Computer Hardware - Science topic

International Conference on Computer Systems and Technologies CompSysTech'25 - 27-28 June 2025, University of Ruse, Bulgaria Call for Papers: The International CompSysTech'25 Conference will take placeat the University of Ruse, Bulgaria. CompSysTech'25 papers will be published in IEEE Xplore and indexed in Scopus. The paper submission deadline is 9...

We develop a method for computing Bayes' factors of conceptual rainfall–runoff models based on thermodynamic integration, gradient-based replica-exchange Markov chain Monte Carlo algorithms and modern differentiable programming languages. We apply our approach to the problem of choosing from a set of conceptual bucket-type models with increasing dy...

Recently, a new frontier in computing has emerged with physical neural networks(PNNs) harnessing intrinsic physical processes for learning. Here, we explore topological mechanical neural networks(TMNNs) inspired by the quantum spin Hall effect(QSHE) in topological metamaterials, for machine learning classification tasks. TMNNs utilize pseudospin st...

VTX is an open-source molecular visualization software designed to overcome the scaling limitations of existing real-time molecular visualization software when handling massive molecular datasets. VTX employs a meshless molecular graphics engine utilizing impostor-based techniques and adaptive level-of-detail (LOD) rendering. This approach signific...

Introduction Volumetric video production in commercial studios is predominantly produced using a multi-view stereo process that relies on a high two-digit number of cameras to capture a scene. Due to the hardware requirements and associated processing costs, this workflow is resource-intensive and expensive, making it unattainable for creators and...

Non‐volatile memory (NVM) based neuromorphic computing, which is inspired by the human brain, is a compelling paradigm in regard to building energy‐efficient computing hardware that is tailored for artificial intelligence. However, the current state of the art NVMs are facing challenges with low operating voltages, energy efficiencies, and high den...

The mathematical complexity and high dimensionality of neural networks hinder the training and deployment of machine learning (ML) systems while also requiring substantial computational resources. This fundamental limitation drives ML research, particularly in the exploration of alternative neural network architectures that integrate novel building...

The rapid advancement of artificial intelligence (AI) technologies has significantly increased the demand for high-performance computational hardware. Memristor-based compute-in-memory (CIM) technology, also known as resistive random-access memory (RRAM)-based CIM technology, shows great potential for addressing the data transfer bottleneck and sup...

The explosive growth in computational demands of artificial neural networks has spurred research into optical neural networks. However, most existing work overlooks the co-design of software and hardware, resulting in challenges with data encoding and nonlinear activation in optical neural networks, failing to fully leverage the potential of optica...

In‐sensor computing hardware with signal sensing and dynamic signal processing capabilities—inspired by the human sensory system—have attracted interest as the rapid proliferation of data sensing and computation in the era of big data. Here, an in‐sensor reservoir computing (RC) system with integrated functions of signal sensing, preprocessing, and...

Methods of artificial intelligence (AI) and especially machine learning (ML) have been growing ever more complex, and at the same time have more and more impact on people’s lives. This leads to explainable AI (XAI) manifesting itself as an important research field that helps humans to better comprehend ML systems. In parallel, quantum machine learn...

We present the Virtual Quantum Device (VQD) platform, a system based on the QuEST quantum emulator. Through the use of VQDs, non-expert users can emulate specific quantum computers with detailed error models, bespoke gate sets and connectivities. The platform boasts an intuitive interface, powerful visualisation, and compatibility with high-perform...

Memristive devices based on two-dimensional (2D) materials have emerged as potential synaptic candidates for next-generation neuromorphic computing hardware. Here, we introduce a numerical modeling framework that facilitates efficient exploration of the large parameter space for 2D memristive synaptic devices. High-throughput charge-transport simul...

The evolution of molecular dynamics (MD) simulations has been intimately linked to that of computing hardware. For decades following the creation of MD, simulations have improved with computing power along the three principal dimensions of accuracy, atom count (spatial scale), and duration (temporal scale). Since the mid-2000s, computer platforms h...

Customized digital backends for Very Long Baseline Interferometry (VLBI) are critical components for radio astronomy observatories. There are several serialized products such as the Digital Baseband Converter (DBBC), Reconfigurable Open Architecture Computing Hardware (ROACH) Digital BackEnd (RDBE), and Chinese Data Acquisition System (CDAS). Howev...

