On-line Computer Research Articles

New insights into the South China Sea throughflow and water budget seasonal cycle: evaluation and analysis of a high-resolution configuration of the ocean model SYMPHONIE version 2.4

Abstract. The South China Sea throughflow (SCSTF) connects the South China Sea (SCS) with neighboring seas and oceans, transferring surface water of the global thermohaline circulation between the Pacific and Indian oceans. A configuration of the SYMPHONIE ocean model at high resolution (4 km) and including an explicit representation of tides is implemented over this region, and a simulation is analyzed over 2010–2018. Comparisons with in situ and satellite data and other available simulations at coarser resolution show the good performance of the model and the relevance of the high resolution for reproducing the spatial and temporal variability of the characteristics of surface dynamics and water masses over the SCS. The added value of an online computation of each term of the water, heat, and salt SCS budgets (surface, lateral oceanic and river fluxes, and internal variations) is also quantitatively demonstrated: important discards are obtained with offline computation, with relative biases of ∼40 % for lateral oceanic inflows and outflows. The SCS water volume budget, including the SCSTF, is analyzed at climatological and seasonal scales. The SCS receives on average a 4.5 Sv yearly water volume input, mainly from the Luzon Strait. It laterally releases this water to neighboring seas, mainly to the Sulu Sea through Mindoro Strait (49 %), to the East China Sea via Taiwan Strait (28 %), and to the Java Sea through Karimata Strait (22 %). The seasonal variability of this water volume budget is driven by lateral interocean exchanges. Surface interocean exchanges, especially at Luzon Strait, are all driven by monsoon winds that favor winter southwestward flows and summer northeastward surface flows. Exchanges through Luzon Strait deep layers show a stable sandwiched structure with vertically alternating inflows and outflows. Last, differences in flux estimates induced by the use of a high-resolution model vs. a low-resolution model are quantified.

A comprehensive high‐level automated driving assistance system with integrated multi‐functionality

AbstractAdvanced Driver Assistance Systems (ADAS) have gained substantial attention in recent years. However, the integration mechanism of multiple functions within ADAS remains unexplored, and the full potential of its functionality remains underutilised. This paper presents a novel multi‐functional integrated High‐level Automated Driving Assistance System that combines the Cruise Control (CC), Adaptive Cruise Control (ACC), Automated Emergency Brake (AEB), and Automated Lane Change (ALC) functions. The presented system utilises a hierarchical framework. The extension multi‐mode switch strategy is established as the superior module and the Event‐Triggered Model Predictive Controller (ETMPC) is designed as the inferior controller. The CC, ACC, and ALC functions are effectively utilised to enhance traffic efficiency, while the AEB function ensures driving safety. To address the time constraints of conventional Model Predictive Control, an event‐trigger mechanism is proposed to reduce computational load. Simulations are conducted using the CarSim and Matlab platforms. The study results demonstrate significant improvements in both safety and traffic efficiency compared to conventional ADAS strategies. Furthermore, the proposed ETMPC method significantly reduces the frequency of solving Optimisation Problems and decreases online computation costs.

Real-time operation strategy of virtual power plants with optimal power disaggregation among heterogeneous resources

The virtual power plant (VPP) can aggregate flexible resources on the demand side to provide frequency regulation for the grid, helping address the supply–demand balance challenges. When deploying regulation, the VPP disaggregates the requested power adjustment in real time among its internal heterogeneous resources. Achieving optimal power disaggregation in this process is challenging due to the temporal coupling characteristics of the resources, the uncertain regulation signals, and the requirement for fast response. Therefore, existing research relies on heuristic methods, such as proportional disaggregation, and fails to leverage the heterogeneity of multiple resources. Here, we propose an optimal operation strategy for VPPs to provide regulation, exploiting the complementary characteristics of heterogeneous resources by prioritising the use of low-cost resources while considering temporal coupling. To reduce the computational overhead of online deployment, we further propose a fast disaggregation algorithm to eliminate the reliance on optimisation solvers. We conducted case studies on the operation of a VPP composed of resources including thermostatically controlled loads and industrial production processes. The results verified the reduced operation cost and increased profit of the VPP under the proposed strategy, with only milliseconds of online computation time. We believe that our work can help better exploit demand-side flexibility.

