the usage of voting systems into a software engineering task. First, several mutated, faulty versions are generated for a program. Then, the mutated versions are executed with the test data. Next, the effectiveness of each existing ranking metric is computed for each mutated version. After that, for each mutated version, the computed existing metrics are ranked using a preferential voting system. Consequently, several top metrics are chosen based on their ranks across all mutated versions. Finally, the chosen ranking metrics are normalized and synthesized, yielding a new ranking metric. To evaluate ConsilientSFL, we have conducted experiments on 27 subject programs from Code4Bench and Siemens benchmarks. In the experiments, we found that ConsilientSFL outperformed every single ranking metric. In particular, for all programs on average, we have found performance measures recall, precision, f-measure, and percentage of code inspection, to be nearly 7, 9, 12, and 5 percentages larger than using single metrics, respectively. The impact of this work is twofold. First, it can mitigate the issue with the choice and usage of a proper ranking metric for the faulty program at hand. Second, it can help debuggers find more faults with less time and effort, yielding higher quality software.