Computing - Science topic

Supercomputing power is one of the fundamental pillars of the digital society, which depends on the accurate scheduling of parallel applications in High-Performance Computing (HPC) centers to minimize computing times. However, precedence-constraint task scheduling is a well-known NP-Hard optimization problem, and no optimal polynomial-time algorith...

In the present article, we establish the numerical solution for the mixed Volterra-Fredholm integral equation (MV-FIE) in (1+1) dimensional in the Banach space L 2 [−1, 1] × C[0, T ], T < 1. The Fredholm integral term is considered in the space L 2 [−1, 1], and it has a discontinuous kernel in position. While the Volterra integral term is considere...

Aim & Scope of the book series: A major objective of this book series is to drive innovation in every aspect of Artificial Intelligent. It offers researchers, educators, and students the opportunity to discuss and share ideas on topics, trends, and developments in artificial intelligence, machine learning, deep learning, big data, and computer inte...

Special Issue Information Dear colleagues, Applied mathematics and statistics methods have advanced considerably during the past decades, mainly as a result of the remarkable rise of computing and data abundance. Statistical process monitoring involves collecting data, learning from it, and developing data-driven models for monitoring purposes. W...

Industrial Internet of Things (IIoT) is experiencing rapid developments in the era of Industry 4.0. However, the ever-increasing applications put forwards higher requirements for authentication. Facing such a problem, researchers combine two cutting-edge techniques, i.e., Physical Unclonable Function (PUF) and blockchain. In detail, PUF can gener...

In this paper, an evolutionary single-pixel imaging (SPI) scheme is proposed to solve combinational optimization problems. SPI is a unique optical imaging technique by replacing the pixelated sensor array in a conventional camera with a single-pixel detector. SPI is conventionally employed for capturing object images or performing image processing...

This paper addresses the double traveling salesman problem with partial last‐in‐first‐out (LIFO) loading constraints. A vehicle picks up items in the pickup area and loads them into its container, a horizontal stack. Once all the pickup operations are done, the vehicle can deliver the items to the delivery area because pickup‐and‐delivery areas are...

This project explores the potential of Differentiable Digital Signal Processing (DDSP) to represent and synthesize the timbre of five different notes of the Korean traditional musical instrument, Geo-mungo, using digital instrumental samples of the bass guitar, which has a similar mechanism to produce the sound. To evaluate the feasibility and qual...

Today, DNNs’ high computational complexity and sub-optimal device utilization present a major roadblock to democratizing DNNs. To reduce the execution time and improve device utilization, researchers have been proposing new system design solutions, which require performance models (especially GPU models) to help them with pre-product concept valida...

The aim of the conference is to open a discussion on the topic of “computing the human.” It is intended as a “melting pot” for interdisciplinary debate reflecting the complexity of the issues: cultural history of computing, human-computer interaction (HCI), and emotion programming, all framed by the ethos of diversity and inclusion in computing and...

Topic models are a class of unsupervised learning algorithms for detecting the semantic structure within a text corpus. Together with a subsequent dimensionality reduction algorithm, topic models can be used for deriving spatializations for text corpora as two-dimensional scatter plots, reflecting semantic similarity between the documents and suppo...

As the professional field of data visualization grows, so does the importance of preparing students effectively for the demands of real-world practice. Computing education has historically sought to teach and evaluate abstract knowledge (e.g., theories, principles, guidelines, design patterns) and the application of such knowledge to given problems...

https://www.mdpi.com/journal/processes/special_issues/Computational_Genome The aim of this Special Issue is to collect research articles on, among other topics, methods, algorithms and their implementations in the field of computational biology. New approaches are especially important during the analysis of genomes and proteins, and striving to est...

This research introduces an extended Information Extrac- tion system for Named Entity Recognition (NER) that allows machine learning (ML) practitioners and medical domain experts to customize and develop their own models using transformers and a range of Cloud resources. Our system provides support for the entire process of managing Cloud resources...

