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Electrochemical Impedance Spectroscopy (EIS) and Equivalent Circuit Models (ECMs) are widely used to characterize the impedance and estimate parameters of electrochemical systems such as batteries. We use a generic ECM with ten parameters grouped to model ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

The ITER Electron Cyclotron Resonance Heating and Current Drive (ECRH&CD) system relies on 1 MW 170 GHz Gyrotrons to provide the mm-wave power needed for plasma heating, current drive, and magneto-hydrodynamic control. The design and modeling of the contro ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

Memory devices have returned to the spotlight due to increasing interest in using in-memory computing architectures to make data-driven algorithms more energy-efficient. One of the main advantages of this architecture is the efficient performance of vector ...

Analytical engines rely on in-memory data caching to avoid storage accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- and time-based caching decisions, however, are a proxy of the expected query ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

By supporting the access of multiple memory words at the same time, Bit-line Computing (BC) architectures allow the parallel execution of bit-wise operations in-memory. At the array periphery, arithmetic operations are then derived with little additional o ...

Information derived from experiences is incorporated into the brain as changes to ensembles of cells, termed engram cells, which allow memory storage and recall. The mechanism by which those changes hold specific information is unclear. Here, we test the h ...

Objective: To characterize ambulatory knee moments with respect to medial knee osteoarthritis (OA) severity comprehensively and to assess the possibility of developing a severity index combining knee moment parameters. ...

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

A method of accessing a memory space of a memory device with a decoder, the memory space having faults, including the steps of performing a memory access operation by an electronic device to a access a logical memory space of the memory device, and randomi ...

We have witnessed a wide range of theoretical as well as experimental investigations to envisage external stimuli induced changes in electronic, optical and magnetic properties in the metal organiccomplexes, while hybrid perovskites have recently joined th ...

Analytical engines rely on in-memory caching to avoid disk accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- & time-based caching decisions, however, are a proxy of the expected query execution ...

Since the 70s, there has been a growing interest in activity-based modelling. This approach models the need to travel as a result of performing daily activities (Bowman and Ben-Akiva, 2001). Nevertheless, the activities need to be scheduled which involves ...

We consider expected performances based on max-stable random fields and we are interested in their derivatives with respect to the spatial dependence parameters of those fields. Max-stable fields, such as the Brown-Resnick and Smith fields, are very popula ...

Bootstrapping parameters for the approximate homomorphic-encryption scheme of Cheon et al., CKKS (Asiacrypt 17), are usually instantiated using sparse secrets to be efficient. However, using sparse secrets constrains the range of practical parameters withi ...

Disaggregated memory can address resource provisioning inefficiencies in current datacenters. Multiple software runtimes for disaggregated memory have been proposed in an attempt to make disaggregated memory practical. These systems rely on the virtual mem ...

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On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Secure Interface Design Leveraging Hardware/Software Support

Sensitivity Analysis of the Lumped Thermal Model of the EU 170 GHz Gyrotron Magnetron Injection Gun

EdgeAI-Aware Design of In-Memory Computing Architectures

Rebooting Virtual Memory with Midgard

How to Achieve Large-Area Ultra-Fast Operation of MoS 2 Monolayer Flash Memories?

HPCache: memory-efficient OLAP through proportional caching revisited

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference

Engram cell connectivity as a mechanism for information encoding and memory function

Diverse parameters of ambulatory knee moments differ with medial knee osteoarthritis severity and are combinable into a severity index

Data-driven modeling of beam loss in the LHC

Method for reading and writing unreliable memories and a corresponding memory controller device and memory

Tuning paradigm of external stimuli driven electronic, optical and magnetic properties in hybrid perovskites and metalorganic complexes br

HPCache: Memory-Efficient OLAP Through Proportional Caching

Representing location choice within activity-based models

Stochastic derivative estimation for max-stable random fields

Bootstrapping for Approximate Homomorphic Encryption with Negligible Failure-Probability by Using Sparse-Secret Encapsulation

Rethinking Software Runtimes for Disaggregated Memory