System In Order Research Articles

Continuous Time Algebraic Riccati Equation Solution for Second Order Systems

Abstract The continuous time algebraic Riccati equation (ARE) is often utilized in control, estimation, and optimization. For a linear system with a second order structure, the ARE required to be solved to get the control values in standard control problems results in complex sub-equations in terms of the second order system matrices. The computational costs of solving the algebraic Riccati equation through standard methods such as the Hamiltonian matrix pencil approach increase substantially as matrix sizes increase for a second order system, due to the eigendecomposition of the 2n x 2n system matrices involved. This work introduces a new solution that does not require the eigendecomposition of the 2n x 2n system matrices, while satisfying all of the requirements of the solution to the Riccati equation (e.g., detectability, stabilizability, positive semi-definite solution matrix).

Active learning for quantum mechanical measurements

The experimental evaluation of many quantum mechanical quantities requires the estimation of several directly measurable observables, such as local observables. Due to the necessity to repeat experiments on individual quantum systems in order to estimate expectation values of observables, the question of how many repetitions to allocate to a given directly measurable observable arises. We show that an active learning scheme can help to improve such allocations, and the resultant decrease in experimental repetitions required to evaluate a quantity with the desired accuracy increases with the size of the underlying quantum mechanical system. Published by the American Physical Society 2024

Defeating cancer through education, prevention, and youth athletics.

e22548 Background: Barriers to effective scientific learning exists for elementary students, particularly in socially and financially disadvantaged settings. Maintaining interest, concentration and focus can be difficult for children, particularly when confronted with complex material and multiple distractions. Methods: We implemented a scientific educational program for children attending an urban community center after-school program entailing tutoring stations conducted during a basketball practice. Five tutoring stations included human physiology, astronomy, geography, geology and cancer. Five children spend 3 minutes with tutors who are medical students or residents while five other children are on the basketball court going through drills with a coach. After 3 minutes the kids on the court and the kids being tutored switch places. The sequence is repeated until each child has rotated through each of the 5 tutoring stations and through each of the 5 basketball drills. After this, each child rotates through each tutoring station for one minute where they are quizzed on what they were taught and the end of practice scrimmage begins with a score based upon each team of fives’ performance on the quiz. Results: The method proved to be highly effective in the children’s ability to understand and retain scientific concepts. Within weeks nearly every child could list the planets of the solar system in order, calculate their pulse and explain its importance, list the most common symptoms of the most prevalent cancers, correctly identify continents, oceans, countries and states on maps and explain the origin of volcanos, earthquakes, hurricanes and tsunamis. Conclusions: This novel teaching method proved highly effective with children being able to maintain interest, focus and concentration in a setting where physical exertion is rapidly alternated with educational instruction. Parents and teachers commented that the kids learned more in 45 minutes with this method than in 2 weeks of conventional classroom teaching. The approach is widely applicable to students from diverse backgrounds.

Lyapunov Stability Theory for Caputo Fractional Order Systems: The System Comparison Method

Lyapunov Stability Theory for Caputo Fractional Order Systems: The System Comparison Method

Senior-Centric Object Detection for Independent Living

Abstract: The need for creative solutions that help seniors preserve their independence is growing as a result of the worldwide population aging issue. A major obstacle that many seniors encounter is the possibility of a loss in their physical and cognitive abilities, which can make it difficult for them to carry out everyday chores. This study introduces a senior-oriented object detecting system in order to address this urgent problem. The technology assists elderly people in recognizing and locating things in their living areas by utilizing sophisticated computer vision techniques and machine learning algorithms. It aims to improve seniors' safety and autonomy through real-time support, ultimately leading to a better quality of life. This system is carefully designed to accommodate the special requirements of senior citizens, providing a viable means of fostering autonomous live in a population that is aging. This initiative is a big step forward in the fight to empower seniors and improve their well-being in an aging society because of its creative approach and emphasis on user-centric design