A novel high-fidelity FEM modeling approach is developed to simulate the micro-motion in the main bearing assembly of a wind turbine (WT) drive train. This model will not only simulate the rolling bearing itself but also the stiffness of the neighboring structure, as this is mandatory to simulate the ring migration effect realistically. Due to the...

Quantum social science provides a novel theoretical and methodological framework for addressing the complexities of future urban governance. This study explores the applications of quantum probability, quantum measurement effects, quantum game theory, and quantum computing in optimizing decision-making, enhancing policy simulations, and improving u...

Upon the advent of the big data era, information processing hardware platforms have undergone explosive development, facilitating unprecedented computational capabilities while significantly reducing energy consumption. However, conventional electronic computing hardware, despite significant upgrades in architecture optimization and chip scaling, s...

The world obeys quantum physics and quantum computing presents an alternative way to map physical problems to systems that follow the same laws. Such computation fundamentally constitutes a better way to understand the most challenging quantum problems. One such problem is the accurate simulation of highly correlated quantum systems. Still, modern-...

This study presents the first implementation of multilayer neural networks on a memristor/complementary metal‐oxide‐semiconductor (CMOS)‐integrated system‐on‐chip (SoC) to simultaneously detect multiple diseases. To overcome limitations in medical data, generative artificial intelligence techniques are used to enhance the dataset, improving the cla...

The precipitous rise of consumer network applications reiterates the urgency to redefine computing hardware with a low power footprint. Neuromorphic computing utilizing correlated oxides offers an energy‐efficient solution. By designing anisotropic functional properties in LSMO on a twinned LAO substrate and driving it out of thermodynamic equilibr...

As one of the data‐intensive in‐memory computing hardware, ternary content addressable memory (TCAM) stands out for its efficient in‐memory‐searching capability, enabling high‐throughput and low‐latency computing. However, TCAMs, especially those based on resistive non‐volatile memories, face challenges in limited resistance ratio (Rhigh/Rlow) that...

Virtual Reality (VR) is a disruptive technology rapidly advancing as computing hardware and software are getting better and cheaper. This chapter attempts to apprise the scholarly community with five futuristic trends that will shape VR. Immersive Social Experiences with Virtual Reality will make social interaction even better. They allow dynamic a...

Quadratic Programs (QPs) are widely used in the control of walking robots, especially in Model Predictive Control (MPC) and Whole-Body Control (WBC). In both cases, the controller design requires the formulation of a QP and the selection of a suitable QP solver, both requiring considerable time and expertise. While computational performance benchma...

There has been tremendous progress in the physical realization of quantum computing hardware in recent times, bringing us closer than ever before to realizing the promise of quantum computing. However, noise continues to pose a crucial challenge when it comes to scaling up present day quantum processors. While decoherence limits the qubits ability...

The precipitous rise of consumer network applications reiterates the urgency to redefine computing hardware with low power footprint. Neuromorphic computing utilizing correlated oxides offers an energy-efficient solution. By designing anisotropic functional properties in LSMO on a twinned LAO substrate and driving it out of thermodynamic equilibriu...

Advanced computational chemistry software packages have transformed chemical research by leveraging quantum chemistry and molecular simulations. Despite their capabilities, the complicated design and the requirement for specialized computing hardware hinder their applications in the broad chemistry community. Here, we introduce AutoSolvateWeb, a ch...

The rapid development of deep learning enables significant breakthroughs for intelligent edge‐terminal devices. However, neural network training for edge computing is currently overly dependent on cloud service platforms, resulting in low adaptivity for fast‐changing real‐world environments. The training energy efficiency is also strictly constrain...

Concrete surface crack detection and maintenance are crucial for ensuring structural safety. Deep learning-based techniques for detecting concrete cracks have become popular due to the quick advancement of artificial intelligence. However, the actual uses of these methods are limited due to issues like large model sizes and significant dependence o...

Spintronic oscillators being highly nonlinear have gained immense attention to mimic the neuron spiking behavior in spiking neural networks used for building neuromorphic computing hardware. However, the need for an external magnetic field to realize spintronic oscillators imposes significant limitations on their scalability, tunability, and fabric...

On-chip computing metasystems composed of multilayer metamaterials have the potential to become the next-generation computing hardware endowed with light-speed processing ability and low power consumption but are hindered by current design paradigms. To date, neither numerical nor analytical methods can balance efficiency and accuracy of the design...

