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# Computer Algorithm - Science topic

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Chaos, a long-term aperiodic and random-like behavior manifested by many nonlinear complex dynamic systems requires the unveiling of representative paths into richness of complexity and the plethora of experimental processes. There exist numerous attribute properties and patterns which cannot be described only by theory, so the internal complexity...

Greetings from Biomimetics. With great pleasure I am contacting you about the Special Issue “Nature-Inspired Computer Algorithms” of Biomimetics in which I am serving as Guest Editor. We are excited to share the news that /Biomimetics/ received an Impact Factor for 2021 of 3.743, following our earlier news of a CiteScore of 5.2.
This Special Issue...

Computer-aided process planning is mainly focusing on industrial processes and implies the use of computer technology in manufacturing of products. In the present social-economical context, one of the main components of the competitiveness refers to the time reduction of the preparatory and production
launch stages. For this, simple tools such as c...

The rapid development of technology allows people to obtain a large amount of data, which contains important information and various noises. How to obtain useful knowledge from data is the most important thing at this stage of machine learning (ML). The problem of unbalanced classification is currently an important topic in the field of data mining...

Quantum computing opens up new possibilities for the simulation of many-body nuclear systems. As the number of particles in a many-body system increases, the size of the space if the associated Hamiltonian increases exponentially. This presents a challenge when performing calculations on large systems when using classical computing methods. By usin...

The recognition of human actions in videos is one of the most active research fields in computer vision. The canonical approach consists in a more or less complex preprocessing stages of the raw video data, followed by a relatively simple classification algorithm. Here we address recognition of human actions using the reservoir computing algorithm,...

In recent years, the research on the non-photorealistic painting of watercolor painting through computer algorithms has made rapid progress, and its specific application has also been increasingly valued. This paper proposes a new machine vision method based on genetic algorithm and applies it to the research of oil painting style and image process...

The inverse Toeplitz eigenvalue problem (ToIEP) concerns finding a vector that specifies the real-valued symmetric Toeplitz matrix with the prescribed set of eigenvalues. Since phase "calibration" errors in uniform linear antenna arrays (ULAs) do not change the covariance matrix eigenvalues and the moduli of the covariance matrix elements, we formu...

The Joint Automated Repository for Various Integrated Simulations (JARVIS) infrastructure at the National Institute of Standards and Technology (NIST) is a large-scale collection of curated datasets and tools with more than 80000 materials and millions of properties. JARVIS uses a combination of electronic structure, artificial intelligence (AI), a...

The application of Artificial Intelligence (AI) in painting has gained significant attention in recent years, promising to revolutionize the digital art world and enhance traditional painting processes. AI painting involves the use of computer algorithms and machine learning techniques to generate and manipulate digital images. This paper provides...

This paper considers the problem of designing an optimal inter-orbital spacecraft transfer. We present a computational algorithm and modeling results of the optimal transfer
trajectory between near-Earth elliptical orbits for a spacecraft with a chemical booster and fixed thrust. The trajectory design procedure includes four stages as follows: a)...

In this work, we intend to present the power of recent AI models specially Generative AI. Generative AI is an emerging field of artificial intelligence that focuses on the creation of new and original content using machine learning algorithms and neural networks. Generative AI (GAI)systems can generate a wide variety of content, including images, m...

Generative AI models like DALL-E 2 can interpret textual prompts and generate high-quality images exhibiting human creativity. Though public enthusiasm is booming, systematic auditing of potential gender biases in AI-generated images remains scarce. We addressed this gap by examining the prevalence of two occupational gender biases (representationa...

This paper presents the development of a mathematical model for a direct-expansion solar-assisted heat pump (DX-SAHP) operating in steady-state. The mathematical model was implemented using the scientific software EES and using a code written in Python. It was utilized a lumped parameter model for the heat exchangers and a semi-empirical model for...

Parabolic equations play an important role in chemical engineering, vibration theory, particle diffusion and heat conduction. Solutions of such equations are required to analyze and predict changes in physical systems. Solutions of such equations require efficient and effective techniques to get reasonable accuracy in lesser time. For this purpose,...

There are speculations that conventional libraries will no longer run and go extinct if they do not diversify their activities from manual to smart technologies. The emerging technologies have made information professionals refer to the library as smart libraries. The influx of emerging technology has compelled librarians and patrons to search for...