Evaluating the success of applications from a summative perspective is essential to many industry researchers' roles, yet a thorough understanding of what to measure and how to bridge business frameworks remains elusive. New technologies and novel ways of interacting with applications have garnered domain-specific interest in evaluating these exper...

During the COVID-19 pandemic, remote learning (RL) transformed the educational landscape for hands-on Computer Science courses. This paradigm shift accelerated the transition from traditional in-person programming labs to decentralized student-provided resources. Even as students returned to in-person learning, many continued to rely on their perso...

The rapid computerized simulation of stochastic computing (SC) systems is a challenging problem. A method for agile simulation of SC image processing is proposed in this work. The input operands are processed with the aid of a correlation-controlled contingency table (CT) construct without using actual stochastic bit-streams. The proposed approach...

Wi-Fi Channel State Information (CSI) based human activity recognition (HAR) which using channel disturbances caused by signal reflection is a novel way of environment sensing and motion recognition. The collected channels characteristics are heavily influenced by the environment , human activity patterns and subject's weight and height. These sign...

Enabling students to evaluate the impacts of computing on their own lives and on society is an internationally proclaimed goal of secondary computing education. The literature and existing curricula provide no shortage of various example impacts and contexts, but how these relate to each other, and what, if anything, constitutes their common conce...

This paper studies the possibility of exploring Field Programmable Gate Array (FPGA) in the acceleration of Computational Fluid Dynamics (CFD). CFD is an industrial analysis tool to estimate the flow of matter. In the previous experience, CFD are most implemented on the conventional CPU, and may accelerate with GPUs in a high-performance computing...

For the fatigue reliability analysis of aeroengine blade-disc systems, the traditional direct integral modelling methods or separate independent modelling methods will lead to low computational efficiency or accuracy. In this work, a physics-informed ensemble learning (PIEL) method is proposed, i.e. firstly, based on the physical characteristics of...

Sixth-generation wireless systems not only have more demanding communication requirements, they are also expected to have high-precision sensing capabilities and sufficient computing power. Integrated sensing, communication, and computation (ISCC) can meet the above system requirements and save spectrum resources. In this paper, we build a resource...

The synthetic control method (SCM) represents a notable innovation in estimating the causal effects of policy interventions and programs in a comparative case study setting. In this paper, we demonstrate that the data-driven approach to SCM requires solving a bilevel optimization problem. We show how the original SCM problem can be solved to the gl...

Satellite edge computing (SEC) has emerged as a promising technology to deliver network services to remote users. Coupled with software-defined networking (SDN) and network function virtualization (NFV), SEC can provide flexibility, agility, and efficiency when allocating computing and storage resources. However, there still remain a number of tech...

ABSTRACT The digital technology has transferred the whole world. Starting from the day-to-day activity almost all of the transactions, communications are happening in the digital format. These data that are communicated are also getting stored in a number of devices starting from sensors to mobile and other computing devices. These devices can be o...

With the development of autonomous driving technology, its applications permeate many aspects of work and life, providing convenience while reducing labor costs. Path planning has always been important for autonomous driving, where APF is widely used thanks to its simplicity of calculation and effectiveness. However, therere still problems existing...

The demand for high-performance computing (HPC) resources in computing fields such as machine learning has increased significantly in recent years. Computing power has been growing exponentially to keep up with this demand. However, these gains have not been able to translate to performance improvement in real-world applications. One of the biggest...

Mobility trajectory data is of great significance for mobility pattern study, urban computing, and city science. Self-driving, traffic prediction, environment estimation, and many other applications require large-scale mobility trajectory datasets. However, mobility trajectory data acquisition is challenging due to privacy concerns, commercial cons...

Magnetic skyrmions have emerged as promising elements for encoding information toward biomimetic computing applications due to their pseudoparticle nature and efficient coupling to spin currents. A key hindrance for skyrmionic devices is their instability against elongation at zero magnetic field (ZF). Prevailing materials approaches focused on tai...

Identifying influential nodes in multiplex complex networks have a critical importance to implement in viral marketing and other real-world information diffusion applications. However, selecting suitable influential spreaders in multiplex networks are more complex due to existing multiple layers. Each layer of multiplex networks has its particular...