Car Price Prediction Using Machine Learning

Abstract: The objective of the "Car Price Prediction Using Machine Learning" project is to anticipate car prices based on pertinent variables by utilizing predictive modelling and advanced data analytics. The rising need for precise and active pricing systems in the automobile sector is addressed by this initiative. The system will evaluate past vehicle data, including brand, model, manufacturing year, the mileage, type of fuel, and other details, by utilizing machine learning techniques. In order to produce specific predictions, the suggested model will be trained on an extensive dataset, noticing patterns and parallels within the data. In order to create a reliable prediction model, the research focuses on using regression techniques, such as ensemble approaches or linear regression. System of measurement like as absolute mean error and R-squared coefficient will be used to evaluate the predicted accuracy of the system in order to regulate its usefulness. If this resourcefulness is employed successfully, it will have a big impact on the automobile business for clients and venders alike by giving them a tool to evaluate fair market prices and helping them make decisions. This study enhances to the body of knowledge in price analysis using machine learning and lays the footing for future improvements in the prognostication of dynamic market trends in the automobile sector.

An Innovative Kot Ordering System for Restaurants

Abstract: This study proposes a digital menu ordering system to address challenges in the restaurant industry's digital transformation. Traditional paper-based methods lead to losses and inefficiencies. The system, using QR codes, enables customers to register, log in, and order online, with features like suggesting popular dishes and online payments. Managers gain real-time oversight of orders, tables, and payments, supported by sales data visualization. By automating tasks, the system reduces errors, enhances service, and streamlines operations, offering a transformative solution to industry challenges in the digital era.

Kinetic Diagram Analysis: A Python Library for Calculating Steady-State Observables of Kinetic Systems Analytically.

Kinetic diagrams are commonly used to represent biochemical systems in order to study phenomena such as free energy transduction and ion selectivity. While numerical methods are commonly used to analyze such kinetic networks, the diagram method by King, Altman and Hill makes it possible to construct exact algebraic expressions for steady-state observables in terms of the rate constants of the kinetic diagram. However, manually obtaining these expressions becomes infeasible for models of even modest complexity as the number of the required intermediate diagrams grows with the factorial of the number of states in the diagram. We developed Kinetic Diagram Analysis ( KDA ), a Python library that programmatically generates the relevant diagrams and expressions from a user-defined kinetic diagram. KDA outputs symbolic expressions for state probabilities and cycle fluxes at steady-state that can be symbolically manipulated and evaluated to quantify macroscopic system observables. We demonstrate the KDA approach for examples drawn from the biophysics of active secondary transmembrane transporters. For a generic 6-state antiporter model, we show how the introduction of a single leakage transition reduces transport efficiency by quantifying substrate turnover. We apply KDA to a real-world example, the 8-state free exchange model of the small multidrug resistance transporter EmrE of Hussey et al ( J General Physiology 152 (2020), e201912437), where a change in transporter phenotype is achieved by biasing two different subsets of kinetic rates: alternating access and substrate unbinding rates. KDA is made available as open source software under the GNU General Public License version 3.

Existence of solutions to a strongly nonlinear elliptic coupled system of finite order

Existence of solutions to a strongly nonlinear elliptic coupled system of finite order

Implementasi Hukum Administrasi Negara Dalam Perspektif Maslahah Mursalah

State administrative law has an important role to create a good and orderly system of government. It is hoped that state administrative law wiil function to expedite the task of administering the state and provide legal guarantees to citizens and protect all people. This is also in line with the objektives of maslahah mursalah, so that the implementation of state administrative law can be integrated with exploring the values of maslahah mursalah. The purpose of this study is to find out how the role of islamic law (maslahah mursalah) in the implementation of state administrative law. The benefit of this research is to find out how far maslahah mursalah is applied to state administrative law. This study uses the usul fiqh approach as an epistemological basis in the application of state administrative law. This research is a qualitative reseach with descriptive analysis and library reseach. The results of this study are to find a common goal between state administrative law and maslahah mursalah, and the effectiveness of implementing state administrative law besed on maslahah mursalah values.