Computed Tomography (CT) scanning is a powerful imaging technique that utilizes X-rays and advanced computer algorithms to create detailed cross-sectional images of the human body. This article explores the principles of CT scanning, including the technology behind it and its applications in various medical specialties. Introduction:

Cytochrome P450 oxidoreductase (POR) protein is essential for steroidogenesis, and POR gene mutations are frequently associated with P450 Oxidoreductase Deficiency (PORD), a disorder of hormone production. To our knowledge, no previous attempt has been made to identify and analyze the deleterious/pathogenic non-synonymous single nucleotide polymorp...

Haplotype networks are graphs used to represent evolutionary relationships between a set of taxa and are characterized by intuitiveness in analyzing genealogical relationships of closely related genomes. We here propose a novel algorithm termed McAN that considers mutation spectrum history (mutations in ancestry haplotype should be contained in des...

There are many ways to monetize video games: from the simple direct purchase to the system of “games as a service”. There are, however, forms of monetization that show strong indications of being detrimental to consumers, such as the so-called “loot boxes” that are offered during gameplay. No study so far has categorically proven whether or not loo...

For searching an item in unstructured databases, Grover's quantum search algorithm offers quadratic speedup over classical search algorithms. This paper reports 2 to 5 quantum-bit (Qubit) implementations of Grover's search algorithm using the phase-flip method for oracle function realization without any extra ancilla qubit. A comprehensive estimati...

The utmost popular dementia cause is because the (AD) Alzheimer’s disease. A continuous drop in mental ability is referred to as Dementia. Using the medical images of the brain, the developmental stages of AD symptom of neuropsychiatric functionality are analyzed often. Particularly in the area of classification and detection, cutting edge technolo...

In urban areas, deep excavation-induced ground deformation may damage adjacent existing structures and is conventionally evaluated by levelling at installed settlement points. However, a small number of measurements cannot represent the total change in ground deformation adjacent to excavation sites. Furthermore, significant local subsidence may oc...

This paper concerns the stabilization problem for an underactuated robot called the Pendubot. Relying on a computational algorithm which is based on various results of the ‘polynomial matrix approach’, we propose an output-feedback-based internally stabilizing controller to stabilize the Pendubot at the unstable vertical upright position. The algor...

The cerebellum operates exploiting a complex modular organization and a unified computational algorithm adapted to different behavioral contexts. Recent observations suggest that the cerebellum is involved not just in motor but also in emotional and cognitive processing. It is therefore critical to identify the specific regional connectivity and mi...

It is very important for holographic optical tweezers (OTs) to develop high-quality phase holograms through calculation by using some computer algorithms, and one of the most commonly used algorithms is the Gerchberg–Saxton (GS) algorithm. An improved GS algorithm is proposed in the paper to further enhance the capacities of holographic OTs, which...

Recent developments in quantum computing pose a significant threat to the asymmetric cryptography currently in use. Neural cryptography offers a potential alternative that is resistant to attacks of known quantum computer algorithms. The considered solution is lightweight and computationally efficient. If a quantum computer algorithm were successfu...

Voronoi treemaps are widely used for hierarchical data visualization. Existing methods calculate the visualization layouts of hierarchical data by combining the proportion optimization of weights and Lloyd’s method of sites. However, this may not only produce results with large area errors but also require more time consumption. Besides, the relati...

Many networks in political and social research are bipartite, with edges connecting exclusively across two distinct types of nodes. A common example includes cosponsorship networks, in which legislators are connected indirectly through the bills they support. Yet most existing network models are designed for unipartite networks, where edges can ari...

We propose an easy-to-implement iterative method for resolving the implicit (or semi-implicit) schemes arising in solving reaction-diffusion (RD) type equations. We formulate the nonlinear time implicit scheme as a min-max saddle point problem and then apply the primal-dual hybrid gradient (PDHG) method. Suitable precondition matrices are applied t...

This study used two computational algorithms to investigate the rate of increased heat generation(ėgen) and decrease thermal diffusivity constant (α) on a three-dimensional heat equation in a rectangular coordinate system for three materials (air, water, soil). The proposed algorithms were developed using the MAPLE 18 software, and numerical soluti...

Fresnel incoherent correlation holography (FINCH) is a well-established incoherent digital holography technique. In FINCH, light from an object point splits into two, differently modulated using two diffractive lenses with different focal distances and interfered to form a self-interference hologram. The hologram numerically back propagates to reco...