The concept of parallelism of computations is very important to obtain the results required by the algorithms of big data processing applied in several domains, like ML, AI, neural networks, approximate computing, etc. In this chapter the use of and stations and of their respective generation/synchronization policies are described [12]. Three eleme...

There are several approaches to machine translation. The approaches can be roughly divided into two categories. The oldest approach is based on language analysis and linguistic rules for converting the text from one language to another. There are several varieties of this so-called rule-based approach. The second main approach includes the statisti...

Counting polynomials find their way into chemical graph theory through quantum chemistry in two ways: as approximate solutions to the Schrödinger equation or by storing information in a mathematical form and trying to find a pattern in the roots of these expressions. Coefficients count how many times a property occurs, and exponents express the ext...

Most of the supporting tools developed for logistic optimization and processing infrastructure planning are based on the network flow problem. The real-world application of these instruments can provide great insight and help to ensure long-term sustainability. The main limitation of these tools lies in great computing demand when there is the nece...

Sports is greatly valued both for its internal benefits (e.g., joy and fulfilment) and its external benefits (e.g., physical health). Still, many people struggle to find or uphold the motivation to practice sports. To ameliorate this issue, researchers in the field of SportsHCI have been actively exploring various gamification strategies. In this c...

Shoreline position is a key parameter of a beach state, often used as a descriptor of the response of the system to changes in external forcing, such as sea‐level rise. Changes in shoreline position are the result of coupled hydrodynamic and morphodynamic processes happening in the nearshore and acting at different temporal scales. Due to this comp...

INTRODUCTION: Eco-development is an essential national strategy, which has become an effective way to sustain China's tourism industry in the new era. Nowadays, the problem of climate change is becoming more and more serious, and the restriction on natural resources and the environment is becoming more and more serious. Improving the economic effic...

Microprocessor, the heart of modern technology, is a continuously growing field with newer ideas, designs and materials always being introduced. Since the first appearance of microprocessors, speed, transistor count and energy efficiency of microprocessors have increased exponentially. To keep pace with a competitive world that demands higher perfo...

We introduce quantum algorithms able to sample equilibrium water solvent molecules configurations within proteins thanks to analog quantum computing. To do so, we combine a quantum placement strategy to the 3D Reference Interaction Site Model (3D-RISM), an approach capable of predicting continuous solvent distributions. The intrinsic quantum nature...

Spin orbit torque (SOT) devices with the advantages of high speed, low power consumption, and high stability have wide application prospects in the field of spintronics. The SOT‐based crossbar array device is an important extension of SOT devices, but it is not reported so far. Here, the all electrical magnetization switching of Hall crossings base...

With the advent of the 21st century, the demand for computing power and numerical models has led to an integrative approach of using Machine Learning methods in physical sciences, specifically in Statistical Physics. The paper outlines the foundational principles of Statistical Physics and Machine Learning, bridging the gap between these discipline...

In neuromorphic computing, the coding method of spiking neurons serves as the foundation and is crucial for various aspects of network operation. Existing mainstream coding methods, such as rate coding and temporal coding, have different focuses, and each has its own advantages and limitations. This paper proposes a novel coding scheme called activ...

The need for new approaches for designing microprocessors are becoming more prominent day-by-day. Soon we are going to hit the theoretical limit of the performance of conventional CMOS technology. Fortunately, there are several emerging technologies on the rise that are showing the potential of surpassing the existing technologies. This article poi...

We present the final legacy version of stellar photometry for the Panchromatic Hubble Andromeda Treasury (PHAT) survey. We have reprocessed all of the Hubble Space Telescope Wide Field Camera 3 and Advanced Camera for Surveys near-ultraviolet (F275W, F336W), optical (F475W, F814W), and near-infrared (F110W, F160W) imaging from the PHAT survey using...

Plankton is critical for the structure and function of marine ecosystems. In the past three decades, various underwater imaging systems have been developed to collect in-situ plankton images and image processing has been a major bottleneck that hinders the deployment of plankton imaging systems. In recent years, deep learning methods have greatly e...

