Computer Memory - Science topic

Despite the advantages of the plastic limit analysis of structures, this robust method suffers from some drawbacks such as intense computational cost. Through two recent decades, metaheuristic algorithms have improved the performance of plastic limit analysis, especially in structural problems. Additionally, graph theoretical algorithms have decrea...

Mathematics is the most logical and unbiased scientific field there is. What is true in mathematics today will forever stay true, and mathematical arguments will always clearly indicate which side “wins”. These are some of the characteristics of mathematics that I have liked very much since I was young. In this article, I will try to demonstrate th...

In this paper, a new high-performance and memory-efficient contact and road model is developed. Specifically, the road is modeled as a rectangular structured grid of deformable springs in the vertical direction, thus enabling fast execution. The new road model stands out due to its ability to handle large road scenarios by allocating computer memor...

Based on three-dimensional optical proximity correction (3D OPC), recent advancements in 3D lithography have enabled the high-fidelity customization of 3D micro-optical elements. However, micron-to-millimeter scale structures represented by Fresnel lens design bring more stringent requirements for 3D OPC, which poses significant challenges to the a...

Abstract. To overcome the negative effects of environment pollution by chemicals and for their prevention we had invented and constructed original information system “EcoIS” for detecting and monitoring of harmful and toxic substances effects on biological organisms. Four functional sectors were developed in “EcoIS” which registered effects of harm...

Analysis of microbial data from archaeological samples is a growing field with great potential for understanding ancient environments, lifestyles, and diseases. However, high error rates have been a challenge in ancient metagenomics, and the availability of computational frameworks that meet the demands of the field is limited. Here, we propose aMe...

Hameroff-Penrose engage Mesgarani linguistics by humanizing a sub-neuronal helical solution for what is “little understood” as “phonetic feature encoding.” Orch OR microtubulin (MT) computation potentiates Watson–Crick 1953 helx information storage as 1957 Bell Lab twistor memory, a system in which many messages pass simultaneously” substantiating...

Finite Element codes used for solving the mechanical equilibrium equations in transient problems associated to (time-dependent) viscoelastic media generally relies on time-discretized versions of the selected constitutive law. Recent concerns about the use of non-integer differential equations to describe viscoelasticity or well-founded ideas based...

Despite the remarkable progress in the video generation field, generating videos of longer-term remains challenging due to the challenge of sustaining the temporal consistency and continuity in the resulting synthesized movement while ensuring realism. In this paper, we propose a recall mechanism for enabling an encoder-empowered short-term video g...

This research addresses the issue of evaluating CPU rendering performance by introducing the innovative benchmark test suite construction method RenderBench. This method combines CPU microarchitecture features with rendering task characteristics to comprehensively assess CPU performance across various rendering tasks. Adhering to principles of repr...

In this this paper for the first time, we have formulated the dotriacontal number system using existing number systems like binary, and hexadecimal numbers. The dotriacontal number is one with a base of 32, containing 32 single-character digits or symbols. Each symbol contains five binary digits. This number system can be used in computers for redu...

The electronics market is highly competitive and driven by consumers desire for the latest and most sophisticated devices at the lowest cost. In the last decade there has been increasing interest in printing electronic materials on lightweight and flexible substrates such as plastics and fabrics. This not only lowers fabrication and capital costs b...

Objectives Synthetic data reproduces features of a dataset without disclosing sensitive information, allowing researchers to explore data structures and test code without requiring access to real, potentially sensitive, data. We produced a low-fidelity synthetic data generation tool, accompanied by extensive documentation, allowing novice and exper...

Background Mitochondria are the cell organelles that produce most of the chemical energy required to power the cell's biochemical reactions. Despite being a part of a eukaryotic host cell, the mitochondria contain a separate genome whose origin is linked with the endosymbiosis of a prokaryotic cell by the host cell and encode independent genomic in...

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can provide computing capabilities as part of the memory array structures (In-Memory Computing, IM...

The importance of information technology in the fight against crime cannot be overestimated in the modern world. It is the use of computer software and appropriate technical means that have become the most effective measures to neutralize and eradicate offenses in practice. Of particular importance are analytical information systems, which can allo...

Personalized PageRank (PPR) is a widely used graph processing algorithm used to calculate the importance of source nodes in a graph. Generally, PPR is executed by using a high-performance microprocessor of a server, but it needs to be executed on edge devices to guarantee data privacy and network latency. However, since PPR has a variety of computa...

Simulation speed matters for neuroscientific research: this includes not only how quickly the simulated model time of a large-scale spiking neuronal network progresses but also how long it takes to instantiate the network model in computer memory. On the hardware side, acceleration via highly parallel GPUs is being increasingly utilized. On the sof...

