PLOS ONE: [sortOrder=DATE_NEWEST_FIRST, sort=Date, newest first, q=subject:"Computing methods"]PLOShttps://journals.plos.org/plosone/webmaster@plos.orgaccelerating the publication of peer-reviewed sciencehttps://journals.plos.org/plosone/search/feed/atom?sortOrder=DATE_NEWEST_FIRST&unformattedQuery=subject:%22Computing+methods%22&sort=Date,+newest+firstAll PLOS articles are Open Access.https://journals.plos.org/plosone/resource/img/favicon.icohttps://journals.plos.org/plosone/resource/img/favicon.ico2024-03-28T19:29:40ZBayesian-knowledge driven ontologies: A framework for fusion of semantic knowledge under uncertainty and incompletenessEugene Santos Jr.Jacob JurmainAnthony Ragazzi10.1371/journal.pone.02968642024-03-27T14:00:00Z2024-03-27T14:00:00Z<p>by Eugene Santos Jr., Jacob Jurmain, Anthony Ragazzi</p>
The modeling of uncertain information is an open problem in ontology research and is a theoretical obstacle to creating a truly semantic web. Currently, ontologies often do not model uncertainty, so stochastic subject matter must either be normalized or rejected entirely. Because uncertainty is omnipresent in the real world, knowledge engineers are often faced with the dilemma of performing prohibitively labor-intensive research or running the risk of rejecting correct information and accepting incorrect information. It would be preferable if ontologies could explicitly model real-world uncertainty and incorporate it into reasoning. We present an ontology framework which is based on a seamless synthesis of description logic and probabilistic semantics. This synthesis is powered by a link between ontology assertions and random variables that allows for automated construction of a probability distribution suitable for inferencing. Furthermore, our approach defines how to represent stochastic, uncertain, or incomplete subject matter. Additionally, this paper describes how to fuse multiple conflicting ontologies into a single knowledge base that can be reasoned with using the methods of both description logic and probabilistic inferencing. This is accomplished by using probabilistic semantics to resolve conflicts between assertions, eliminating the need to delete potentially valid knowledge and perform consistency checks. In our framework, emergent inferences can be made from a fused ontology that were not present in any of the individual ontologies, producing novel insights in a given domain.A fuzzy description logic based IoT framework: Formal verification and end user programmingMiguel Pérez-GasparJavier GomezEverardo BárcenasFrancisco Garcia10.1371/journal.pone.02966552024-03-22T14:00:00Z2024-03-22T14:00:00Z<p>by Miguel Pérez-Gaspar, Javier Gomez, Everardo Bárcenas, Francisco Garcia</p>
The Internet of Things (IoT) has become one of the most popular technologies in recent years. Advances in computing capabilities, hardware accessibility, and wireless connectivity make possible communication between people, processes, and devices for all kinds of applications and industries. However, the deployment of this technology is confined almost entirely to tech companies, leaving end users with only access to specific functionalities. This paper presents a framework that allows users with no technical knowledge to build their own IoT applications according to their needs. To this end, a framework consisting of two building blocks is presented. A friendly interface block lets users tell the system what to do using simple operating rules such as “if the temperature is cold, turn on the heater.” On the other hand, a fuzzy logic reasoner block built by experts translates the ambiguity of human language to specific actions to the actuators, such as “call the police.” The proposed system can also detect and inform the user if the inserted rules have inconsistencies in real time. Moreover, a formal model is introduced, based on fuzzy description logic, for the consistency of IoT systems. Finally, this paper presents various experiments using a fuzzy logic reasoner to show the viability of the proposed framework using a smart-home IoT security system as an example.Stealing complex network attack detection method considering security situation awarenessBo XiHuiying LiuBotao HouYing WangYuling Guo10.1371/journal.pone.02985552024-03-21T14:00:00Z2024-03-21T14:00:00Z<p>by Bo Xi, Huiying Liu, Botao Hou, Ying Wang, Yuling Guo</p>
