Computation a journal of computational science and engineering. Topics: computational biology, including, but not limited to:  bioinformatics  mathematical modeling, simulation and prediction of nucleic acid (DNA/RNA) and protein sequences, structure and functions  mathematical modeling of pathways and genetic interactions  neuroscience computation including neural modeling, brain theory and neural networks  computational chemistry, including, but not limited to:  new theories and methodology including their applications in molecular dynamics  computation of electronic structure  density functional theory  designing and characterization of materials with computation method  computation in engineering, including, but not limited to:  new theories, methodology and the application of computational fluid dynamics (CFD)  optimisation techniques and/or application of optimisation to multidisciplinary systems  system identification and reduced order modelling of engineering systems  parallel algorithms and high performance computing in engineering.

Computation is a journal dedicated to computational science and engineering. The main topics include computational biology, covering but not limited to bioinformatics, mathematical modeling, simulation, and prediction of nucleic acid (DNA/RNA) and protein sequences, modeling of pathways and genetic interactions; neuroscience computation, including neural modeling, brain theory, and neural networks; computational chemistry, encompassing new theories and methodologies, including their applications in molecular dynamics, electronic structure computation, density functional theory, and computational methods for designing and characterizing materials; and computation in engineering, which includes new theories, methodologies, and applications of computational fluid dynamics (CFD), optimization techniques and their applications to multidisciplinary systems, system identification, reduced-order modeling of engineering systems, and parallel algorithms and high-performance computing in engineering.

《Computation》是一本关于计算科学与工程的期刊。主要涉及的主题包括：计算生物学，涵盖但不限于生物信息学、核酸（DNA/RNA）和蛋白质序列的数学建模、模拟与预测、通路和基因相互作用的数学建模；神经科学计算，包括神经建模、大脑理论和神经网络；计算化学，涵盖但不限于新理论和方法论及其在分子动力学中的应用、电子结构计算、密度泛函理论、材料设计与表征的计算方法；工程计算，包括但不限于新理论、方法论及计算流体动力学（CFD）的应用、优化技术及其在多学科系统中的应用、工程系统的系统识别和降阶建模、工程中的并行算法和高性能计算。

Computation

In the field of cryptography, many algorithms rely on the computation of modular multiplicative inverses to ensure the security of their systems. In this study, we build upon our previous research by introducing a novel sequence, (zj)j≥0, that can calculate the modular inverse of a given pair of integers (a,n), i.e., a−1;mod,n. The computational complexity of this approach is O(a), which is more efficient than the traditional Euler’s phi function method, O(n,ln,n). Furthermore, we investigate the properties of the sequence (zj)j≥0 and demonstrate that all solutions of the problem belong to a specific set, I, that only contains the minimum values of (zj)j≥0. This results in a reduction of the computational complexity of our method, especially when a∼n and it also opens new opportunities for discovering closed-form solutions for the modular inverse.

Michele Bufalo

Daniele Bufalo

Giuseppe Orlando

Some Properties of the Computation of the Modular Inverse with Applications in Cryptography

模逆计算的一些性质及其在密码学中的应用

Convolutional neural networks (CNNs) are one of the main types of neural networks used for image recognition and classification. CNNs have several uses, some of which are object recognition, image processing, computer vision, and face recognition. Input for convolutional neural networks is provided through images. Convolutional neural networks are used to automatically learn a hierarchy of features that can then be utilized for classification, as opposed to manually creating features. In achieving this, a hierarchy of feature maps is constructed by iteratively convolving the input image with learned filters. Because of the hierarchical method, higher layers can learn more intricate features that are also distortion and translation invariant. The main goals of this study are to help academics understand where there are research gaps and to talk in-depth about CNN’s building blocks, their roles, and other vital issues.

Mohammad Mustafa Taye

Theoretical Understanding of Convolutional Neural Network: Concepts, Architectures, Applications, Future Directions

卷积神经网络的理论理解：概念、架构、应用、未来方向

Energy efficiency has become a crucial focus with the growing attention on sustainable development and decreasing energy consumption in the built environment. Different construction methods are being applied worldwide, such as conventional, modular, and 3D-printing methods, to increase energy efficiency in buildings. This study aims to enhance the decision-making process by identifying optimal construction techniques, material selection, and ventilation window dimensions to promote sustainable energy use in buildings. A novel framework combining Building Information Modeling (BIM), computational analysis, and Multi-Criteria Decision-Making (MCDM) approaches is applied to assess the energy use intensity (EUI), annual electric energy consumption, and lifecycle energy cost across multiple sequences for each type of construction. Computational analysis in this research is combined in two main tools. Minitab is utilized for experimental design to determine the number and configurations of sequences analyzed. The Simple Additive Weighting (SAW) method, applied as an MCDM tool, is used to assess and rank the performance of sequences based on equally weighted criteria. Subsequently, 3D models of case study buildings are developed, and energy simulations are conducted using Autodesk Revit and Autodesk Green Building Studio, respectively, as BIM tools to compare the energy performance of various design alternatives. The results revealed that 3D printing surpassed other methods, where Sequence 7 achieved approximately 10.3% higher efficiency than modular methods and 40.5% better performance than conventional methods in the evaluated criteria. The findings underscore the higher energy efficiency of 3D printing, followed by modular construction as a competitive method, while conventional methods lagged significantly.