Measuring Change in Undergraduate Students’ Attitudes towards On-line Exams Depending on Gender and Some Technological Variables

The purpose of this study is to determine and compare how undergraduate students’ attitudes towards on-line exams vary depending on gender and some technological variables. This study was carried out by using a survey method. As data collection tool, the Undergraduate Students Attitude Scale Towards On-line Exams which consists of 21 items, each with five response alternatives covering attitudes of undergraduate students towards on-line exams was used. Scale was developed by Ocak & Karakuş (2022).In this research, scale was administered to 1361 undergraduate school students from four different universities 2020–2021 academic year in Turkey. The convenience sampling method was used for selecting participants. The data were analyzed by One-Way ANOVA and independent-sample t- tests using a statistical package program (SPSS 10.0). As a result, Wi-Fi-using undergraduate students had higher attitude scores in Taking Precautions, Individual Characteristics dimensions and in total scores of USASOE. Female undergraduate students had higher attitude scores in the Taking Precautions dimension. Moreover, students who spend more hours on the internet had higher attitude scores and in on-line exams computer using students also had higher attitudes.Finally, in the Taking Precautions dimension, students who always or sometimes attend on-line courses had more positive attitudes than the ones who never attend on-line courses.

Online Determination of Grid Impedance Spectrum through Pseudo-Random Excitation of a Pulse Width Modulator

The last decade has seen a dramatic rise in renewable energy converters connected to the grid, consisting mostly of intermittent distributed generators on the medium or low voltage grid. Due to this evolution in energy transmission, improved monitoring and control of the distribution grid is becoming mandatory in order to efficiently integrate the new power sources and guarantee power quality, efficiency and reliability. Our paper describes a reliable and precise power grid impedance estimation method using an innovative scheme to control the Pulse Width Modulator’s pulse pattern on the inverters, in order to inject broad spectrum identification patterns. The generated harmonics and inter-harmonics will allow the online computation of the complete spectrum of the grid impedance at the Point of Common Coupling during normal operation. Simulations in typical grid situations verify that the proposed algorithm is robust to a realistic environment and can be used for automated feedback control.

Early Detection of Voltage Instability in Distribution System utilizing Phasor Measurement Units

Power system automation leads to a great jump in detecting and solving the system problems. Due to the serious problems of system voltage collapse, an early prediction online voltage instability detector is discussed in this paper. The voltage instability detector utilizes the voltage and current phasor readings of connected phasor measurement units to the distribution terminals. The detector works according to two parallel algorithms. The first algorithm is a comparison for terminal current and voltage phasors with an offline calculated Look-up table, in which particle swarm optimization technique is used. The Look-up table represents the permissible maximum current and minimum voltage phasors for each terminal. The second algorithm is based on the online computation of the ratio of the Thevenin equivalent system impedance to the terminal load impedance. The simulated voltage detector is applied to two different unified power systems. It gives good and reasonable results.

Metastable nickel–oxygen species modulate rate oscillations during dry reforming of methane

AbstractWhen a heterogeneous catalyst is active, it forms metastable structures that constantly transform into each other. These structures contribute differently to the catalytic function. Here we show the role of different metastable oxygen species on a Ni catalyst during dry reforming of methane by combining environmental scanning electron microscopy, near ambient pressure X-ray photoelectron spectroscopy, on-line product detection and computer vision. We highlight the critical role of dissociative CO2 adsorption in regulating the oxygen content of the catalyst and in CH4 activation. We also discover rate oscillations during dry reforming of methane resulting from the sequential transformation of metastable oxygen species that exhibit different catalytic properties: atomic surface oxygen, subsurface oxygen and bulk NiOx. The imaging approach allowed the localization of fluctuating surface regions that correlated directly with catalytic activity. The study highlights the importance of metastability and operando analytics in catalysis science and provides impetus towards the design of catalytic systems.

