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Model order reduction (MOR) has been widely used in the electric networks but little has been done to reduce higher index differential algebraic equations (DAEs). The paper aims to discuss these issues.

Most methods first do an index reduction before reducing a higher DAE but this can lead to a loss of physical properties of the system.

The paper presents a MOR method for DAEs called the index-aware MOR (IMOR) which can reduce a DAE while preserving its physical properties such as the index. The feasibility of this method is tested on real-life electric networks.

MOR has been widely used to reduce large systems from electric networks but little has been done to reduce higher index DAEs. Most methods first do an index reduction before reducing a large system of DAEs but this can lead to a loss of physical properties of the system. The paper presents a MOR method for DAEs called the IMOR which can reduce a DAE while preserving its physical properties such as the index. The feasibility of this method is tested on real-life electric networks.

The purpose of this paper is to propose an interpolation-based projection framework for model reduction of quadratic-bilinear systems. The approach constructs projection matrices from the bilinear part of the original quadratic-bilinear descriptor system and uses these matrices to project the original system.

The projection matrices are constructed by viewing the bilinear system as a linear parametric system, where the input associated with the bilinear part is treated as a parameter. The advantage of this approach is that the projection matrices can be constructed reliably by using an a posteriori error bound for linear parametric systems. The use of the error bound allows us to select a good choice of interpolation points and parameter samples for the construction of the projection matrices by using a greedy-type framework.

The results are compared with the standard quadratic-bilinear projection methods and it is observed that the approximations through the proposed method are comparable to the standard method but at a lower computational cost (offline time).

In addition to the proposed model order reduction framework, the authors extend the one-sided moment matching parametric model order reduction (PMOR) method to a two-sided method that doubles the number of moments matched in the PMOR method.

By designing a system dynamics model in the form of a multimodal transportation system, this study for the first time seeks to reduce costs and time, and increase customer satisfaction by considering uncertainties in the intra city transit system, especially demand uncertainty and provide a prototype system to prove the capability of the dynamical system.

The paper tried to model the factors affecting the intra city multimodal transportation system by defining different scenarios in the cause-and-effect model. The maps and results developed according to system dynamics modeling principles are discussed.

Four scenarios were considered given the factors affecting the urban transportation system to implement the transportation information system for reducing the material and non-material costs of wrong planning of the intra city transit system. After implementing the scenarios, scenario two was selected under the following conditions: advertising for cultural development, support of authorities by efforts such as street widening to reduce traffic, optimize infrastructure, increase and optimize public transport and etc.

The value of this paper is considering uncertainty in traffic optimization; taking into account behavioral and demand indicators such as cultural promotion, official support, early childhood learning, traffic hours and the impact of traveler social status; investigating the factors affecting the system under investigation and the reciprocal effects of these factors and real-world simulation by considering the factors and effects between them.

The maximum entropy snapshot sampling (MESS) method aims to reduce the computational cost required for obtaining the reduced basis for the purpose of model reduction. Hence, it can significantly reduce the original system dimension whilst maintaining an adequate level of accuracy. The purpose of this paper is to show how these beneficial results are obtained.

The so-called MESS method is used for reducing two nonlinear circuit models. The MESS directly reduces the number of snapshots by recursively identifying and selecting the snapshots that strictly increase an estimate of the correlation entropy of the considered systems. Reduced bases are then obtained with the orthogonal-triangular decomposition.

Two case studies have been used for validating the reduction performance of the MESS. These numerical experiments verify the performance of the advocated approach, in terms of computational costs and accuracy, relative to gappy proper orthogonal decomposition.

The novel MESS has been successfully used for reducing two nonlinear circuits: in particular, a diode chain model and a thermal-electric coupled system. In both cases, the MESS removed unnecessary data, and hence, it reduced the snapshot matrix, before calling the QR basis generation routine. As a result, the QR-decomposition has been called on a reduced snapshot matrix, and the offline stage has been significantly scaled down, in terms of central processing unit time.