Abdullah Al Masri

Assed N. Haddad

Mohammad K. Najjar

Comparative Analysis of Energy Efficiency in Conventional, Modular, and 3D-Printing Construction Using Building Information Modeling and Multi-Criteria Decision-Making

基于建筑信息建模与多准则决策的常规建筑、模块化建筑及3D打印建筑能效比较分析

Gyroid-like structures are promising in terms of energy absorption levels. Due to additive manufacturing, they can now be manufactured and verified for different functions. In this article, it has been proven that a Gyroid manufactured by FDM using PLA with 0.2 relative density must be oriented so that compression takes place along the build direction to obtain higher levels of force and energy. The Gyroid can be scaled, allowing the use of a single compression curve with almost constant forces up to 50% compression. The model to predict properties as a function of relative density fits well with a power-law for n = 2.2. The ability of the Gyroid to absorb energy per kilogram is about seven times lower than that of a solid PLA cube, but it can be used to obtain desired levels of deceleration. It is possible to use a simple constant deceleration model to define the Gyroid size, mass, and velocity of the object to be impacted. The use of this approach allows the tailored combination of Gyroid sizes to meet multi-objective impact targets. The simulation of impacts with a finite element model of only 125 solid elements is possible with errors below 10%. By combining different Gyroid sizes, two different safety regulations can be met. Modeling the Gyroid by meshing the real geometry allows for the local maximum force magnified at high strain rates, but it is not able to correctly predict densification.

Horacio Rostro-González

Guillermo Reyes-Pozo

Josep Maria Puigoriol-Forcada

Francisco-José López-Valdés

Sriharsha Srinivas Sundarram

Andres-Amador Garcia-Granada

Additive Manufacturing Gyroid Structures Used as Crash Energy Management

增材制造Gyroid结构用于碰撞能量管理

One of the issues in Natural Language Processing (NLP) and Artificial Intelligence (AI) is language representation and modeling, aiming to manage its structure and find solutions to linguistic issues. With the pursuit of the most efficient capture of knowledge about the Modern Greek language and, given the scientifically certified usability of the ontological structuring of data in the field of the semantic web and cognitive computing, a new ontology of the Modern Greek language at the level of structure and vocabulary is presented in this paper, using the Protégé platform. With the specific logical and structured form of knowledge representation to express, this research processes and exploits in an easy and useful way the distributed semantics of linguistic information.

Nikoletta Samaridi

Evangelos Papakitsos

Nikitas Karanikolas

Ontological Representation of the Structure and Vocabulary of Modern Greek on the Protégé Platform

基于Protégé平台的现代希腊语结构与词汇的本体论表示

This paper introduces a novel adaptive control method for suspension vehicle systems in response to road disturbances. The considered model is based on an active symmetry quarter car (SQC) fractional order suspension system (FOSS). The word symmetry in SQC refers to the symmetry of the suspension system in the front tires or the rear tires of the car. The active suspension controller is generally driven by an external force like a hydraulic or pneumatic actuator. The external force of the actuator is determined using fractional dynamic sliding mode control (FDSMC) to counteract road disturbances and eliminate the chattering caused by sliding mode control (SMC). In FDSMC, a fractional integral acts as a low-pass filter before the system actuator to remove high-frequency chattering, necessitating an additional state for FDSMC implementation assuming all FOSS state variables are available but the parameters are unknown and uncertain. Hence, an adaptive procedure is proposed to estimate these parameters. To enhance closed-loop system performance, an adaptive proportional-integral (PI) procedure is also employed, resulting in the FDSMC-PI approach. A comparison is made between two SQC suspension system models, the fractional order suspension system (FOSS) and the integer order suspension system (IOSS). The IOSS controller is based on dynamic sliding mode control (DSMC) and a PI procedure (DSMC-PI). The results show that FDSMC outperforms DSMC.

Ali Karami-Mollaee

Oscar Barambones

On Adaptive Fractional Dynamic Sliding Mode Control of Suspension System

关于悬架系统的自适应分数阶动态滑模控制

Aircraft cabins have high occupant densities and may introduce the risk of COVID-19 contamination. In this study, a segment of a Boeing 767 aircraft cabin with a mixing type of air distribution system was investigated for COVID-19 deposition. A section of a Boeing 737-300 cabin, featuring four rows with 28 box-shaped mannequins, was used for simulation. Conditioned air entered through ceiling inlets and exited near the floor, simulating a mixed air distribution system. Cough droplets were modeled using the Discrete Phase Model from two locations: the centre seat in the second row and the window seat in the fourth row. These droplets had a mean diameter of 90 µm, an exhalation velocity of 11.5 m/s and a flow rate of 8.5 L/s. A high-quality polyhedral mesh of about 7.5 million elements was created, with a skewness of 0.65 and an orthogonality of 0.3. The SIMPLE algorithm and a second-order upwind finite volume method were used to model airflow and droplet dynamics. It was found that the ceiling accounted for the maximum concentration followed by the seats. The concentration of deposits was almost 50% more when the source was at window as compared to the centre seat. The Covid particles resided for longer duration when the source was at the centre of the cabin than when it was located near the widow.

