There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

A diverse spectrum of technology drivers such as improved thermal barriers, higher efficiency thermoelectric energy conversion, phase-change memory, heat-assisted magnetic recording, thermal management of nanoscale electronics, and nanoparticles for thermal medical therapies are motivating studies of the applied physics of thermal transport at the nanoscale. This review emphasizes developments in experiment, theory, and computation in the past ten years and summarizes the present status of the field. Interfaces become increasingly important on small length scales. Research during the past decade has extended studies of interfaces between simple metals and inorganic crystals to interfaces with molecular materials and liquids with systematic control of interface chemistry and physics. At separations on the order of ∼1 nm, the science of radiative transport through nanoscale gaps overlaps with thermal conduction by the coupling of electronic and vibrational excitations across weakly bonded or rough interface...

/pdf/nanoscale-thermal-transport-ii-2003-2012-4upcs4bq86.pdf

Nanoscale thermal transport. II. 2003–2012

The smart grid concept continues to evolve and various methods have been developed to enhance the energy efficiency of the electricity infrastructure. Demand Response (DR) is considered as the most cost-effective and reliable solution for the smoothing of the demand curve, when the system is under stress. DR refers to a procedure that is applied to motivate changes in the customers' power consumption habits, in response to incentives regarding the electricity prices. In this paper, we provide a comprehensive review of various DR schemes and programs, based on the motivations offered to the consumers to participate in the program. We classify the proposed DR schemes according to their control mechanism, to the motivations offered to reduce the power consumption and to the DR decision variable. We also present various optimization models for the optimal control of the DR strategies that have been proposed so far. These models are also categorized, based on the target of the optimization procedure. The key aspects that should be considered in the optimization problem are the system's constraints and the computational complexity of the applied optimization algorithm.

A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms

Introduction to heat transfer

Logic Cell modeling is an important component in the analysis and design of CMOS integrated circuits, mostly due to nonlinear behavior of CMOS cells with respect to the voltage signal at their input and output pins. A current-based model for CMOS logic cells is presented which can be used for effective crosstalk noise and delta delay analysis in CMOS VLSI circuits. Existing current source models are expensive and need a new set of Spice-based characterization which is not compatible with typical EDA tools. In this paper we present Imodel, a simple nonlinear logic cell model that can be derived from the typical cell libraries such as NLDM, with accuracy much higher than NLDM-based cell delay models. In fact, our experiments show an average error of 3% compared to Spice. This level of accuracy comes with a maximum runtime penalty of 19% compared to NLDM-based cell delay models on medium sized industrial designs.

/pdf/an-efficient-current-based-logic-cell-model-for-crosstalk-4i1mdbww09.pdf

An efficient current-based logic cell model for crosstalk delay analysis

With the aggressive downscaling of process technologies and the importance of battery-powered systems, reducing leakage power consumption has become a crucial design challenge for IC designers. In addition, the traditional bulk CMOS technologies face significant challenges related to short-channel effects and process variations. FinFET devices have attracted a lot of attention as an alternative to bulk CMOS in sub-32nm technology nodes. This paper presents a device-circuit cross-layer framework to utilize fine-grained gate-length biased FinFETs for circuit leakage power reduction in near- and super-threshold ( $V_T$ ) operation regimes. The impacts of cell-level and transistor-level Gate-Length Biasing (GLB) on circuit speed and leakage power are studied using a 7 nm FinFET technology.

An Exploration of Applying Gate-Length-Biasing Techniques to Deeply-Scaled FinFETs Operating in Multiple Voltage Regimes

Dynamic energy pricing policy introduces real-time power-consumption-reflective pricing in the smart grid in order to incentivise energy consumers to schedule electricity-consuming applications (tasks) more prudently to minimise electric bills. This has become a particularly interesting problem with the availability of photovoltaic (PV) power generation facilities and controllable energy storage systems. This study addresses the problem of concurrent task scheduling and storage management for residential energy consumers with PV and storage systems, in order to minimise the electric bill. A general type of dynamic pricing scenario is assumed where the energy price is both time-of-use and power dependent. Tasks are allowed to support suspend-now and resume-later operations. A negotiation-based iterative approach has been proposed. In each iteration, all tasks are ripped-up and rescheduled under a fixed storage charging/discharging scheme, and then the storage control scheme is derived based on the latest task scheduling. The concept of congestion is introduced to gradually adjust the schedule of each task, whereas dynamic programming is used to find the optimal schedule. A near-optimal storage control algorithm is effectively implemented. Experimental results demonstrate that the proposed algorithm can achieve up to 60.95% in the total energy cost reduction compared with various baseline methods.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cps.2017.0050

CTS2M: concurrent task scheduling and storage management for residential energy consumers under dynamic energy pricing

An optimal energy co-scheduling framework for smart buildings

With the aggressive downscaling of the process technologies and importance of battery-powered systems, reducing leakage power consumption has become one of the most crucial design challenges for IC designers. This paper presents a device-circuit cross-layer framework to utilize fine-grained gate-length biased FinFETs for circuit leakage power reduction in the near- and super-threshold operation regimes. The impacts of Gate-Length Biasing (GLB) on circuit speed and leakage power are first studied using one of the most advanced technology nodes — a 7nm FinFET technology. Then multiple standard cell libraries using different leakage reduction techniques, such as GLB and Dual-Fj-, are built in multiple operating regimes at this technology node. It is demonstrated that, compared to Dual-Fj-, GLB is a more suitable technique for the advanced 7nm FinFET technology due to its capability of delivering a finer-grained trade-off between the leakage power and circuit speed, not to mention the lower manufacturing cost. The circuit synthesis results of a variety of ISCAS benchmark circuits using the presented GLB 7nm FinFET cell libraries show up to 70% leakage improvement with zero degradation in circuit speed in the near- and super-threshold regimes, respectively, compared to the standard 7nm FinFET cell library.

Shahin Nazarian

Papers

An efficient current-based logic cell model for crosstalk delay analysis

An Exploration of Applying Gate-Length-Biasing Techniques to Deeply-Scaled FinFETs Operating in Multiple Voltage Regimes

CTS2M: concurrent task scheduling and storage management for residential energy consumers under dynamic energy pricing

An optimal energy co-scheduling framework for smart buildings

Leakage power reduction for deeply-scaled FinFET circuits operating in multiple voltage regimes using fine-grained gate-length biasing technique