Factor analysis provides a canonical framework for imposing lower-dimensional structure such as sparse covariance in high-dimensional data. High-dimensional data on the same set of variables are often collected under different conditions, for instance in reproducing studies across research groups. In such cases, it is natural to seek to learn the s...

Improving and enhancing the effectiveness of software vulnerability detection methods is urgently needed today. In this study, we propose a new source code vulnerability detection method based on intelligent and advanced computational algorithms. It's a combination of four main processing techniques including (i) Source Embedding, (ii) Feature Lear...

The purpose of this paper is twofold. Firstly, to emphasise that the class of Lie algebras with chain lattices of ideals are elementary blocks in the embedding or decomposition of Lie algebras with finite lattice of ideals. Secondly, to show that the number of Lie algebras of this class is large and they support other types of Lie structures. Begin...

In response to socioeconomic development, the number of machine learning applications has increased, along with the calls for algorithmic transparency and further sustainability in terms of energy efficient technologies. Modern computer algorithms that process large amounts of information, particularly artificial intelligence methods and their work...

This paper proposed and applied a three-step computational algorithm to solve the time-fractional Navier-Stokes equation (FNS) in a given cylindrical coordinates for one-way unstable flow motion. The Caputo definition of fraction order was obtained using the Riemann Liouville fractional integral operator, which was coded with the MAPLE18 software c...

We investigate local computation algorithms (LCA) for two-coloring of $k$-uniform hypergraphs. We focus on hypergraph instances that satisfy strengthened assumption of the Lov\'{a}sz Local Lemma of the form $2^{1-\alpha k} (\Delta+1) \mathrm{e} < 1$, where $\Delta$ is the bound on the maximum edge degree. The main question which arises here is for...

We approach the process of protein folding as a form of molecular self-assembly, with unfolding considered as disassembly. Fracture, on the other hand, tends to occur much more rapidly than self-assembly. Self-assembly typically follows an exponential decay pattern, as energy dissipates, while fracture proceeds at a constant rate, with damping oppo...

Global traveltime modeling is an essential component of modern seismological studies with a whole gamut of applications ranging from earthquake source localization to seismic velocity inversion. Emerging acquisition technologies like distributed acoustic sensing (DAS) promise a new era of seismological discovery by allowing a high-density of seismi...

Protein phosphorylation is a key post-translational modification (PTM) that is a central regulatory mechanism of many cellular signaling pathways. Several protein kinases and phosphatases precisely control this biochemical process. Defects in the functions of these proteins have been implicated in many diseases, including cancer. Mass spectrometry...

Huge advancements have been made over the years in terms of modern image-sensing hardware and visual computing algorithms (e.g., computer vision, image processing, and computational photography). However, to this day, there still exists a current gap between the hardware and software design in an imaging system, which silos one research domain from...

This paper presents a shadowless projection mapping system for interactive applications in which a target surface is frequently occluded from a projector with a user's body. We propose a delay-free optical solution for this critical problem. Specifically, as the primary technical contribution, we apply a large format retrotransmissive plate to proj...

In Continuum Mechanics a widely cited formula, due to Nanson (Mess Math 7:182–185, 1878), contributes the relation between the product of area and unit normal vectors relevant to corresponding surfaces in two configurations of a 3D body. A geometric treatment provides equivalent expressions of Nanson formula by direct elaborations on Euler–Jacobi v...

The research on Internet of Things (IoT) network and edge computing has been a research hotspot in both industry and academia in recent years, especially for the ambient intelligence and massive communication. As a typical form of IoT network and edge computing, the intelligent perception vocal music singing learning system has attracted the attent...

To stay competitive in the growing dairy market, farmers must continuously improve their livestock production systems. Precision livestock farming technologies provide individualised monitoring of animals on commercial farms, optimising livestock production. Continuous acoustic monitoring is a widely accepted sensing technique used to estimate the...

Background
Osteosarcoma (OS) is the most prevalent primary fatal bone neoplasm in adolescents and children owing to limited therapeutic methods. Circular RNAs (circRNAs) are identified as vital regulators in a variety of cancers. However, the roles of circRNAs in OS are still unclear.
Methods
Firstly, we evaluate the differentially expressed circR...

Machine learning (ML) refers to computer algorithms that predict a meaningful output or categorize complex systems based on a large amount of data. ML is applied in various areas including natural science, engineering, space exploration, and even gaming development. This review focuses on the use of machine learning in the field of chemical and bio...