We propose a duality between thermodynamics and computational complexity, elevating the difficulty of a computational task to the status of a thermodynamic variable. By introducing a complexity measure C as a novel coordinate, we formulate an extended first law, dU = T dS - p dV + ... + lambda dC, capturing energy costs beyond classical bit erasure...

The success of deep learning has sparked significant interest in designing computer hardware optimized for the high computational demands of neural network inference. As further miniaturization of digital CMOS processors becomes increasingly challenging, alternative computing paradigms, such as analog computing, are gaining consideration. Particula...

Audio signal decomposition breaks a mixture of musical instrument audio signals into its fundamental musical instrument components. Machine learning is one of the methods widely used in audio signal decomposition. However, the limitation of computer hardware and the complexity of the algorithm may cause the computational speed of machine learning t...

Highly entangled quantum states are an ingredient in numerous applications in quantum computing. However, preparing these highly entangled quantum states on currently available quantum computers at high fidelity is limited by ubiquitous errors. Besides improving the underlying technology of a quantum computer, the scale and fidelity of these entang...

This study aimed to develop a learning video on computer hardware material at SMP Negeri 8 Jangkang using the ADDIE development method. This study involved 32 grade VII students as test subjects and six validators consisting of material, design, and media experts. Qualitative and quantitative data analysis showed that the developed learning video h...

The emergence of 5G and edge computing hardware has brought about a significant shift in artificial intelligence, with edge AI becoming a crucial technology for enabling intelligent applications. With the growing amount of data generated and stored on edge devices, deploying AI models for local processing and inference has become increasingly neces...

Structured light adjusts optical trapping forces through flexible structure design. However, it is challenging to evaluate optical forces on microscopic particles in structured light due to high computational hardware requirements, prolonged computation times, and data inefficiencies associated with solving optical trapping forces using generalized...

One particularly intriguing object in superconductivity is the Josephson junction, which is an integral part of quantum computer hardware. Analysing this object requires solving differential equations. Such problems often cannot be solved with analytical methods; therefore, numerical methods and computational mathematics must be utilized. This arti...

Lightweight container technology has emerged as a fundamental component of cloud-native computing, with the deployment of containers and the balancing of loads on virtual machines representing significant challenges. This paper presents an optimization strategy for container deployment that consists of two stages: coarse-grained and fine-grained lo...

Reverse logistics, particularly in the realm of computer product returns, has become a critical factor in modern business operations. With the rapid expansion of e-commerce, businesses must navigate the complexities of return policies to maintain both customer satisfaction and operational efficiency. This study examines the impact of consumer satis...

Reverse logistics, particularly in the realm of computer product returns, has become a critical factor in modern business operations. With the rapid expansion of e-commerce, businesses must navigate the complexities of return policies to maintain both customer satisfaction and operational efficiency. This study examines the impact of consumer satis...

The loads that have several working states cannot be accurately distinguished by the conventional Non-Intrusive Load Monitoring (NILM) methods. This paper proposed an improved NILM method based on the Resnet18 Convolutional Neural Network (CNN) and Support Vector Machine (SVM) algorithm to address the misidentification of multi-state appliances. Th...

Nanoparticle superlattices consisting of ordered arrangements of nanoparticles exhibit unique optical, magnetic, and electronic properties arising from nanoparticle characteristics as well as their collective behaviors. Understanding how processing conditions influence the nanoscale arrangement and microstructure is critical for engineering materia...

We investigate the interaction of a transmon qubit with a classical gravitational field. Exploiting the generic phenomena of the gravitational redshift and Aharonov-Bohm phase, we show that entangled quantum states dephase with a universal rate. The gravitational phase shift is expressed in terms of a quantum computing noise channel. We give a meas...

Alternative computing paradigms open the door to exploiting recent innovations in computational hardware to probe the fundamental thermodynamic limits of information processing. One such paradigm employs superconducting quantum interference devices (SQUIDs) to execute classical computations. This, though, requires constructing sufficiently complex...

The emergence of 5G and edge computing hardware has brought about a significant shift in artificial intelligence, with edge AI becoming a crucial technology for enabling intelligent applications. With the growing amount of data generated and stored on edge devices, deploying AI models for local processing and inference has become increasingly neces...