Enhanced real-time road-vehicles’ detection and tracking for driving assistance

Road-object detection, recognition, and tracking are vital tasks that must be performed reliably and accurately by self-driving car systems in order to achieve the automation/autonomy goal. Other vehicles are one of the main objects that the egocar must accurately detect and track on the road. However, deep-learning approaches proved their effectiveness at the expense of very demanding computational power and low throughput. They must be deployed on expensive CPUs and GPUs. Thus, in this work, a lightweight vehicle detection and tracking technique (LWVDT) is suggested to fit low-cost CPUs without sacrificing robustness, speed, or comprehension. The LWVDT is suitable for deployment in both advanced driving assistance systems (ADAS) functions and autonomous-car subsystems. The implementation is a sequence of computer-vision techniques fused together and merged with machine-learning procedures to strengthen each other and streamline execution. The algorithm details and their execution are revealed in detail. The LWVDT processes raw RGB camera pictures to generate vehicle boundary boxes and tracks them from frame to frame. The performance of the proposed pipeline is assessed using real road camera images and video recordings under different circumstances and lighting/shading conditions. Moreover, it is also tested against the well-known KITTI database, achieving an average accuracy of 87%.

Multi-Criteria Optimization of a Laboratory Top-Lit Updraft Gasifier in Order to Reduce Greenhouse Gases and Particulate Matter Emissions

Air pollution from combustion processes is harming human health and the environment. To mitigate this, one needs to adopt cleaner energy production methods, in particular, to optimize combustion systems in order to minimize pollutants and increase efficiency. Flue gas analysis and particulate matter (PM) monitoring, starting from the prototype phase, is crucial to minimize and regulate pollutant emissions. This article analyses the emissions of pollutants and particulate matter from a combustion test gasifier working on the Top-Lit Updraft (TLUD) principle in order to optimize functionality and reduce exhaust emissions. Three experiments were performed in which the primary (gasification) air flow rate (GA) was kept constant at 25 L/min, and the secondary (combustion) air flow rate (CA) was adjusted to obtain a CA/GA ratio of 2 (50 L/min), 3 (75 L/min), and 4 (100 L/min) respectively. Based on a multi-criterial analysis, the optimal CA/GA ratio for TLUD combustion is 3, offering a well-rounded performance in output temperatures, PM and greenhouse gases (GHG) emissions, and efficiency, while the CA/GA ratio of 4 has good PM and GHG emissions performance but lower efficiency, and the CA/GA ratio of 2 is the least favorable due to its poor performance in output temperatures, PM and GHG emissions.

Exploring nonlinearity in quarter car models with an experimental approach to formulating fractional order form and its dynamic analysis.

This study explores the inherent nonlinearity of quarter car models by employing an experimental and numerical approach. The dynamics of vehicular suspension systems are pivotal for ensuring passenger comfort, vehicle stability, and overall ride quality. In this paper we assessed the impact of various parameters and components on suspension performance, enabled the optimization of ride comfort, stability, and handling characteristics. Firstly, experimental analysis allowed for the investigation of factors that are challenging to model theoretically, such as stiffness nonlinearity and damping characteristics, which may vary under different operating conditions. Time domain and frequency response diagram of the model has been obtained. Secondly, a quarter-car with single degree-of-freedom presented and investigated in fractional order form. Fractional order dynamics emphasize nonlinearities in quarter car models, capturing real-world dynamics effectively. The proposed fractional-order nonlinear quarter car model employed Caputo derivative. For numerical analysis of fractional order system, the Adam-Bashforth-Moulton method is used and the disturbance of road assumed to be stochastic. Results show that the dynamic response of the vehicle can be chaotic. Influence of road roughness amplitude and frequency on vehicle vibration is investigated.