This study addresses the issues of the limited or unavailable unmanned aerial vehicle (UAV) image matching labels, differences in imagery between UAV and ground cameras, and the limited UAV airborne computer memory in UAV visual navigation. To tackle these challenges, a novel unsupervised UAV image matching network called USuperGlue is developed, w...

p>This paper proposes a global positioning system (GPS)-aided visual simultaneous localization and mapping (SLAM) called GO-SLAM for adaptive UAV navigation. The proposed system offers a solution by the method to address the adaptive navigation challenge, wherein the navigation path needs to pass through an indoor area or outdoor area. GO-SLAM reli...

p>This paper proposes a global positioning system (GPS)-aided visual simultaneous localization and mapping (SLAM) called GO-SLAM for adaptive UAV navigation. The proposed system offers a solution by the method to address the adaptive navigation challenge, wherein the navigation path needs to pass through an indoor area or outdoor area. GO-SLAM reli...

The utilization of unmanned aerial vehicles (UAVs) for the precise and convenient detection of litchi fruits, in order to estimate yields and perform statistical analysis, holds significant value in the complex and variable litchi orchard environment. Currently, litchi yield estimation relies predominantly on manual rough counts, which often result...

One-dimensional nanostructures are generally cited as nanowires, nanofibers, nanotubes, and so on. The foremost prominent feature of these materials is their electrical conductivity, which, unlike classical physics, doesn't increase their resistance because the diameter decreases. Numerous properties of these materials like electrical conductivity,...

It remains a challenge for discrete element method to simulate large-scale systems with arbitrarily shaped particles. This paper presents a novel approach called Ray Tracing Discrete Element Method (RTDEM) to offer ultra-high efficiency in simulating particles with arbitrary shapes. In RTDEM, we use a triangular mesh to represent the surface of a p...

This paper introduces a new approach for examining and analyzing fileless malware artifacts in computer memory. The proposed approach offers the distinct advantage of conducting a comprehensive live analysis of memory without the need for periodic memory dumping. Once a new process arrives, log files are collected by monitoring the Event Tracing fo...

Reverse-time migration (RTM) is a well-established imaging technique that utilizes the two-way wave equation to achieve high-resolution imaging of complex subsurface media. However, when using RTM for reverse time extrapolation, a source wavefield needs to be stored for cross-correlation with the backward wavefield. This requirement results in a si...

Original computerized information system “EcoIS” for monitoring of influences of harmful and toxic substances on biological organisms was developed. It unites four sectors with possibilities of information registration in different time intervals after the influence of harmful substances – from “0” (the first moments) after the harmful substance at...

Original computerized information system “EcoIS” for monitoring of influences of harmful and toxic substances on biological organisms was developed. It unites four sectors with possibilities of information registration in different time intervals after the influence of harmful substances – from “0” (the first moments) after the harmful substance at...

A new method of representing graph projections in computer memory is proposed, which is more informative than matrix and list data structures based on elementary relations of vertices adjacency or edge incidences. The class of graphs considered in this study is expanded to include mixed graphs containing both undirected and directed edges (arcs). A...

Resumen. Desde su introducción en 2015 por Courbariaux, las redes neuronales binarias han surgido como una alternativa prometedora para reducir los grandes requisitos de cómputo, memoria y almacenamiento en modelos de aprendizaje profundo, permitiendo su implementación en dispositivos con recursos limitados, como los utilizados en el cómputo de fro...

Deep neural networks (DNNs) are state-of-the-art techniques for solving most computer vision problems. DNNs require billions of parameters and operations to achieve state-of-the-art results. This requirement makes DNNs extremely compute, memory, and energy-hungry, and consequently difficult to deploy on small battery-powered Internet-of-Things (IoT...

We predict steady-state Stokes flow of fluids within porous media at pore scales using sparse point observations and a novel class of physics-informed neural networks, called "physics-informed PointNet" (PIPN). Taking the advantages of PIPN into account, three new features become available compared to physics-informed convolutional neural networks...

Tuberculosis is a global pandemic disease with a rising burden of antimicrobial resistance. As a result, the World Health Organization (WHO) has a goal of enabling universal access to drug susceptibility testing (DST). Given the slowness of and infrastructure requirements for phenotypic DST, whole-genome sequencing, followed by genotype-based predi...

For the autonomous operation of an Unmanned system, it is necessary to develop a mathematical model of the atmospheric environment and relief over which the flight will be carried out. The presented material shows the principles for synthesizing such an environment. Atmospheric turbulence is included in the simulations, and terrain topography is se...

Genetic algorithms, a stochastic research method, are Darwin’s “survival of the best.” Development of biological systems based on the principle of “survival of the fittest” emerged with the adaptation of the process to the computer environment. In genetic algorithms, processes executed are stored in computer memory similar to natural populations pe...