Chaos and stability of a fractional model of the cyber ecosystem

<p>The widespread use of computer hardware and software in society has led to the emergence of a type of criminal conduct known as cybercrime, which has become a major worldwide concern in the 21st century spanning multiple domains. As a result, in the present setting, academics and practitioners are showing a great deal of interest in conducting research on cybercrime. In this work, a fractional-order model was replaced by involving three sorts of human populations: online computer users, hackers, and cyber security professionals, in order to examine the online computer user-hacker system. The existence, uniqueness and boundedness were studied. To support our theoretical conclusions, a numerical analysis of the influence of the various logical parameters was conducted and we derived the necessary conditions for the different equilibrium points to be locally stable. We examined the effects of the fear level and refuge factor on the equilibrium densities of prey and predators in order to explore and understand the dynamics of the system in a better way. Using some special circumstances, the model was examined. Our theoretical findings and logical parameters were validated through a numerical analysis utilizing the generalized Adams-Bashforth-Moulton technique.</p>

ANALYSIS OF THE CURRENT STATE OF TRAINING LINGUISTS USING INFORMATION TECHNOLOGY

This article analyzes the current state of linguists' education with an emphasis on the use of information technologies in the educational process. In the modern world, information technology has become an integral part of education, and linguistics is no exception. The article examines various aspects of the use of information technology in teaching linguists, including online resources, computer programs, artificial intelligence and other innovative methods. The author of the article analyzes the current trends and challenges faced by students and teachers of linguistic programs when integrating information technologies into the educational process. The article also examines the benefitsthat can be obtained from the use of modern technologies in the training of linguists, such as improving the availability of educational materials, improving the effectiveness of teaching and developing research skills in the field of linguistics. In conclusion, the article provides recommendations for educational institutions and teachers of linguistics on the optimal use of information technologies in the educational process in order to provide a better and modern education for future linguists.

Development of a Distributed Adaptive Dual MPC Scheme with Application to Control of an Octuple Tank System

The distributed model predictive control (dMPC) provides a computationally efficient framework for designing controllers for a large dimensional plant. The performance of such dMPC scheme critically depends upon the quality of the control relevant models used for predictions. In continuously operated processes, model plant mismatch (MPM) arises due to the time-varying nature of process parameters and shift in the operating conditions due to economic considerations and this results in performance degradation. Recently an adaptive version of dMPC (dAMPC) has been developed that achieves better control performance using online model parameter update. A conventional adaptive MPC scheme, however, requires external dither signal to be injected to generate sufficient excitation needed for parameter estimation. In this work, dAMPC is cast in the dual control framework (dADMPC) which ensured sufficient input excitation as and when needed for better online parameter estimation. The proposed controller is based on black-box models parameterized using generalized orthogonal basis filters (GOBF). The Fourier coefficients of the GOBF models are dynamically updated online using recursive parameter estimators to account for MPM. The efficacy of the proposed scheme is demonstrated by simulating servo and regulatory problems associated with the benchmark octuple tank process. The simulation study reveals that performance of the proposed dADMPC scheme is comparable to a centralized ADMPC while achieving a considerable reduction in the online computation time.

Finite-Horizon H∞ State Estimation for Complex Networks With Uncertain Couplings and Packet Losses: Handling Amplify-and-Forward Relays.

This article is concerned with the state estimation problem for a class of complex networks (CNs) with uncertain inner couplings and packet losses over communication networks. The inner couplings are allowed to be uncertain and varying in a specific interval. The amplify-and-forward (AaF) relay protocols are introduced to improve the communication quality and enhance the propagation distance. The Bernoulli random variables are used to characterize the randomly occurring packet losses encountered in communication channels. The focus of this article is on the design of a state estimator for each node of CNs such that a prescribed H∞ performance constraint is satisfied for the dynamical error system over a finite horizon. A sufficient condition is first provided to verify the existence of the desired H∞ state estimator, and the estimator gain is then determined by solving two coupled backward Riccati difference equations (RDEs). Subsequently, a recursive state estimation algorithm is put forward that is suitable for online computation. Finally, a numerical example is given to demonstrate the effectiveness of the proposed estimation method.

Evaluation of Chrisofix® Chest Orthosis Application in Patients with Traumatic Rib Fractures

Background: The Chrisofix® Chest Orthosis is an effective and easy to use device for the treatment of rib fractures. It is used as a supportive treatment to reduce the pain levels and complication risks of the patients.
 Methods: Patients hospitalized with the diagnosis of rib fractures in the Thoracic Surgery Service of a university hospital were retrospectively scanned in an online computer program between October 2018 and October 2021. The study sample consisted of patients with the treatment (30) and control (30) groups.
 Results: Visual Analog Scale and incidence of atelectasis of the patients in the experimental group (The Chrisofix® Chest Orthosis) is statistically significantly lower than the control group (P < 0.05). In both the experimental and control groups, no statistically significant difference was found between the variables of patient’s demographic and clinical characteristics (p > 0.05).
 Conclusions: In the study, with the use of The Chrisofix® Chest Orthosis, a significant decrease was observed in the Visual Analog Scale and the incidence of atelectasis.
 Bangladesh Journal of Medical Science Vol. 23 No. 01 January’24 Page : 83-88