Tracking and detection have brought great challenges to network security. Therefore, this paper proposes a monitoring method of stealthy complex network attacks considering security situation awareness. By constructing a tracking model of invisible complex network attacks, public monitoring nodes are selected for monitoring. The cost of a single monitoring node is calculated by the algorithm, and the monitoring node is determined by the monitoring node algorithm, so as to reduce the resource occupancy rate of the monitoring node and improve the monitoring accuracy. The simulation results show that this method is stable in the range of 1000 to 4000 nodes, and can effectively monitor the complex network attacks of stealing secrets.Control strategies for inverted pendulum: A comparative analysis of linear, nonlinear, and artificial intelligence approachesSaqib IrfanLiangyu ZhaoSafeer UllahAdeel MehmoodMuhammad Fasih Uddin Butt10.1371/journal.pone.02980932024-03-07T14:00:00Z2024-03-07T14:00:00Z<p>by Saqib Irfan, Liangyu Zhao, Safeer Ullah, Adeel Mehmood, Muhammad Fasih Uddin Butt</p>
An inverted pendulum is a challenging underactuated system characterized by nonlinear behavior. Defining an effective control strategy for such a system is challenging. This paper presents an overview of the IP control system augmented by a comparative analysis of multiple control strategies. Linear techniques such as linear quadratic regulators (LQR) and progressing to nonlinear methods such as Sliding Mode Control (SMC) and back-stepping (BS), as well as artificial intelligence (AI) methods such as Fuzzy Logic Controllers (FLC) and SMC based Neural Networks (SMCNN). These strategies are studied and analyzed based on multiple parameters. Nonlinear techniques and AI-based approaches play key roles in mitigating IP nonlinearity and stabilizing its unbalanced form. The aforementioned algorithms are simulated and compared by conducting a comprehensive literature study. The results demonstrate that the SMCNN controller outperforms the LQR, SMC, FLC, and BS in terms of settling time, overshoot, and steady-state error. Furthermore, SMCNN exhibit superior performance for IP systems, albeit with a complexity trade-off compared to other techniques. This comparative analysis sheds light on the complexity involved in controlling the IP while also providing insights into the optimal performance achieved by the SMCNN controller and the potential of neural network for inverted pendulum stabilization.Intelligent control decision integrating fuzziness and randomness for automatic management of cash flowHongli WangLiguo FeiYuqiang Feng10.1371/journal.pone.02927482024-03-01T14:00:00Z2024-03-01T14:00:00Z<p>by Hongli Wang, Liguo Fei, Yuqiang Feng</p>
Automatic management of cash flow from the perspective of cybernetics decisions can improve work efficiency and accuracy of cash flow management. Disadvantage of traditional fuzzy control method is that it only expresses fuzziness and ignores randomness. The automatic management of cash flow involves variables representing the fuzziness and randomness of human cognition which need new calculation methods to solve. Based on fuzzy control this paper proposes a cloud set control decision method for cash flow management. Cloud set and its <i>I</i> operation and <i>P</i> operation are described. Methods are studied including observation variables and control variables, fuzziness of observation variables and control variables, description of rules, and cloud reasoning based on cloud set. The method is applied successfully in automatic management of cash flow in which control amount of expenditure intensity is -2.285. It is shown that this method can effectively obtain reasonable control quantities considering fuzzy and random properties by the comparison with fuzzy control method. The method for automatic management of cash flow proposed has greater objectivity and effectiveness for the integration of fuzzy and randomness representing human cognition and decision.Security load frequency control model of interconnected power system based on deception attackXin SunQiuhang TangQianyi Lu10.1371/journal.pone.02988892024-02-29T14:00:00Z2024-02-29T14:00:00Z<p>by Xin Sun, Qiuhang Tang, Qianyi Lu</p>