Simulator use cases are pushing the limits of the current technology in network fabrics with regard to bandwidth and latency across their infrastructure deployments. Many leading technology companies (HP, Intel) have suggested that the network is the bottleneck for performance and that a new network fabric for the compute environment can help solve...

Although deep-learning based video super-resolution (VSR) studies have achieved excellent progress in recent years, the majority of them do not take into account the impact of lossy compression. A large number of real-world videos are characterized by compression artifacts (e.g., blocking, ringing, and blurring) due to transmission bandwidth or sto...

Deep neural networks (DNNs) are computationally/memory-intensive and vulnerable to adversarial attacks, making them prohibitive in some real-world applications. By converting dense models into sparse ones, pruning appears to be a promising solution to reducing the computation/memory cost. This paper studies classification models, especially DNN-bas...

Seismic oceanography can provide a two- or three-dimensional view of the water column thermocline structure at a vertical and horizontal resolution from the multi-channel seismic dataset. Several seismic imaging methods and techniques for seismic oceanography have been presented in previous research. In this study, we suggest a new formulation of t...

Within the framework of this article, an analysis of the dynamics of the growth of information security incidents identified in companies by specialists of the department of monitoring and responding to information security threats was carried out. The study examined the problems faced by information security specialists in companies, and what tool...

The widespread use of maximum Jeffreys'-prior penalized likelihood in binomial-response generalized linear models, and in logistic regression, in particular, are supported by the results of Kosmidis and Firth (2021, Biometrika), who show that the resulting estimates are also always finite-valued, even in cases where the maximum likelihood estimates...

The principal constituent of a block cipher in symmetric-key cryptography is the Boolean function, determining the substitution box (S-box). Block ciphers rely totally on S-boxes with excellent nonlinearity and upright cryptographic structures. In AES, an 8 × 8 S-box is a 16 × 16 lookup table over the Galois field GF 2 8 , that occupies 8 × 2 8 byt...

An operating system (OS) is a software program that acts as an intermediary between the computer hardware and the user or application software. It provides a platform for running and managing computer programs, coordinating system resources, and facilitating communication between software and hardware components. The primary functions of an operati...

Various components are involved in the end-to-end path of data transfer. Protecting data integrity from failures in these intermediate components is a key feature of big data transfer tools. Although most of these components provide some degree of data integrity, they are either too expensive or inefficient in recovering corrupted data. This proble...

In this study, we coupled the one-step simplified lattice Boltzmann method (OSLBM) [1] with flexible forcing immersed boundary (FFIB) scheme [2] and proposed a computationally efficient FFIB-OSLBM solver for complex two-dimensional fluid-solid interaction problems. The adopted OSLBM algorithm has the benefits of lower virtual memory requirement and...

Genetic analysis using big data can enhance the power of GWAS, but large data sets often have a large number of missing phenotypes. The UK Biobank database contains ∼500,000 individuals with ∼3,000 phenotypes, with phenotype missing rates ranging from 0.11% to 98.35%. Imputation of missing phenotypes is an important way of improving the GWAS power....

Cartesian Cell Registration (CCR) is an effective method to reduce computational time for particle search and positioning, for example, in the Direct Simulation Monte Carlo (DSMC) method for dilute fluid flows and multiphase flow calculations. In this chapter, an efficient FORTRAN algorithm for the CCR method is presented to further reduce both the...

Neural operators have proven to be a promising approach for modeling spatiotemporal systems in the physical sciences. However, training these models for large systems can be quite challenging as they incur significant computational and memory expense -- these systems are often forced to rely on autoregressive time-stepping of the neural network to...

Simulation speed matters for neuroscientific research: this includes not only how quickly the simulated model time of a large-scale spiking neuronal network progresses, but also how long it takes to instantiate the network model in computer memory. On the hardware side, acceleration via highly parallel GPUs is being increasingly utilized. On the so...

Most machine learning proposals in the Internet of Things (IoT) are designed and evaluated on pre-processed datasets, where data acquisition and cleaning steps are often considered a black box. In addition, IoT environments have numerous challenges related to acquiring data from sensors, where sensitive data can be threatened by malicious users who...

The development of the agricultural economy is hindered by various pest-related problems. Most pest detection studies only focus on a single pest category, which is not suitable for practical application scenarios. This paper presents a deep learning algorithm based on YOLOv5, which aims to assist agricultural workers in efficiently diagnosing info...

Accurate, rapid, and smart pest recognition and detection are important for crop protection and management. Existing deep learning-based pest detection algorithms often require high computing resources and computational memory. In addition, detection of small and high-density pests (e.g., sugarcane aphids (SCAs)) in un-structured natural environmen...