We introduce RobotPerf, a vendor-agnostic bench-marking suite designed to evaluate robotics computing performance across a diverse range of hardware platforms using ROS 2 as its common baseline. The suite encompasses ROS 2 packages covering the full robotics pipeline and integrates two distinct benchmarking approaches: black-box testing, which meas...

The core reasoning task for datalog engines is materialization, the evaluation of a datalog program over a database alongside its physical incorporation into the database itself. The de-facto method of computing is through the recursive application of inference rules. Due to it being a costly operation, it is a must for datalog engines to provide i...

The recognition of lane line type plays an important role in the perception of advanced driver assistance systems (ADAS). In actual vehicle driving on roads, there are a variety of lane line type and complex road conditions which present significant challenges to ADAS. To address this problem, this paper proposes an improved YOLOv5 method for recog...

The integration of robot activities with cloud computing and the internet of things is essential to Industry 4.0 implementation. In the chapter, the fundamental principles of cloud computing and integrated robotics are explained. Emergence, characteristics, service delivery models, and computing models of robot-cloud computing principles have been...

p>In this work we investigate the conductance quantization (QC or CQ) phenomenon in the Cu/Ta2O5/Pt resistive random access memory (RRAM) devices. The Ta2O5 film was deposited on Pt-Si substrate using RF magnetron sputtering, followed by patterning of Cu top electrodes. The devices demonstrate robust bipolar resistive switching behavior, with low s...

p>Fiducial tags have attracted increased attention and use in the robotics community due to their relative ease of detection and pose estimation. Previous methods to detect these tags search the image pixel spaces in their entirety. With the advent of higher resolution video such as 4K and increased camera frame rate, however, it has become increas...

p>Fiducial tags have attracted increased attention and use in the robotics community due to their relative ease of detection and pose estimation. Previous methods to detect these tags search the image pixel spaces in their entirety. With the advent of higher resolution video such as 4K and increased camera frame rate, however, it has become increas...

We are interested in numerical algorithms for computing the electrical field generated by a charge distribution localized on scale ℓ in an infinite heterogeneous correlated random medium, in a situation where the medium is only known in a box of diameter L ≫ ℓ around the support of the charge. We show that the algorithm of Lu, Otto and Wang, sugges...

The fusion of computing with textile materials has enhanced the interactive capabilities of textiles. Applying these electronic aspects of textile design is an evolving discipline. This study introduces a case study of teaching textile design in higher education with an interactive focus on art and design. We analysed projects and contents that app...

New Dates and Timings in Fall 2023: Seminars and Career Meetings (SACM) for the Statistical Analytics Computing and Modeling (SACM) Program

p>TinyRCE is a hyperspherical classifier aimed at Continual Learning On-Tiny-Devices, a challenging task in which a Machine Learning model is required to learn from continuous streams of data while being directly installed on a (tiny) device with limited computational resources. The classifier has so far been applied to several use cases, including...

p>In this work we investigate the conductance quantization (QC or CQ) phenomenon in the Cu/Ta2O5/Pt resistive random access memory (RRAM) devices. The Ta2O5 film was deposited on Pt-Si substrate using RF magnetron sputtering, followed by patterning of Cu top electrodes. The devices demonstrate robust bipolar resistive switching behavior, with low s...

This paper addresses the computation of the Fibonacci sequence with arbitrary precision, recognizing that while the Fibonacci sequence is straightforward from a mathematical perspective, its calculation encounters limitations when using a 64-bit environment, specifically above the 93 rd Fibonacci number. To overcome this limitation, we explore vari...

In recent decades, memory-intensive applications have experienced a boom, e.g., machine learning, natural language processing (NLP), and big data analytics. Such applications often experience out-of-memory (OOM) errors, which cause unexpected processes to exit without warning, resulting in negative effects on a system’s performance and stability. T...