Reliable Model Predictive Vibration Control for Structures with Nonprobabilistic Uncertainties

This paper proposes a novel reliable model predictive control (MPC) method for active vibration control of structure with nonprobabilistic uncertainties. First, the framework of reliable MPC is established by integrating nonprobabilistic reliability constraints into nominal MPC. Based on the first‐order Taylor expansion and first‐passage theory, an efficient nonprobabilistic reliability analysis method that is suitable for online computation is proposed. A nonprobabilistic Kalman filter is further proposed for determine system states and their uncertain region. Unlike most robust MPC approaches, the proposed reliable MPC focuses on the satisfaction of state constraints in terms of structural reliability and is more suitable for structures with stringent safety requirements. Compared to existing reliability‐based vibration control methods, reliable MPC requires no knowledge of disturbance and exhibits greater adaptability to load environments. The effectiveness and superiority of the proposed reliable MPC are validated through a numerical example and an engineering case study.

Fast Online Computation of MPC-based Integrated Decision Control for Autonomous Vehicles

Fast Online Computation of MPC-based Integrated Decision Control for Autonomous Vehicles

Optimal DoS attack on multi-channel cyber-physical systems: A Stackelberg game analysis

In this commentary, optimal denial-of-service (DoS) attack strategies on multi-channel cyber-physical systems (CPSs) are considered, which focus on energy allocation on communication channels. For simplicity, a Stackelberg game between one defender and one attacker is constructed. Compared with the existing literature, which mainly pay attention to static equilibrium, the dynamic process of the game is also exhibited in this paper, which fills the gap in the demonstration of dynamic decision-making between both players of the game. In the solution of Stackelberg equilibrium, a self-adaptive particle swarm optimization (PSO) algorithm with Sigmoid-like update function is applied to cope with the nonlinearity of the reward function with faster convergence and wider adaptability. Besides, to acquire better performance of both sides to allocate energy, an online computation algorithm is proposed for dynamic Stackelberg game. Finally, numerical examples are provided to illustrate similarities between theoretic static equilibrium and optimal strategies obtained by Monte Carlo simulations.

Approximate SDD-TMPC with Spiking Neural Networks: An Application to Wheeled Robots

Model Predictive Control (MPC) optimizes an objective function within a prediction window under constraints. In the presence of bounded disturbances, robust versions are used. Recently, a promising robust MPC was introduced that outperforms SOTA approaches. However, solving the optimization problem online is computationally expensive. An efficient approximation method, such as neural networks (NN), can be substituted to accelerate the online computation. There are discrepancies between the control inputs due to the approximation. We propose to model them as bounded state-dependent disturbances to robustly control nonlinear wheeled robots. We consider a spiking NN to ensure that small robots could use it.

Ganoderma adspersum (Ganodermataceae): Investigation of Its Secondary Metabolites and the Antioxidant, Antimicrobial, and Cytotoxic Potential of Its Extracts.

Ganoderma is a genus of wood-degrading mushrooms with medicinal importance. Most Ganoderma species have been studied extensively for their secondary metabolites, biological activities, and ecological value. In this study, the biological activities of the extracts of G. adspersum growing wild on Morus alba trees in the region of Western Thrace (Greece) were evaluated, and the petroleum ether, dichloromethanolic, and methanolic extracts were studied further for their secondary metabolites. Six substances were isolated by chromatographic (Clumn Chromatography (C.C.), High Performance Liquid Chromatography (HPLC)) and spectroscopic methods (Nuclear Magnetic Resonance (NMR)), which were classified in the following categories: (a) unsaturated fatty acids: cis-oleic acid (1); (b) sterols: ergosta-7,22-dien-3-one (2), ergosta-7,22-dien-3-ol (3), and ergosta-5,7,22-trien-3-ol (4); and (c) lanostane-type triterpenoids: applanoxidic acid G (5) and applanoxidic acid A (6). Finally, the biological activities of the extracts were estimated for their antioxidant, antimicrobial, and cytotoxic potential. The methanolic extract of G. adspersum showed the highest total antioxidant activity. The results of the antimicrobial activities indicated that all of the extracts had a minimum inhibitory concentration (MIC) ranging between 39.1 and 312.5 μg/mL. The evaluation of the cytotoxic activity of the samples showed once again that the methanolic extract was the most potent among the examined extracts, with half-maximal inhibitory concentration (IC50) values of 19.22 μg/mL (Hep2c cells), 32.9 μg/mL (RD cells), and 8.94 μg/mL (L2OB cells). Moreover, the bioactivity scores of the isolated secondary metabolites were calculated using the online computer software program Molinspiration. The compounds showed promising bioactivity scores for drug targets.