The application of the security region methodology in a practical distribution system with large scale normally requires large computer memory and high computation time. To overcome this problem, this article proposes a decoupling and dimension reduction method, which can significantly accelerate the calculation of distribution system security regi...

Memory acquisition process is one of digital forensics act. There are several tools that support memory acquisition process. At this time, there is a feature named secure mode that can caused crash or error in memory acquisition tools system and caused the tools to be unusable, also the loss of the computer memory. This research is focusing on anal...

Data-driven medium-range weather forecasting has attracted much attention in recent years. However, the forecasting accuracy at high resolution is unsatisfactory currently. Pursuing high-resolution and high-quality weather forecasting, we develop a data-driven model SwinRDM which integrates an improved version of SwinRNN with a diffusion model. Swi...

A load flow program is developed using MATLAB and based on the Newton–Raphson method,which shows very fast and efficient rate of convergence as well as computationally the proposed method is very efficient and it requires less computer memory through the use of sparsing method and other methods in programming to accelerate the run speed to be near...

In 1993, I submitted a Master's Thesis titled "Coherers, A Review". I had hoped to revise the thesis, if new materials appeared, either pre-1993 materials or post-1993 materials. I was surprised to discover significant amounts of old and new original source materials. Unfortunately, I was soon overwhelmed with the information, and when I tried to i...

Representation learning is an important step in the machine learning pipeline. Given the current biological sequencing data volume, learning an explicit representation is prohibitive due to the dimensionality of the resulting feature vectors. Kernel-based methods, e.g., SVM, are a proven efficient and useful alternative for several machine learning...

Recursive algorithms always consume a computer's memory stack, and in this paper we worked to increase the speed of the recursive algorithm through a dynamic base that changes during its implementation process. Dynamic base regulation often allows avoiding repeated calculations of the same sets of parameter values, which reduces the number of repea...

Continual learning on sequential data is critical for many machine learning (ML) deployments. Unfortunately, LSTM networks, which are commonly used to learn on sequential data, suffer from catastrophic forgetting and are limited in their ability to learn multiple tasks continually. We discover that catastrophic forgetting in LSTM networks can be ov...

The SPIHT image compression algorithm is characterized by low computational complexity, good performance, and the production of a quality scalable bitstream that can be decoded at several bit-rates with image quality enhancement as more bits are received. However, it suffers from the enormous computer memory consumption due to utilizing linked list...

Being the 4th fundamental passive element, the memristor could play a vital role in emerging technology. A simple two-terminal device structure and small dimension extend the application of memristor in super-fast computing, memory and neuromorphic systems. The high dielectric constant of hafnium oxide (HfOx) attracts considerable interest in resis...

It is essential to generate multivariate three-dimensional cross-correlated random fields since the spatial variability of geomaterials has a great influence on the failure mechanism and reliability of geotechnical structures. Standard matrix decomposition (MD) method has now been commonly employed to generate random field due to its simplicity. Ho...

Organic material-based computer memory devices are critical for lowering the amount of electronic waste. Toward this end, we here present the resistive switching property of metalinsulator-metal type devices consisting of active layers made of raw organic cow milk. Our devices were made up of fat-free, medium cream, and full cream raw cow milk acti...

The softmax attention mechanism has emerged as a noteworthy development in the field of Artificial Intelligence research, building on the successes of Transformer-based architectures. However, their ever increasing sizes necessitate ever increasing computational memory, that limits their usage. We propose KgV, a sigmoid gating mechanism that, in co...

High-resolution three-dimensional (3D) seismic simulation imposes severe demands for computational memory, making low-storage seismic simulation particularly important. Due to its high-efficiency and low-storage, the half-precision floating-point 16-bit format (FP16) is widely used in heterogeneous computing platforms, such as Sunway series superco...

Graphs model several real-world phenomena. With the growth of unstructured and semi-structured data, parallelization of graph algorithms is inevitable. Unfortunately, due to inherent irregularity of computation, memory access, and communication, graph algorithms are traditionally challenging to parallelize. To tame this challenge, several libraries...

The dominant paradigm for analysing genetic variation relies on a central idea: all genomes in a species can be described as minor differences from a single reference genome. However, this approach can be problematic or inadequate for bacteria, where there can be significant sequence divergence within a species. Reference graphs are an emerging sol...

Experiences and studies have shown that soil-structure interaction (SSI) effect has a vital role in the dynamic behaviour of a soil-structure system. Despite this, analyses involving dynamic SSI are still challenging for practicing engineers due to their complexity and accessibility. In this thesis, the hybrid BEM-FEM implementation is aimed at pra...

Digital data is crucial in the investigation of cybercrime, and digital forensics is a field that encompasses various scientific approaches to acquire, analyses, and report digital evidence. One of the key components of digital forensics is memory forensics, which involves analyzing the volatile data stored in a computer's memory to gather evidence...