Application of mRNA nano-delivery system in CAR-T tumor immunotherapy

Chimeric antigen receptor T cells (CAR-T) immunotherapy, which activates immunity specific to the system in order to achieve antitumor effects, has experienced exciting progress in recent years. mRNA nano-delivery systems, which encapsulate tumor immunotherapy-related antigen mRNA with nanoparticles, have shown great potential in CAR-T tumor immunotherapy. On one hand, these systems can directly target T cells to generate CAR-T cells that directly act upon the corresponding tumor cells. On the other hand, they can be delivered to antigen-presenting cells through targeting, thereby enhancing the function of CAR-T cells and further inducing specific immune responses against tumor cells. This review summarizes the synthesis of mRNA nano-delivery systems and their application in CAR-T tumor immunotherapy.

Toward Sustainable Urban Mobility: A Multidimensional Ontology-Based Framework for Assessment and Consensus Decision-Making Using DS-AHP

Urban mobility is a critical aspect of sustainable urban development, with significant environmental, social, and economic implications. Assessing the sustainability of urban mobility systems in order to create more carbon neutral, liveable, healthier, and sustainable cities and neighborhoods for the future requires a multidimensional approach that integrates diverse factors. However, the lack of a unified assessment framework poses challenges in comparing and evaluating different urban mobility projects. This article proposes an ontology for assessing the sustainability of urban mobility systems. This ontology is based on a multidimensional approach that integrates knowledge from experts in transportation engineering, urban planning, environmental science, and social sciences to incorporate existing sustainability indicators and frameworks, as well as domain-specific knowledge. A consensus approach based on Dempster–Shäfer (DS) and Analytic Hierarchy Process (AHP) methods is proposed to account for uncertainties and to allow for the consideration of preferences and ill judgment. Through a case study in Romania, the authors demonstrated the applicability of the proposal to provide a comprehensive and flexible framework for assessing urban mobility sustainability. The proposed ontology provides a valuable tool for policymakers, urban planners, and transportation engineers to make informed decisions towards sustainable urban mobility, and the sensitivity analysis is carried out to demonstrate the robustness of the proposed framework. It has potential for iterative validation and feedback from domain experts, and can serve as a foundation for future research.

Pengendalian Persediaan Bahan Baku Dengan Metode Material Requirement Planning Pada Produksi Majalah SM PT ABC

PT ABC operates in the printing and publishing sector which produces magazines using a make to order system. The problem that often occurs is related to the fluctuating demand for SM magazines from March 2021 to February 2024. As a result of this condition, the company cannot estimate the amount of raw materials needed, so orders are made based on estimates only. This causes overstock, especially 1001 reams of 58 gram HVS paper. The research objective is to find out planning, inventory control, and ordering techniques that produce minimal costs. In this case, suitable methods to apply are Material Requirement Planning (MRP), lot size Economic Order Quantity (EOQ), Lot For Lot (LFL) and Period Order Quantity (POQ). From the proposed improvements, the minimum cost with Lot For Lot (LFL) was IDR 2.320.000. So, costs can be minimized to IDR 93.260.746 or 98% compared to the method used by the company.

Preparation and Identification of Magnetic Iron Nanoparticle based on a Natural Hydrogel and its Performance in Targeted Drug Delivery

Billions of dollars are spent annually in the world to treat and investigate problems caused by drug side effects. According to the estimates of health researchers, about 40%of people who take medicine suffer from side effects. In this way, the necessity of using a targeted system in order to deliver medicine to the desired place without damaging healthy tissues is felt more than ever. In recent years, targeted drug delivery systems based on nanoparticles have received much attention. Meanwhile, the use of natural polymers is more suitable for various purposes in drug delivery systems in terms of indicating greater biological compatibility with the body and being non-toxic.In this research, the natural hydrogel extracted from the seeds of the Plantago ovata, which is loaded on the bed of magnetic iron nanoparticles, was used to entrap the drugmefenamic acid. In order to achieve this goal, at the beginning, magnetic iron nanoparticles were prepared by co-precipitation method using iron (II) and iron (III) oxides, and then a coating of silica was created on its surface, then the hydrocolloid of Plantago ovata was extracted from its seed, in order to connect the magnetite nanoparticles and the polymer extracted from the Plantago ovata, the surface of both components was modified by vinyl-functional groups. Next, radical polymerization under heat was used to connect the particles and trap the drug, after that the release of the drug from the polymer capsule was checked by UV-Vis device. Before examining the drug release, the resulting product was identified by FT-IR, XRD, VSM, DLS, TGA, SEM analysis. Therefore, the obtained results indicated that the natural polymer was correctly loaded on the desired magnetic substrate and the drug mefenamic acid was trapped inside the hydrogel networks and polymer capsule. Therefore, the drug can be directed in a controlled and targeted manner by the magnetic field, and the release of the drug was done well and at an acceptable speed.