The interconnected power system connects the power grids of different regions through transmission lines, achieving power interconnection and resource sharing. However, data is transmitted through open power networks and is more susceptible to network attacks. To improve the stability of interconnected power systems under deception attacks, three scenarios of system security load frequency control were studied. Based on the construction of a dynamic model of load frequency control, an event-triggered strategy was used to reduce the communication frequency between nodes, resulting in a reduction in the amount of network transmission data. A sliding mode controller was constructed to solve the problem of event-triggered sliding mode security load frequency control. Elastic event-triggered sliding mode load frequency control for interconnected power systems under mixed attacks. The simulation results showed that using the load frequency control model triggered by events, the load frequency deviation of the interconnected power system can be stabilized at around 12 seconds, effectively saving the cost of network resources. Under the regulation of the load frequency control model based on sliding mode control, the interconnected power system stabilized in 10 seconds, reducing the load of network transmission. The elastic event-triggered sliding mode load frequency control model can ensure stable transmission of power data under various attacks and has good anti-interference performance. The results of this study have played an important role in achieving the stability of power resource supply. Compared with previous studies on individual power systems, this study solves the attack problem of interconnected power systems and considers the frequency control problem of system security loads under mixed attacks, enabling the system to recover stability faster.Nonlinear control of two-stage single-phase standalone photovoltaic systemAdil LatifLaiq KhanShahrukh AghaSidra MumtazJamshed Iqbal10.1371/journal.pone.02976122024-02-08T14:00:00Z2024-02-08T14:00:00Z<p>by Adil Latif, Laiq Khan, Shahrukh Agha, Sidra Mumtaz, Jamshed Iqbal</p>
This paper presents a single-phase Photovoltaic (PV) inverter with its superior and robust control in a standalone mode. Initially, modeling and layout of the Buck-Boost DC-DC converter by adopting a non-linear Robust Integral Back-stepping controller (RIBSC) is provided. The controller makes use of a reference voltage generated through the regression plane so that the operating point corresponding to the maximum power point (MPP) could be achieved through the converter under changing climatic conditions. The other main purpose of the Buck-Boost converter is to act like a transformer and produce an increased voltage at the inverter input whenever desired. By not using a transformer makes the circuit size more compact and cost-effective. The proposed RIBSC is applied to an H-bridge inverter with an LC filter to produce the sinusoidal wave in the presence of variations in the output to minimize the difference between the output voltage and the reference voltage. Lyapunov stability criterion has been used to verify the stability and finite-time convergence of the overall system. The overall system is simulated in MATLAB/Simulink to test the system performance with different loads, varying climatic conditions and inverter reference voltages. The proposed methodology is compared with a back-stepping controller and Proportional Integral Derivative (PID) controller under rapidly varying climatic conditions. Results demonstrated that the proposed technique yielded a tracking time of 0.01s, a total harmonic distortion of 9.71% and a root means square error of 0.3998 in the case of resistive load thus showing superior control performance compared to the state-of-the-art control techniques.CyVerse: Cyberinfrastructure for open scienceTyson L. SwetnamParker B. AntinRyan BartelmeAlexander BuckschDavid CamhyGreg ChismIllyoung ChoiAmanda M. CookseyMichele CosiCindy CowenMichael Culshaw-MaurerRobert DaveySean DaveyUpendra DevisettyTony EdginAndy EdmondsDmitry FedorovJeremy FradyJohn FonnerJeffrey K. GillanIqbal HossainBlake JoyceKonrad LangTina LeeShelley LittinIan McEwenNirav MerchantDavid MicklosAndrew NelsonAshley RamseySarah RobertsPaul SarandoEdwin SkidmoreJawon SongMary Margaret SprinkleSriram SrinivasanDan StanzioneJonathan D. StrootmanSarah StryeckReetu TutejaMatthew VaughnMojib WaliMariah WallRamona WallsLiya WangTodd WickizerJason WilliamsJohn WregglesworthEric Lyons10.1371/journal.pcbi.10112702024-02-07T14:00:00Z2024-02-07T14:00:00Z<p>by Tyson L. Swetnam, Parker B. Antin, Ryan Bartelme, Alexander Bucksch, David Camhy, Greg Chism, Illyoung Choi, Amanda M. Cooksey, Michele Cosi, Cindy Cowen, Michael Culshaw-Maurer, Robert Davey, Sean Davey, Upendra Devisetty, Tony Edgin, Andy Edmonds, Dmitry Fedorov, Jeremy Frady, John Fonner, Jeffrey K. Gillan, Iqbal Hossain, Blake Joyce, Konrad Lang, Tina Lee, Shelley Littin, Ian McEwen, Nirav Merchant, David Micklos, Andrew Nelson, Ashley Ramsey, Sarah Roberts, Paul Sarando, Edwin Skidmore, Jawon Song, Mary Margaret Sprinkle, Sriram Srinivasan, Dan Stanzione, Jonathan D. Strootman, Sarah Stryeck, Reetu Tuteja, Matthew Vaughn, Mojib Wali, Mariah Wall, Ramona Walls, Liya Wang, Todd Wickizer, Jason Williams, John Wregglesworth, Eric Lyons</p>