Healthcare-associated infections (HAIs) are a major cause of concern because of the high levels of associated morbidity, mortality, and cost. In addition, children and intensive care unit (ICU) patients are more vulnerable to these infections due to low levels of immunity. Various medical interventions and statistical process control techniques have been suggested to counter the spread of these infections and aid early detection of an infection outbreak. Methods such as hand hygiene help in the prevention of HAIs and are well-documented in the literature. This chapter demonstrates the utilization of a systems methodology to model and validate factors that contribute to the risk of HAIs in a pediatric ICU. It proposes an approach that has three unique aspects: it studies the problem of HAIs as a whole by focusing on several HAIs instead of a single type, it projects the effects of interventions onto the general patient population using the system-level model, and it studies both medical and behavioral interventions and compares their effectiveness. This methodology uses a systems modeling framework that includes simulation, risk analysis, and statistical techniques for studying interventions to reduce the transmission likelihood of HAIs.

The purpose of this paper is to address the intersection between supply chain coordination and information technology (IT) by building on transaction cost analysis. Literature frequently predicts that the application of IT reduces transaction costs. Often, no real explanation is given, and the impact of IT on supply chain management (SCM) is not assessed.

Discussing the application of IT in SCM, a classification of different forms of collaboration (integration) is presented. Building on the essential transaction cost elements of specificity and uncertainty, the (high) costs of transactions in different supply chain integration forms are revealed.

The claim that IT reduces transaction costs is objected to in its general form. The reduction of transaction costs is dependent on the form of supplier integration. Through market transactions (not managed process links) and monitored process links, a reduction of transaction costs by using IT is likely. In the case of managed process links and non‐member process links, a reduction of transaction costs is achieved only if certain conditions apply. A conceptual framework is presented, using uncertainty and specificity to explain which IT applications can reduce transaction costs in a supply chain.

The research is based on conceptual thought. Beyond this framework for reducing IT‐based transaction costs in supply chains empirical research is needed to validate the findings.

Companies need to be aware that applying IT in their supply chain is not sake in itself. The classification provided in this paper support‐related decision by pointing out that different IT‐solutions fit different business process links.

The paper presents a more detailed analysis of the impacts IT applications have in SCM. This includes a discussion on how uncertainty and specificity influence the implementation of IT in supply chains.

This paper aims to present a method for the efficient reduction of networks modelling parasitic couplings in very‐large‐scale integration (VLSI) circuits.

The parasitic effects are modelled by large RLC networks and current sources for the digital switching currents. Based on the determined behaviour of the digital modules, an efficient description of these networks is proposed, which allows for a more efficient model reduction than standard methods.

The proposed method enables a fast and efficient simulation of the parasitic effects. Additionally, an extension of the reduction method to elements, which incorporate some supply voltage dependence to model the internal currents more precisely than independent current sources is presented.

The presented method can be applied to large electrical networks, used in the modelling of parasitic effects, for reducing their size. A reduced model is created which can be used in investigations with circuit simulators requiring a lowered computational effort.

Contrary to existing methods, the presented method includes the knowledge of the behaviour of the sources in the model to enhance the model reduction process.

This article is based on the REACCESS research project, sponsored by the European Commission, with the objectives of evaluating the technical, economic, and environmental aspects of present and future energy corridors between the European countries (EU27) and their main energy suppliers. GCC countries have an important role to play given their role in EU energy supply and in greenhouse gas emissions. The paper aims to discuss these issues.

A single energy model was built by hard‐linking the TIMES integrated assessment model (TIAM‐World), the Pan European TIMES model (PET), and the RECOR model (REaccess CORridors), including more than 1,000 possible energy corridors supplying the European countries. Another major methodology advance was to create a hybrid objective function, combining the usual cost objective and a metric representing the supply risk incurred by EU27. The risk component was constructed via a novel approach that aggregates the elemental risk parameters of each corridor using a Min‐Max function. Four contrasted scenarios were assessed, based on security and climate objectives.