Integrated photonics, because of its intrinsic high speed, large bandwidth and unlimited parallelism, is critical in the drive to ease the increasing data traffic. Its technological enabler is high-precision lithography, which allows for the fabrication of high-resolution photonic structures. Here, in complete contrast to the state of the art, wher...

The connection of simulation models with virtual reality (VR) technology is of great importance in implementing Industry 4.0 in industrial practice. The article deals with the use of virtual reality in discrete event simulation (DES) using the Tecnomatix Plant Simulation software to visualize, analyze and optimize the modelled production–assembly p...

Brain tumor (BT) diagnosis is a lengthy process, and great skill and expertise are required from radiologists. As the number of patients has expanded, so has the amount of data to be processed, making previous techniques both costly and ineffective. Many academics have examined a range of reliable and quick techniques for identifying and categorizi...

Since the cumulative distribution function(CDF) of the doubly non-central beta distribution can be represented by the infinite double series, therefore, truncating the summation of the series can obtain the approximate value of CDF. The existing numerical computation methods must specify the truncating range and cannot estimate the calculation erro...

p>The development of quantum computers represents a breakthrough in the evolution of computing. Their graceful processing capacity will help to solve some problems impossible until now because the algorithms that calculate their solution require too much amount of memory or processing time. In portfolio theory, the investment portfolio optimization...

p>The development of quantum computers represents a breakthrough in the evolution of computing. Their graceful processing capacity will help to solve some problems impossible until now because the algorithms that calculate their solution require too much amount of memory or processing time. In portfolio theory, the investment portfolio optimization...

Nuclear magnetic resonance (NMR) spectroscopy is a powerful method for studying the structure and dynamics of proteins in their native state. For high-resolution NMR structure determination, the collection of a rich restraint dataset is necessary. This can be difficult to achieve for proteins with high molecular weight or a complex architecture. Co...

Convolutional computation takes over 90% of convolutional neural network (CNN) calculations; one way to accelerate the convolutional computation of CNN is to employ hardware-based parallel computing. Memristor-based neuromorphic computing systems are one of the promising hardware acceleration strategies. In this paper, we propose a full-size convol...

We present a physically appealing and elegant picture for quantum computing using rules constructed for a game of darts. A dartboard is used to represent the state space in quantum mechanics and the act of throwing the dart is shown to have close similarities to the concept of measurement, or collapse of the wavefunction in quantum mechanics. The a...

Spectral computational methods leverage modal or nonlocal representations of data, and a physically realized approach to spectral computation pertains to encoded diffraction. Encoded diffraction offers a hybrid approach that pairs analog wave propagation with digital back-end electronics, however the intermediate sensor patterns are correlations ra...

Informatics paradigms for brain and mental health research have seen significant advances in recent years. These developments can largely be attributed to the emergence of new technologies such as machine learning, deep learning, and artificial intelligence. Data-driven methods have the potential to support mental health care by providing more prec...

A pharmaceutical supply chain (PSC) is a system of processes, operations, and organisations for drug delivery. This paper provides a new PSC mathematical cost model, which includes Blockchain technology (BT), that can improve the safety, performance, and transparency of medical information sharing in a healthcare system. We aim to estimate the cost...

The ability to engineer and predict drug release behavior during treatment is critical to the design and implementation of effective drug delivery systems. In this study, a drug delivery system consisting of a methacrylate-based polymer and flurbiprofen was studied, and its release profile in a controlled phosphate-buffered saline solution was char...

High-frequency observations of surface current field data over large areas and long time series are imperative for comprehending sea-air interaction and ocean dynamics. Nonetheless, neither in situ observations nor polar-orbiting satellites can fulfill the requirements necessary for such observations. In recent years, geostationary satellite data w...

The spike-timing dependent plasticity (STDP) learning rules are popular in both neuroscience and computer algorithms due to their ability to capture the change in neural connections arising from the correlated activity of neurons. Recent advances in recording technology have made large neural recordings common, but to date, there is no established...

Weighted Logistic Regression (WLR) is a method used to overcome imbalanced data or rare events by using weighting and is part of the development of a simple logistic regression model. Parameter estimation of the WLR model uses Maximum Likelihood estimation. The maximum likelihood parameter estimator value is obtained using an optimization approach....