CyVerse, the largest publicly-funded open-source research cyberinfrastructure for life sciences, has played a crucial role in advancing data-driven research since the 2010s. As the technology landscape evolved with the emergence of cloud computing platforms, machine learning and artificial intelligence (AI) applications, CyVerse has enabled access by providing interfaces, Software as a Service (SaaS), and cloud-native Infrastructure as Code (IaC) to leverage new technologies. CyVerse services enable researchers to integrate institutional and private computational resources, custom software, perform analyses, and publish data in accordance with open science principles. Over the past 13 years, CyVerse has registered more than 124,000 verified accounts from 160 countries and was used for over 1,600 peer-reviewed publications. Since 2011, 45,000 students and researchers have been trained to use CyVerse. The platform has been replicated and deployed in three countries outside the US, with additional private deployments on commercial clouds for US government agencies and multinational corporations. In this manuscript, we present a strategic blueprint for creating and managing SaaS cyberinfrastructure and IaC as free and open-source software.Foldy: An open-source web application for interactive protein structure analysisJacob B. RobertsAlberto A. NavaAllison N. PearsonMatthew R. InchaLuis E. ValenciaMelody MaAbhay RaoJay D. Keasling10.1371/journal.pcbi.10111712024-02-02T14:00:00Z2024-02-02T14:00:00Z<p>by Jacob B. Roberts, Alberto A. Nava, Allison N. Pearson, Matthew R. Incha, Luis E. Valencia, Melody Ma, Abhay Rao, Jay D. Keasling</p>
Foldy is a cloud-based application that allows non-computational biologists to easily utilize advanced AI-based structural biology tools, including AlphaFold and DiffDock. With many deployment options, it can be employed by individuals, labs, universities, and companies in the cloud without requiring hardware resources, but it can also be configured to utilize locally available computers. Foldy enables scientists to predict the structure of proteins and complexes up to 6000 amino acids with AlphaFold, visualize Pfam annotations, and dock ligands with AutoDock Vina and DiffDock.
In our manuscript, we detail Foldy’s interface design, deployment strategies, and optimization for various user scenarios. We demonstrate its application through case studies including rational enzyme design and analyzing proteins with domains of unknown function. Furthermore, we compare Foldy’s interface and management capabilities with other open and closed source tools in the field, illustrating its practicality in managing complex data and computation tasks. Our manuscript underlines the benefits of Foldy as a day-to-day tool for life science researchers, and shows how Foldy can make modern tools more accessible and efficient.A lightweight attribute-based signcryption scheme based on cloud-fog assisted in smart healthcareYanzhong SunXiaoni DuShufen NiuSiwei Zhou10.1371/journal.pone.02970022024-01-30T14:00:00Z2024-01-30T14:00:00Z<p>by Yanzhong Sun, Xiaoni Du, Shufen Niu, Siwei Zhou</p>
In the environment of big data of the Internet of Things, smart healthcare is developed in combination with cloud computing. However, with the generation of massive data in smart healthcare systems and the need for real-time data processing, traditional cloud computing is no longer suitable for resources-constrained devices in the Internet of Things. In order to address this issue, we combine the advantages of fog computing and propose a cloud-fog assisted attribute-based signcryption for smart healthcare. In the constructed “cloud-fog-terminal” three-layer model, before the patient (data owner)signcryption, it first offloads some heavy computation burden to fog nodes and the doctor (data user) also outsources some complicated operations to fog nodes before unsigncryption by providing a blinded private key, which greatly reduces the calculation overhead of resource-constrained devices of patient and doctor, improves the calculation efficiency. Thus it implements a lightweight signcryption algorithm. Security analysis confirms that the proposed scheme achieves indistinguishability under chosen ciphertext attack and existential unforgeability under chosen