S. M. Abdul Khader

John Valerian Corda

Kevin Amith Mathias

Gowrava Shenoy

Kamarul Arifin bin Ahmad

Augustine V. Barboza

Sevagur Ganesh Kamath

Mohammad Zuber

Study of Ventilation Strategies in a Passenger Aircraft Cabin Using Numerical Simulation

基于数值模拟的客机舱内通风策略研究

This study addresses the accessibility challenges faced by individuals with visual impairments due to limited access to graphic information, which significantly impacts their educational and social integration. Traditional methods for producing tactile graphics are labor-intensive and require specialized expertise, limiting their availability. Recent advancements in generative models, such as GANs, diffusion models, and VAEs, offer potential solutions to automate the creation of tactile images. In this work, we propose a novel generative model conditioned on text prompts, integrating a Bidirectional and Auto-Regressive Transformer (BART) and Vector Quantized Variational Auto-Encoder (VQ-VAE). This model transforms textual descriptions into tactile graphics, addressing key requirements for legibility and accessibility. The model’s performance was evaluated using cross-entropy, perplexity, mean square error, and CLIP Score metrics, demonstrating its ability to generate high-quality, customizable tactile images. Testing with educational and rehabilitation institutions confirmed the practicality and efficiency of the system, which significantly reduces production time and requires minimal operator expertise. The proposed approach enhances the production of inclusive educational materials, enabling improved access to quality education and fostering greater independence for individuals with visual impairments. Future research will focus on expanding the training dataset and refining the model for complex scenarios.

Yehor Dzhurynskyi

Volodymyr Mayik

Lyudmyla Mayik

Enhancing Accessibility: Automated Tactile Graphics Generation for Individuals with Visual Impairments

提升可访问性：面向视障人士的自动化触觉图形生成

This study investigates the transformative potential of blockchain technology in financial accounting by examining its applications, challenges, and implications. The study begins with a review of blockchain’s origins and its ability to address inefficiencies, fraud risks, and transparency limitations in traditional accounting. A mixed-methods approach was employed, combining qualitative thematic analysis and quantitative statistical techniques. The qualitative analysis involved thematic coding of data from case studies and organizational reports, while the quantitative analysis assessed financial data using descriptive and inferential statistical methods. Eight organizations from diverse industries—including banking, retail, and technology—were purposively sampled to capture varied experiences and applications of blockchain technology. Key findings reveal blockchain’s ability to enhance transparency, efficiency, and security in financial transactions, offering significant advantages for financial reporting and auditing. However, challenges such as regulatory uncertainties, scalability concerns, and technical complexities remain barriers to its widespread adoption. This research provides actionable recommendations to overcome these challenges and maximize blockchain’s benefits in financial accounting. By integrating theoretical insights with empirical evidence, this study contributes to advancing the understanding of blockchain’s role in transforming financial practices, offering practical guidance for academia and industry practitioners alike.

Abbreviation	Computation. (Basel).
Journal Impact	1.72
Quartiles(Global)	MATHEMATICS, INTERDISCIPLINARY APPLICATIONS(Q2)

ISSN	2079-3197
h-index	30

Publication Information	Publisher: Multidisciplinary Digital Publishing Institute (MDPI)，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2013，Proportion of original research papers: 97.29%，Self Citation Rate:10.50%， Gold OA Rate: 99.51%
Journal Fees	$Details
Average review cycle	8 weeks

Computation

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Some Properties of the Computation of the Modular Inverse with Applications in Cryptography

Theoretical Understanding of Convolutional Neural Network: Concepts, Architectures, Applications, Future Directions

Comparative Analysis of Energy Efficiency in Conventional, Modular, and 3D-Printing Construction Using Building Information Modeling and Multi-Criteria Decision-Making

Additive Manufacturing Gyroid Structures Used as Crash Energy Management

Ontological Representation of the Structure and Vocabulary of Modern Greek on the Protégé Platform

On Adaptive Fractional Dynamic Sliding Mode Control of Suspension System

Study of Ventilation Strategies in a Passenger Aircraft Cabin Using Numerical Simulation

Ontological Representation of the Structure and Vocabulary of Modern Greek on the Protégé Platform

Enhancing Accessibility: Automated Tactile Graphics Generation for Individuals with Visual Impairments

Development of Blockchain Technology in Financial Accounting