Examining the seniority-based pay system in Korean companies: current trends and its implications for Asian economies

ABSTRACT Human resource management, including the design and implementation of pay systems, is influenced by the specific national context in which it operates. Challenges often arise when HRM practices that have been established in advanced countries are transplanted to developing nations, as they may not fully align with the unique circumstances and cultural dynamics of the target country. Until the 1980s, rapidly growing South Korean companies embraced the seniority-based pay system (SPS) in order to encourage employee tenure. The 1997 IMF foreign currency crisis led to an effort to shift away from this model, which was seen as unrelated to job roles and performance, towards alternative systems. Despite two decades of reforming efforts, SPS pay still prevails, particularly among production workers at large manufacturing companies under trade unions. The workplace panel survey data provides evidence that the implementation of a SPS system does not display any significant negative impact on firm performance, as measured through various methods. As such, the question is not whether to abolish the old system, but instead how to accommodate the new system. The study emphasizes aligning pay systems with the nation’s history, culture and industrialization rather than imposing foreign models.

Opinion formation on evolving network: the DPA method applied to a nonlocal cross-diffusion PDE-ODE system

Abstract We study a system of nonlocal aggregation cross-diffusion PDEs that describe the evolution of opinion densities on a network. The PDEs are coupled with a system of ODEs that describe the time evolution of the agents on the network. Firstly, we apply the Deterministic Particle Approximation (DPA) method to the aforementioned system in order to prove the existence of solutions under suitable assumptions on the interactions between agents. Later on, we present an explicit model for opinion formation on an evolving network. The opinions evolve based on both the distance between the agents on the network and the ’attitude areas’, which depend on the distance between the agents’ opinions. The position of the agents on the network evolves based on the distance between the agents’ opinions. The goal is to study radicalisation, polarisation and fragmentation of the population while changing its open-mindedness and the radius of interaction.

APPLICATION OF MATHEMATICAL MODELS IN THE DIAGNOSIS OF DISEASES OF INTERNAL ORGANS

The application of diagnostic expert systems in medical technology signifies a notable progression, as they provide a computerized framework for decision-support, assisting healthcare practitioners in the process of disease diagnosis. These systems facilitate the integration of patient data, encompassing symptoms and medical history, with a knowledge base in order to produce a comprehensive compilation of potential diagnoses. Through the utilization of knowledge-based methodologies, they enhance these potentialities in order to ascertain the most probable diagnosis. The present study examines expert systems, investigating their historical development, architectural structure, and the approaches utilized for knowledge representation. There is a significant emphasis placed on the advancement and implementation of these systems within the medical industry of Kazakhstan. This paper provides a comprehensive analysis of the benefits and drawbacks associated with diagnostic expert systems, emphasizing their potential to bring about significant advancements in medical fields. The study places significant emphasis on the necessity of developing and conducting thorough testing of these systems in order to improve the precision and effectiveness of medical diagnostics. The statement recognizes the importance of continuous research in order to enhance the design and implementation of these systems in various healthcare settings. This research makes a notable addition by examining optimization theory in the field of medical diagnosis. This study presents novel approaches for effectively addressing the intricacies and uncertainties associated with the diagnosis of complicated disorders. The work presents methodology for navigating the complex field of medical diagnostics by utilizing mathematical modeling and optimization approaches, specifically the gradient projection method. The utilization of diverse ways to tackle qualitative ambiguities in this approach signifies a significant progression inside the domain of diagnostic expert systems.