message attack if the computational bilinear Diffie-Hellman problem and the decisional bilinear Diffie-Hellman problem holds. Furthermore, performance analysis demonstrates that our new scheme has less computational overhead for both doctors and patients, so it offers higher computational efficiency and is well-suited for application scenarios of smart healthcare.A lightweight and robust authentication scheme for the healthcare system using public cloud serverIrshad Ahmed AbbasiSaeed Ullah JanAbdulrahman Saad AlqahtaniAdnan Shahid KhanFahad Algarni10.1371/journal.pone.02944292024-01-30T14:00:00Z2024-01-30T14:00:00Z<p>by Irshad Ahmed Abbasi, Saeed Ullah Jan, Abdulrahman Saad Alqahtani, Adnan Shahid Khan, Fahad Algarni</p>
Cloud computing is vital in various applications, such as healthcare, transportation, governance, and mobile computing. When using a public cloud server, it is mandatory to be secured from all known threats because a minor attacker’s disturbance severely threatens the whole system. A public cloud server is posed with numerous threats; an adversary can easily enter the server to access sensitive information, especially for the healthcare industry, which offers services to patients, researchers, labs, and hospitals in a flexible way with minimal operational costs. It is challenging to make it a reliable system and ensure the privacy and security of a cloud-enabled healthcare system. In this regard, numerous security mechanisms have been proposed in past decades. These protocols either suffer from replay attacks, are completed in three to four round trips or have maximum computation, which means the security doesn’t balance with performance. Thus, this work uses a fuzzy extractor method to propose a robust security method for a cloud-enabled healthcare system based on Elliptic Curve Cryptography (ECC). The proposed scheme’s security analysis has been examined formally with BAN logic, ROM and ProVerif and informally using pragmatic illustration and different attacks’ discussions. The proposed security mechanism is analyzed in terms of communication and computation costs. Upon comparing the proposed protocol with prior work, it has been demonstrated that our scheme is 33.91% better in communication costs and 35.39% superior to its competitors in computation costs.Load balance -aware dynamic cloud-edge-end collaborative offloading strategyYueqi Fan10.1371/journal.pone.02968972024-01-12T14:00:00Z2024-01-12T14:00:00Z<p>by Yueqi Fan</p>
Cloud-edge-end (CEE) computing is a hybrid computing paradigm that converges the principles of edge and cloud computing. In the design of CEE systems, a crucial challenge is to develop efficient offloading strategies to achieve the collaboration of edge and cloud offloading. Although CEE offloading problems have been widely studied under various backgrounds and methodologies, load balance, which is an indispensable scheme in CEE systems to ensure the full utilization of edge resources, is still a factor that has not yet been accounted for. To fill this research gap, we are devoted to developing a dynamic load balance -aware CEE offloading strategy. First, we propose a load evolution model to characterize the influences of offloading strategies on the system load dynamics and, on this basis, establish a latency model as a performance metric of different offloading strategies. Then, we formulate an optimal control model to seek the optimal offloading strategy that minimizes the latency. Second, we analyze the feasibility of typical optimal control numerical methods in solving our proposed model, and develop a numerical method based on the framework of genetic algorithm. Third, through a series of numerical experiments, we verify our proposed method. Results show that our method is effective.Novel enterprises digital transformation influence empirical studyXiaowen SunWenjing SunZheng Wang10.1371/journal.pone.02966932024-01-12T14:00:00Z2024-01-12T14:00:00Z<p>by Xiaowen Sun, Wenjing Sun, Zheng Wang</p>