MAINTAINING BRAIN HEALTH VIA TELEHEALTH-BASED CHAIR YOGA FOR RURAL UNDERSERVED OLDER ADULTS

Abstract We conducted a randomized control pilot trial in an underserved, racially/ethnically diverse community, to examine the efficacy of (1) computer literacy training provided by high school students meeting rural older adults in their homes, followed by 2) telehealth-based online chair yoga (OCY) or computer brain games (CBG). First, high school students engaged in a “train the trainer” computer skills course using a previously-tested curriculum designed for the target population. Students mentored the older adults in learning computer skills and to access either the OCY (n = 15) or CBG (n=15), which were randomly assigned. Outcomes measured at pre, post, and three months following the 12-week intervention included computer proficiency, cognitive function, pain levels, and psychosocial well-being. In a linear mixed growth model with random intercepts, there was a significant linear trend in computer-based competency, t(50, 19) = 2.56, p = .013. Computer proficiency (computer basics, Internet and email use, communication, and calendaring) increased significantly in both the OCY and CBG groups. Importantly, there was a significant linear change in pain by group, controlling for age and living alone, F(1, 14) = 6.64, p = .022, η2 = .32 (large effect size). Chronic pain in the OCY group decreased significantly from baseline to 3-month follow-up (18.89 to 11.35) but increased in the CBG group (14.27 to 17.28). Increases in cognitive function increased pre/post t(29) = -2.98, p = .003 (one-tailed). These results are promising for older adults with limited exercise opportunities, who also face cognitive risk exacerbated by elevated pain levels.

Teacher preparation for implementation of E-learning in the educational process of a German high school

The article examines the problem of using electronic learning (E-learning) in the training of future teachers in German universities, which is a fairly new and at the same time promising direction of comparative pedagogy. This problem has gained particularly active development in recent years, which is largely due to the spread of digital forms of education, which were recognized in Germany as a special category of the latest educational technologies. It is assumed that the constant introduction of new pedagogical technologies will provide wider opportunities for the development of pedagogical universities in Germany and maintain competitiveness in the international market of educational services. It is believed that successful e-learning scenarios take into account the necessary didactic conditions of learning in different contexts, such as authentic or social learning contexts, and provide substantial digital support for learning materials. The authors consider the use of digital learning tools, which have a differentiated presentation and characterize the most widespread types of e-learning used in the training of future teachers in Germany, and cover the modern spectrum of posting event scenarios and lecture materials on the Internet for fully virtual teaching, namely: computer online computer training, internet training, blended learning, exclusively virtual training, and distance training on the Internet. An important aspect of e-learning is the tools and media for its implementation, which include software for portals, a system for managing administrative functions (personnel management and student management), course management, a learning platform, and tools for creating and collaborating on a network. E-learning is widely used in German universities; it supports learning processes through the use of various digital technologies that provide operations in various ways. Teachers are offered a choice of teaching and learning scenarios, and the e-semester reserve is aimed at further supporting classroom teaching.

Reflection on Teacher Feedback in Hybrid Teaching of Translation

In the context of the diversity and multi-modality of teaching feedback, the importance of teacher feedback has been impacted by online (computer) feedback and peer feedback, so it's necessary to highlight and give full play to the important role of teacher feedback. After analysis of the characteristics of hybrid translation teaching, the research asserts that all feedback should be given full play to their roles in translation teaching. Teachers are suggested focusing on students' necessities to offer re-feedback and deep feedback by highlighting key and difficult points, meanwhile, to enrich cultural literacy and provide value guidance as well as promoting students to actively perceive, understand and adopt feedback information are the core work of teacher’s feedback to improve translation teaching efficiently and effectively.