An operating system (OS) is a software program that manages computer hardware and software resources, and provides common services for computer programs. The OS acts as an intermediary between the computer hardware and the software applications, allowing them to communicate with each other and perform their respective functions. Operating systems a...

The process of cultivating soil for crop planting and domesticating animals is known as agriculture. A growing agriculture sector indicates an improving economy. Agriculture is considered as the initial pillar that supports global food safety. Additionally, it controls the majority of the global economy. Since we depend on agriculture for survival,...

The burgeoning volume of parameters in artificial neural network models has posed substantial challenges to conventional tensor computing hardware. Benefiting from the available optical multidimensional information entropy, optical intelligent computing is used as an alternative solution to address the emerging challenges of electrical computing. T...

AncestryHub is a web version of local ancestry analysis software. It contains four built-in software and a set of built-in population reference panels. AncestryHub will significantly reduce the efforts and requirements for the users on their personal computational skills and computational hardware environment for ancestry analysis. Availability ht...

Complex-valued neural networks process both amplitude and phase information, in contrast to conventional artificial neural networks, achieving additive capabilities in recognizing phase-sensitive data inherent in wave-related phenomena. The ever-increasing data capacity and network scale place substantial demands on underlying computing hardware. I...

Operating systems are designed to manage a computer's hardware and software resources. As technology is getting developed day by day, the management of resources and the memory optimization are very important for computing to solve real-world problems has become essential. Over time, advanced researchers continue to study big problems to find solut...

Quantum computers have made significant progress in the last two decades showing great potential in tackling some of the most challenging problems in computing. This ongoing progress creates an opportunity to implement and evaluate quantum-inspired metaheuristics on real quantum devices, with the aim of uncovering potential computational advantages...

The study sought to establish the kind of computer prior knowledge (CPK) students in a teacher training collegepossessed before enrolling with college. It also analyzed the differences in students’ cognitive and affectiveoutputs in their computer studies between students with CPK and those without it. Participants were 168 studentsfrom a teachers’...

Computer software has come to replace the manual form of designing in both architectural education and practice. The use of drawing boards had been employed in architectural education and practice for a long time. Since the first half of the twentieth century, computer hardware and corresponding software have seen dramatic change and development ma...

Interest in digital image processing methods stems from two principal application areas: improvement of pictorial information for human interpretation; and processing of image data for storage, transmission, and representation for autonomous machine perception. Computer digital image technology is a very important branch of the computer application...

Processing long temporal sequences is a key challenge in deep learning. In recent years, Transformers have become state-of-the-art for this task, but suffer from excessive memory requirements due to the need to explicitly store the sequences. To address this issue, structured state-space sequential (S4) models recently emerged, offering a fixed mem...

Training in introducing computer basics is one of the trainings that students can develop because the acquisition of excess competencies from this training is quite promising. If students, after becoming alumni, can develop these competencies, it will be very profitable. Partners in this PKM activity are students from MTs Pembangunan Nurul Islam, S...

The explosive demand for artificial intelligence (AI) workloads has led to a significant increase in silicon area dedicated to lower-precision computations on recent high-performance computing hardware designs. However, mixed-precision capabilities, which can achieve performance improvements of 8x compared to double-precision in extreme compute-int...

This study explores a novel facial expression-based interaction method designed to provide an accessible and hands-free alternative for performing precision tasks. Traditional input devices, such as keyboards and mice, are often unsuitable for individuals with limited mobility or for hands-free environments. The proposed system leverages standard c...

Labeling data is a time-consuming, labor-intensive and costly procedure for many artificial intelligence tasks. Deep Bayesian active learning (DBAL) boosts labeling efficiency exponentially, substantially reducing costs. However, DBAL demands high-bandwidth data transfer and probabilistic computing, posing great challenges for conventional determin...

Researchers and practitioners are increasingly interested in the application of artificial intelligence (AI) to drive advancements in the pharmaceutical sector and elevate it to the required level. The pharmaceutical sector is significantly impacted by drug research and discovery, which also has an impact on several human health problems. AI has be...

With the advancements in high-definition imaging and parallel computing hardware, the analysis of massive visual data has become a key focus in pattern recognition and artificial intelligence. Chinese calligraphy, an integral part of traditional culture, has seen digitization of numerous works stored in digital libraries. However, current automatic...

This study aimed to revise the Bachelor of Technical-Vocational Teacher Education (BTVTEd) Program at Mariano Marcos State University to meet changing societal and educational needs. Using a research and development approach, the study included document analysis, focus group discussions with key stakeholders, and validation by curriculum experts. T...

