A novel low power hybrid cache using GC-EDRAM cells

In a typical embedded CPU, large on-chip storage is critical to meet high performance requirements. However, the fast increasing size of the on-chip storage based on traditional SRAM cells makes the area cost and energy consumption unsustainable for future embedded applications. Replacing SRAM with DRAM on the CPU’s chip is generally considered not worthwhile because DRAM is not compatible with the common CMOS logic and requires additional processing steps beyond what is required for CMOS. However a special DRAM technology, Gain-Cell embedded-DRAM (GC-eDRAM)  [1], [2], [3] is logic compatible and retains some of the good properties of DRAM (small and low power). In this paper we evaluate the performance of a novel hybrid cache memory where the data array, generally populated with SRAM cells, is replaced with GC-eDRAM cells while the tag array continues to use SRAM cells. Our evaluation of this cache demonstrates that, compared to the conventional SRAM-based designs, our novel architecture exhibits comparable performance with less energy consumption and smaller silicon area, enabling the sustainable on-chip storage scaling for future embedded CPUs.     

Co2FeO4@rGO composite: Towards trifunctional water splitting in alkaline media

Development of efficient, low cost and multifunctional electrocatalysts for water splitting to harvest hydrogen fuels is a challenging task, but the combination of carbon materials with transition metal-based compounds is providing a unique and attractive strategy. Herein, composite systems based on cobalt ferrite oxide-reduced graphene oxide (Co₂FeO₄) @(rGO) using simultaneous hydrothermal and chemical reduction methods have been prepared. The proposed study eliminates one step associated with the conversion of GO into rGO as it uses direct GO during the synthesis of cobalt ferrite oxide, consequently rGO based hybrid system is achieved in-situ significantly, the optimized Co₂FeO₄@rGO composite has revealed an outstanding multifunctional applications related to both oxygen evolution reaction (OER) and hydrogen counterpart (HER). Various metal oxidation states and oxygen vacancies at the surface of Co₂FeO₄@rGO composites guided the multifunctional surface properties. The optimized Co₂FeO₄@rGO composite presents excellent multifunctional properties with onset potential of 0.60 V for ORR, an overpotential of 240 mV at a 20 mAcm^?2 for OER and 320 mV at a 10 mAcm^?2 for HER respectively. Results revealed that these multifunctional properties of the optimized Co₂FeO₄@ rGO composite are associated with high electrical conductivity, high density of active sites, crystal defects, oxygen vacancies, and favorable electronic structure arisinng from the substitution of Fe for Co atoms in binary spinel oxide phase. These surface features synergistically uplifted the electrocatalytic properties of Co₂FeO₄@rGO composites. The multifunctional properties of the Co₂FeO₄@ rGO composite could be of high interest for its use in a wide range of applications in sustainable and renewable energy fields.     

Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

PID Control of Planar Nonlinear Uncertain Systems in the Presence of Actuator Saturation

This paper investigates PID control design for a class of planar nonlinear uncertain systems in the presence of actuator saturation. Based on the bounds on the growth rates of the nonlinear uncertain function in the system model, the system is placed in a linear differential inclusion. Each vertex system of the linear differential inclusion is a linear system subject to actuator saturation. By placing the saturated PID control into a convex hull formed by the PID controller and an auxiliary linear feedback law, we establish conditions under which an ellipsoid is contractively invariant and hence is an estimate of the domain of attraction of the equilibrium point of the closed-loop system. The equilibrium point corresponds to the desired set point for the system output. Thus, the location of the equilibrium point and the size of the domain of attraction determine, respectively, the set point that the output can achieve and the range of initial conditions from which this set point can be reached. Based on these conditions, the feasible set points can be determined and the design of the PID control law that stabilizes the nonlinear uncertain system at a feasible set point with a large domain of attraction can then be formulated and solved as a constrained optimization problem with constraints in the form of linear matrix inequalities (LMIs). Application of the proposed design to a magnetic suspension system illustrates the design process and the performance of the resulting PID control law.      

Use of a smartphone-based Student Response System in large active-learning Chemical Engineering Thermodynamics classrooms

Smartphones are a promising tool as student response systems (SRS) for interactive teaching due to their widespread diffusion. Here, the main purpose is to assess the efficacy of smartphone-based SRS in large classroom settings of undergraduate Thermodynamics, as representative of engineering courses requiring high-level cognitive skills for problem solving. Four sets of multiple-choice questions were presented during the course. Overall, the results refer to 1055 students between control and SRS classes, each corresponding to a3 years period.One of the main results of this work is the strong linear correlation between the average questionnaire score and the final exam grade (R² = 0.91). A similar correlation, although with a lower value of R², is already found in the first questionnaire, thus showing the SRS high predictive power of class performance. The results of this study provide guidance for a quantitative use of smartphone-based SRS in teaching basic disciplines. The SRS monitoring capability allows early detection of struggling students, thus paving the way to personalized tutoring and improved student engagement in active learning practices. This approach is especially important in emergency situations, such as the SARS-Cov-2 pandemic, when distance learning is widely adopted, and remote interactive tools are highly needed.     

Dual effect synergistically triggered Ce:(Y,Tb)3(Al,Mn)5O12 transparent ceramics enabling a high color-rendering index and excellent thermal stability for white LEDs

Ce:Y₃Al₅O₁₂ transparent ceramics (TCs) with appropriate emission light proportion and high thermal stability are significant to construct white light emitting diode devices with excellent chromaticity parameters. In this work, strategies of controlling crystal-field splitting around Ce³⁺ ion and doping orange-red emitting ion, were adopted to fabricate Ce:(Y,Tb)₃(Al,Mn)₅O₁₂ TCs via vacuum sintering technique. Notably, 85.4 % of the room-temperature luminescence intensity of the TC was retained at 150 °C, and the color rendering index was as high as 79.8. Furthermore, a 12 nm red shift and a 16.2 % increase of full width at half maximum were achieved owing to the synergistic effects of Tb³⁺ and Mn²⁺ ions. By combining TCs with a 460 nm blue chip, a warm white light with a low correlated color temperature of 4155 K was acquired. Meanwhile, the action mechanism of Tb³⁺ ion and the energy transfer between Ce³⁺ and Mn²⁺ ions were verified in prepared TCs.     

Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

A Voltage Control Method for a Distributed Line Feeder by means of Multiagent Approach

This paper proposes a method for the coordinated control of power factor by means of a multiagent approach. The proposed multiagent system consists of two types of agent: single feeder agent (F_AG) and bus agent (B_AG). In the proposed system, an F_AG plays as an important role, which decides the power factors of all distributed generators by executing the load flow calculations repeatedly. The voltage control strategies are implemented as the class definition of Java into the system. In order to verify the performance of the proposed method, it has been applied to a typical distribution model system. The simulation results show that the system is able to control very violent fluctuation of the demands and the photovoltaic (PV) generations.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

大规模多状态计算系统的容错性能分析

针对异构计算节点组成的大规模多状态计算系统的容错性能分析问题，提出了一种计算系统容错性能的评估方法。该方法采用自定义的两级容错性能形式化描述框架进行系统描述，通过构造多值决策图（Multi-value Decision Diagram，MDD）模型对系统进行容错性能建模，并基于构造的模型高效地计算出部件故障的条件下计算系统在特定性能水平上运行的概率，减少了计算的冗余性。实验结果表明，该方法在模型的大小和构建时间上均优于传统方法。该方法的提出将对系统操作员或程序设计者具有重要意义，使其确保系统适合预期应用。