Efficient logistics and transport at the port heavily relies on efficient AGV scheduling and planning for container transshipment. This paper presents a comprehensive approach to address the challenges in AGV path planning and coordination within the domain of intelligent transportation systems. We propose an enhanced graph search method for constr...

p>TinyRCE is a hyperspherical classifier aimed at Continual Learning On-Tiny-Devices, a challenging task in which a Machine Learning model is required to learn from continuous streams of data while being directly installed on a (tiny) device with limited computational resources. The classifier has so far been applied to several use cases, including...

We set up the theory for a distributed algorithm for computing persistent homology. For this purpose we develop linear algebra of persistence modules. We present bases of persistence modules, together with an operation ⊞\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{ams...

The presented article is dedicated to a new way of teaching substitution in algebra. In order to effectively master the subject matter, it is necessary for students to perceive the equal sign equivalently, to learn to manipulate expressions as objects, and to perceive and use transformations based on defining their own equivalences. According to th...

The creation and delivery of healthcare services are being transformed through patient-engaging digital services. However, their effects on hospital performance are unclear. We build on the theoretical foundations of resource dependency and environmental munificence to identify two characteristics of the hospital’s regional environment, the populat...

With the rapid development of the Internet-of-Things (IoT) and the continuous progress in software technologies, IoT devices (IoTDs) have been applied to various scenarios for executing computation-intensive applications. Limited by many restrictions, IoTDs usually cannot fully meet the demands of these applications. In this context, the mobile edg...

The two main features of the memristive devices which makes them the promising candidates for neuromorphic applications are low power consumption and CMOS compatibility. The monolithic integration of memristive devices with CMOS circuitry paves the way for in-memory computing. This chapter focuses on the factors governing the CMOS integration proce...

Cloud computing enables convenient, on-demand access to computing resources over the internet. While providing agility and cost savings, migrating to the cloud also introduces major security concerns that must be evaluated and mitigated appropriately. This extensive article examines the concept of enterprise cloud security, surveys key threats and...

Matrix factorization is a long-established method employed for analyzing and extracting valuable insight recommendations from complex networks containing user ratings. The execution time and computational resources demanded by these algorithms pose limitations when confronted with large datasets. Community detection algorithms play a crucial role i...

Explainable artificial intelligence has mainly focused on static learning scenarios so far. We are interested in dynamic scenarios where data is sampled progressively, and learning is done in an incremental rather than a batch mode. We seek efficient incremental algorithms for computing feature importance (FI). Permutation feature importance (PFI)...

Background: Augmented reality (AR) has emerged as a promising technology in educational settings owing to its engaging nature. However, apart from applications aimed at the autism spectrum disorder population, the potential of AR in social-emotional learning has received less attention. Objective: This scoping review aims to map the range of AR ap...

Neuromorphic computing is a promising strategy to overcome fundamental limitations, such as enormous power consumption, by massive parallel data processing, similar to the brain. Here we demonstrate a proof-of-principle implementation of the weighted spin torque nano-oscillator (WSTNO) as a programmable building block for the next-generation neurom...

Deep Neural Networks (DNNs) have drawn attention because of their outstanding performance on various tasks. However, deploying full-fledged DNNs in resource-constrained devices (edge, mobile, IoT) is difficult due to their large size. To overcome the issue, various approaches are considered, like offloading part of the computation to the cloud for...

NeighborNet constructs phylogenetic networks to visualize distance data. It is a popular method used in a wide range of applications. While several studies have investigated its mathematical features, here we focus on computational aspects. The algorithm operates in three steps. We present a new simplified formulation of the first step, which aims...

In mobile edge computing (MEC), accurately predicting and monitoring the energy consumption of edge servers is a key challenge in achieving green computing. The importance of solving this problem is that it can help optimize the energy usage in data centers and thus reduce the carbon emission of MEC. To this end, we propose an innovative entropy‐ba...

In a memristor or a so-called memristive device, the resistance state depends on the previous charge flow through the device. The new resistance state is stored and classifies a memristor as a non-volatile memory device. This likewise unique and simple feature qualifies memristive devices as attractive compartments with regard to the development of...