With the rapid development of technologies such as cloud computing and big data, various levels of government departments in the country have successively introduced digital subsidy policies to promote enterprises’ digital transformation. However, the effectiveness of these policies and their ability to truly achieve policy objectives have become pressing concerns across society. Against this backdrop, this paper employs a moderated mediation effects model to empirically analyze the incentive effects of financial subsidies on the digital transformation of A-share listed manufacturing companies in the Shanghai and Shenzhen stock markets from 2013 to 2022. The research findings indicate a significant promotion effect of financial subsidies on the digital transformation of manufacturing enterprises, especially demonstrating a notable incentive impact on the digital transformation of large enterprises, non-asset-intensive enterprises, technology-intensive enterprises, and non-labor-intensive enterprises. However, the incentive effect on the digital transformation of small and medium-sized enterprises (SMEs), asset-intensive enterprises, non-technology-intensive enterprises, and labor-intensive enterprises is not significant. Notably, the expansion of financial subsidies positively influences the augmentation of R&D investment within manufacturing enterprises, subsequently providing indirect encouragement for their digital transformation. Additionally, the incorporation of the degree of marketization implies its potential to moderate both the direct and indirect impacts of financial subsidies on enterprise digital transformation. This study enriches the research on the mechanism of the role of financial subsidies in digital transformation and provides empirical evidence on how market participation influences the effects of financial subsidies, thereby assisting policymakers in comprehensively understanding the impact of financial subsidy policies on different types of enterprises.Research on military-civilian collaborative innovation of science and technology based on a stochastic differential game modelXin LiangYunjuan LiangWeijia KangHua Wei10.1371/journal.pone.02926352024-01-05T14:00:00Z2024-01-05T14:00:00Z<p>by Xin Liang, Yunjuan Liang, Weijia Kang, Hua Wei</p>
The construction of an integrated national strategic system and capability is an essential goal of implementing the strategy of military-civilian integration in the contemporary era. And the collaborative innovation of military-civilian S&T is an inevitable choice to achieve this goal. Due to the dynamic, complex, and stochastic characteristics of military-civilian S&T collaborative innovation, the level of S&T innovation is highly volatile. This paper takes the internal and external stochastic disturbance factors of military-civilian S&T collaborative innovation as the perspective, studies the strategy selection problem of military-civilian S&T collaborative innovation under military domination, constructs a differential game model to explore the innovation strategies under the non-cooperative model without military subsidies, the non-cooperative model with military subsidies, and the collaborative model. Finally, we use numerical experiments to verify the validity of the conclusions. The study shows that: (1) Within a reasonable range of values of the benefit distribution coefficient, the system can achieve the Pareto optimum, and the collaborative model is conducive to improving the S&T innovation level and the optimum benefit level of the system. (2) Military subsidies can increase the benefits of the system and the parties involved to achieve Pareto improvement. (3) The level of S&T innovation under the collaborative model has dynamic evolutionary characteristics of maximum expectation and variance. As the intensity of disturbance increases, the stability of the system may be destroyed. Risk-averse civil enterprises prefer the cooperative mode, whereas risk-averse civil enterprises prefer the non-cooperative model.Geometric analysis of non-degenerate shifted-knots Bézier surfaces in Minkowski spaceSadia BashirDaud Ahmad10.1371/journal.pone.02963652024-01-03T14:00:00Z2024-01-03T14:00:00Z<p>by Sadia Bashir, Daud Ahmad</p>
In this paper, we investigate the properties of timelike and spacelike shifted-knots Bézier surfaces in Minkowski space-E 1 3. These surfaces are commonly used in mathematical models for surface formation in computer science for computer-aided geometric design and computer graphics, as well as in other fields of mathematics. Our objective is to analyze the characteristics of timelike and spacelike shifted-knots Bézier surfaces in Minkowski space-E 1 3. To achieve this, we compute the fundamental coefficients of shifted-knots Bézier surfaces, including the Gauss-curvature, mean-curvature, and shape-operator of the surface. Furthermore, we present numerical examples of timelike and spacelike bi-quadratic (<i>m</i> = <i>n</i> = 2) and bi-cubic (<i>m</i> = <i>n</i> = 3) shifted-knots Bézier surfaces in Minkowski space-E 1 3 to demonstrate the applicability of the technique in Minkowski space.