Among the many results, it appears that a large reduction of the supply risk may be achieved at a very modest increase of the total energy system cost for EU27. Cross‐effects of climate mitigation and security objectives are also observed. Due to the diversification requirement, the contribution of GCC countries to EU energy imports increases under risk scenario. Sensitivity analyses show that the European energy system seems unable to reduce the market shares of fossil fuels import from MENA countries, including GCC countries, much below the reference case, proving the strong dependency of EU27 energy system from these countries. However, total fossil fuels imports, as well as total energy consumed, are decreased under the risk adverse scenarios.

Methodological developments, as described above, result in an advanced tool to assess how to increase the “energy system security”, by reducing the concentration of supply countries, diversifying import sources but also reducing the energy dependence at the end‐use side.

The purpose of this paper is to provide an extensive examination and analysis of the current literature on the use of blockchain technology in courts. The paper aims to explore the potential benefits of implementing blockchain technology in courts, such as increasing transparency and accountability, improving the efficiency of court procedures and enhancing the security of court records. Additionally, the paper intends to identify the challenges and limitations of using blockchain technology in courts and propose potential solutions to overcome these obstacles. The ultimate goal is to provide a comprehensive understanding of the potential applications and implications of blockchain technology in the context of the court system.

The research design of this study is qualitative, involving a thorough examination and analysis of existing literature on the use of blockchain technology in courts. The data collection procedure involves gathering information from various sources, such as academic publications, official reports and other relevant records. Data analysis is conducted using a thematic analysis approach, which identifies and categorizes recurring themes that emerge from the data. This approach ensures that the results are credible, dependable and accurate representations of the experiences of the participants. By using these methodologies, the study is able to draw meaningful conclusions and insights into the use of blockchain technology in courts.

The major findings of this paper suggest that the implementation of blockchain technology in courts has the potential to bring significant benefits such as increased transparency, efficiency and security. The use of blockchain technology in courts can enable the creation of tamper-proof records that are immutable, secure and transparent, which can help prevent fraud, reduce costs and enhance trust in the judicial system. However, adopting this technology also poses challenges and limitations, such as interoperability, governance and scalability. Overall, the paper concludes that while there are challenges to be addressed, the benefits of blockchain technology in courts are significant and should be explored further.

The study has several limitations that need to be taken into account. Firstly, the availability of data on blockchain implementation in the court system is limited, making it challenging to provide a comprehensive analysis of the topic. Thus, the study’s findings may not be generalizable to other contexts. Secondly, the study takes a technology-centric approach and does not consider blockchain technology’s social and legal implications in court operations. Thirdly, the case studies presented in this paper are limited to a few countries. Moreover, the implementation of blockchain technology in the court system is still in its early stages and lacks standardization, technical expertise and regulatory frameworks. Lastly, uncertainty around the legal framework may hinder its widespread adoption and use.

The practical implications of this study suggest that the use of blockchain technology in courts has the potential to improve efficiency, security, transparency and accountability in the court system. It can reduce the risk of data tampering, expedite case resolution and lower the cost of legal proceedings. Therefore, this study provides a framework for courts to consider blockchain technology’s potential benefits and explore its future adoption.

The social implications of this study are significant, as the adoption of blockchain technology in the court system can have a profound impact on society. Firstly, by increasing transparency and accountability, blockchain technology can promote public trust in the court system and improve access to justice, particularly for disadvantaged communities (Liu et al., 2020). Secondly, blockchain technology can reduce the reliance on intermediaries, such as lawyers, and streamline the case management process, making legal services more accessible and affordable for the general public (Khurana, 2020). Finally, the use of blockchain technology can create a more secure and efficient court system, enhancing the overall effectiveness of the judicial system and promoting public confidence.

This study provides an original contribution to the literature by exploring the use of blockchain technology in courts from a qualitative research design perspective. While there are a growing number of studies on the potential applications of blockchain technology in various fields, this study provides a comprehensive examination of the current literature on the use of blockchain in courts, identifying the benefits and limitations of its implementation. The study’s focus on the strengths and limitations of blockchain technology and its implications in court adds to the originality of this research.