This work focuses on the numerical study of a recently published class of Runge-Kutta methods designed for mixed-precision arithmetic. We employ the methods in solving partial differential equations on modern hardware. In particular we investigate what speedups are achievable by the use of mixed precision and the dependence of the methods algorithm...

Probabilistic computing (p‐computing) is a customized approach for solving complex combinatorial optimization problems. However, issues of compatibility with well‐established complementary metal‐oxide‐semiconductor (CMOS) technology, robustness to environmental temperature variations and stochasticity need to be addressed. This study resolves these...

In response to evolving societal needs and educational goals, this study aimed to revise the Bachelor of Technical-Vocational Teacher Education (BTVTEd) Program at Mariano Marcos State University. Utilizing a research and development framework, the study incorporated document analysis, focus group discussions with selected stakeholders, and validat...

We present a novel architecture for quantum computing hardware that implements error correction through geometric properties of the physical system rather than through software-based protocols. By encoding quantum information in the topological and geometric degrees of freedom of a carefully engineered Hamiltonian system, we demonstrate that quantu...

Antibodies play critical roles in modern medicine, serving as diagnostics and therapeutics for various diseases due to their ability to specifically bind to target antigens. Traditional antibody discovery and optimization methods are time-consuming and resource-intensive, though they have successfully generated antibodies for diagnosing and treatin...

As quantum computing hardware becomes more complex with ongoing design innovations and growing capabilities, the quantum computing community needs increasingly powerful techniques for fabrication failure root-cause analysis. This is especially true for trapped-ion quantum computing. As trapped-ion quantum computing aims to scale to thousands of ion...

Thin film ferroelectric devices with ultralow power operation, non-volatile data retention and fast and reliable switching are attractive for non-volatile memory and as synaptic weight elements. However, low thermal budget ferroelectric oxides suffer from crystalline inhomogeneity and defects that makes their large-scale circuit integration challen...

This research is intended to create and develop interactive multimedia-based desktop application products that are effective and have advantages for use in learning to introduce computer hardware in PGMI study programs, and evaluate the benefits of these products in improving PGMI student learning outcomes. The development process of this research...

Photogrammetry is a significant tool museums utilize to produce high-quality 3D models for research and exhibit content. As advancements in computer hardware and software continue, it is crucial to assess the effectiveness of photogrammetry software in producing research-quality 3D models. This study evaluates the efficacy of Apple’s Object Capture...

Photonic technologies hold significant potential for creating innovative, high-speed, efficient and hardware-friendly neuromorphic computing platforms. Neuromorphic photonic methods leveraging ubiquitous, technologically mature and cost-effective Vertical-Cavity Surface Emitting Lasers (VCSELs) are of notable interest. VCSELs have demonstrated the...

Finding optimal solutions to combinatorial optimization problems is pivotal in both scientific and technological domains, within academic research and industrial applications. A considerable amount of effort has been invested in the development of accelerated methods that leverage sophisticated models and harness the power of advanced computational...

As the demand for precise predictions grows across various industries due to advancements in sensor technology and computer hardware, multi-feature time series prediction shows significant promise in fields such as information fusion, finance, energy, and meteorology. However, traditional machine learning methods often struggle to forecast future e...

Currently, data-intensive scientific applications require vast amounts of compute resources to deliver world-leading science. The climate emergency has made it clear that unlimited use of resources (e.g., energy) for scientific discovery is no longer acceptable. Future computing hardware promises to be much more energy efficient, but without better...

In order to characterize and benchmark computational hardware, software, and algorithms, it is essential to have many problem instances on-hand. This is no less true for quantum computation, where a large collection of real-world problem instances would allow for benchmarking studies that in turn help to improve both algorithms and hardware designs...

The co‐integration of logic, memory, synapse, and other essential functionalities into one single element with run‐time reconfigurability is explored as a promising approach for an efficient and flexible in‐memory computing platform. However, despite ample research focused on such reconfigurable semiconductor technology, it remains challenging to a...

Memristor is an emerging electronic component, tremendous efforts have been made in the fields of memristor, motivated by its unique resistor switching feature, as well as the good compatibility with the current integrated circuit (IC) technologies. It has been widely accepted that memristor would be a powerful candidate for constructing the brain-...