Enhancing Prostate Cancer Diagnosis with In-Memory Sensing and Edge Computing of Percent-free PSA Index

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Distributed systems, which enable the efficient processing of large-scale data and complex tasks across multiple interconnected processes, offer significant advantages over single-machine systems. These include enhanced scalability, improved fault toleran ...

This thesis aimed to estimate the effect of demographic and biomechanical preoperative variables on total shoulder arthroplasty (TSA) outcomes. To achieve this, various biomechanical variables were calculated using a clinical database comprising normal and ...

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 ...

Computing servers play a key role in the development and process of emerging compute-intensive applications in recent years. However, they need to operate efficiently from an energy perspective viewpoint, while maximizing the performance and lifetime of th ...

Analog computing has emerged as a promising candidate for real-time and parallel continuous data processing. This paper presents a reciprocal way for realizing asymmetric optical transfer functions (OTFs) in the reflection side of the on-axis processing ch ...

Today, a large portion of mobile data traffic is consumed behind the shielding walls of buildings or in the Faraday cage of trains. This renders cellular network coverage from outdoor cell sites difficult. Indoor small cells and distributed antennas along ...

Amid a data revolution that is transforming industries around the globe, computing systems have undergone a paradigm shift where many applications are scaled out to run on multiple computers in a computing cluster. As the storage and processing capabilitie ...

Deep neural networks (DNNs) have revolutionized the field of artificial intelligence and have achieved unprecedented success in cognitive tasks such as image and speech recognition. Training of large DNNs, however, is computationally intensive and this has ...

The increasing ubiquity of edge devices in the consumer market, along with their ever more computationally expensive workloads, necessitate corresponding increases in computing power to support such workloads. In-memory computing is attractive in edge devi ...

In-Memory Computing (IMC) solutions, and particularly bitline computing in SRAM, appear promising as they mitigate one of the most energy consuming aspects in computation: data movement. In this work we propose a fast (2.4Ghz for bitwise operations and 2.4 ...

The integration of the resistive random access memory (ReRAM) with CMOS logic circuitry provides a solution to scaling limitations, and offers promising candidates for use in next generation computing applications. It is challenging to realize a reliable, ...

Dynamically-scheduled elastic circuits generated by High-Level Synthesis (HLS) tools are inherently out-of-order, following the flow of data rather than the evolution of an instruction pointer. Components of the circuit which access memory need to be conne ...

Nowadays electric power systems are subject to continuous changes and the needs in the power generation and delivery service are constantly increasing, with a higher complexity of a progressively more distributed network. Because the impact of a failure ca ...

Converting a color image to a grayscale image, namely decolorization, is an important process for many real-world applications. Previous methods build contrast loss functions to minimize the contrast differences between the color images and the resultant g ...

Reliable, low cost, and accessible drug monitoring systems for individualized healthcare, especially chemotherapy for malignant diseases like prostate cancer and AIDS, are highly desira-ble. This is even more critical for drugs like abiraterone and TFV, wi ...

Resistive memories have gained high research attention for enabling design of in-memory computing circuits and systems. We propose for the first time an automatic compilation methodology suited to a recently proposed computer architecture solely based on r ...

Cloud computing has been proposed as a new paradigm to deliver services over the internet. The proliferation of cloud services and increasing users’ demands for computing resources have led to the appearance of geo-distributed data centers (DCs). These DCs ...

Enhancing Prostate Cancer Diagnosis with In-Memory Sensing and Edge Computing of Percent-free PSA Index

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Optimal Byzantine Agreement with Little Cryptography

Multimodal Prediction Framework for Total Shoulder Arthroplasty Outcomes: Integrating Morphological, Musculoskeletal, Finite Element, and Bayesian Causal Models

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

Reinforcement Learning-Based Joint Reliability and Performance Optimization for Hybrid-Cache Computing Servers

Reciprocal Metasurfaces for On-axis Reflective Optical Computing

Adding Indoor Capacity without Fiber Backhaul: An mmWave Bridge Prototype

An Architecture for Load Balance in Computer Cluster Applications

Mixed-Precision Deep Learning Based on Computational Memory

BLADE: A BitLine Accelerator for Devices on the Edge

A Fast, Reliable and Wide-voltage-range In-memory Computing Architecture

Performance improvement of chip-level CMOS-integrated ReRAM cells through material optimization

A Self-organized Method for Computing the Epidemic Threshold in Computer Networks

Optimized Memory Access For Dynamically Scheduled High Level Synthesis

Electronic solutions for power system emulation

Preserving Perceptual Contrast in Decolorization with Optimized Color Orders

Ultra Selective and Sensitive Electrochemical Detection of Anti-Cancer and Anti-Viral Drugs by Optimized Nano-Bio-Sensors

An MIG-based Compiler for Programmable Logic-in-Memory Architectures

Exploiting CPU-Load and Data Correlations in Multi-Objective VM Placement for Geo-Distributed Data Centers