Solution Framework Research Articles

IDeSyDe: Systematic Design Space Exploration via Design Space Identification

Design space exploration (DSE) is a key activity in embedded design processes, where a mapping between applications and platforms that meets the process design requirements must be found. Finding such mappings is very challenging due to the complexity of modern embedded platforms and applications. DSE tools aid in this challenge by potentially covering sections of the design space that could be unintuitive to designers, leading to more optimised designs. Despite this potential benefit, DSE tools remain relatively niche in the embedded industry. A significant obstacle hindering their wider adoption is integrating such tools into embedded design processes. We present two contributions that address this integration issue. First, we present the design space identification (DSI) approach for systematically constructing DSE solutions that are modular and tuneable. Modularity means that DSE solutions can be reused to construct other DSE solutions, while tuneability means that the most specific DSE solution is chosen for the target DSE problem. Moreover, DSI enables transparent cooperation between exploration algorithms. Second, we present IDeSyDe, an extensible DSE framework for DSE solutions based on DSI. IDeSyDe allows extensions to be developed in different programming languages in a manner compliant with the DSI approach. We showcase the relevance of these contributions through five different case studies. The case study evaluations showed that non-exploration DSI procedures create overheads, which are marginal compared to the exploration algorithms. Empirically, most evaluations average 2% of the total DSE request. More importantly, the case studies have shown that IDeSyDe indeed provides a modular and incremental framework for constructing DSE solutions. In particular, the last case study required minimal extensions over the previous case studies so that support for a new application type was added to IDeSyDe.

Robust Charging Network Planning for Metropolitan Taxi Fleets

We study the robust charging station location problem for a large-scale commercial taxi fleet. Vehicles within the fleet coordinate on charging operations but not on customer acquisition. We decide on a set of charging stations to open to ensure operational feasibility. To make this decision, we propose a novel solution method situated between the location routing problems with intraroute facilities and flow refueling location problems. Additionally, we introduce a problem variant that makes a station sizing decision. Using our exact approach, charging stations for a robust operation of citywide taxi fleets can be planned. We develop a deterministic core problem employing a cutting plane method for the strategic problem and a branch-and-price decomposition for the operational problem. We embed this problem into a robust solution framework based on adversarial sampling, which allows for planner-selectable risk tolerance. We solve instances derived from real-world data of the metropolitan area of Munich containing 1,000 vehicles and 60 potential charging station locations. Our investigation of the sensitivity of technological developments shows that increasing battery capacities shows a more favorable impact on vehicle feasibility of up to 10 percentage points compared with increasing charging speeds. Allowing for depot charging dominates both of these options. Finally, we show that allowing just 1% of operational infeasibility risk lowers infrastructure costs by 20%. Funding: This work was partially funded by the Deutsche Forschungsgemeinschaft [Project 277991500]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.0207 .

A Comprehensive Framework for Mitigating Digital Divide Factors in Higher Education : A Case Study of Kabul University

The issue of Digital Divide is a prevalent concern across various educational and non educational domains in Afghanistan. The situation is particularly challenging at Kabul University, where numerous factors hinder the effective utilization of av ailable digital technologies by students, teachers, and staff. Drawing on the existing factors, our research pr oposes a comprehensive solution framework to address this problem. Our framework aims to mitigate most of the Digital Divide factors that are pre sent at Kabul University, thereby enabling its stakeholders to leverage digital technologies effectively. Compared to similar frameworks proposed in other developing countries, our approach is specifically tailored to the cultural and educatio nal environme nts of Kabul University and Afghanistan. As such, it takes into account the unique challenges and opportunities presented by these contexts. Our research is a significant contribution to the discourse on Digital Divide in Afghanistan, an d we believe that o ur proposed framework has the potential to transform the digital landscape of Kabul University. We hope that our findings and recommendations will inform further research and policy interventions in this area, ultimately contributing to t he development of a more digitally inclusive society. In our research, we utilized a case study and design science methodology to address the issue of the Digital Divide at Kabul University in Afghanistan.

Hydrogen-bonded organic frameworks in solution enables continuous and high-crystalline membranes

Hydrogen-Bonded organic frameworks (HOFs) are a type of emerging porous materials. At present, little research has been conducted on their solution state. This work demonstrates that HOFs fragment into small particles while maintaining their original assemblies upon dispersing in solvents, as confirmed by Cryo-electron microscopy coupled with 3D electron diffraction technology. 1D and 2D-Nuclear Magnetic Resonance (NMR) and zeta potential analyses indicate the HOF-based colloid solution and the isolated molecular solution have significant differences in intermolecular interactions and aggregation behavior. Such unique solution processibility allows for fabricating diverse continuous HOF membranes with high crystallinity and porosity through solution-casting approach on various substrates. Among them, HOF-BTB@AAO membranes show high C3H6 permeance (1.979 × 10−7 mol·s−1·m−2·Pa−1) and excellent separation performance toward C3H6 and C3H8 (SF = 14). This continuous membrane presents a green, low-cost, and efficient separation technology with potential applications in petroleum cracking and purification.

Generalized sequential state equation method for moving subsystem-induced structural parametric resonance

Parametric excitation is a unique type of excitation that arises from the time-varying parameters of a dynamical system, typically induced by the periodic movements of the system components. However, the structure-moving subsystems problem creates a new type of parametric excitation where the subsystems do not have exact periodic movements. Under the circumstances, dimension of the mathematical model of such a system exhibits time dependency, which prohibits the employment of conventional analytical methods to predict its stability. In this paper, we propose a novel Generalized Sequential State Equation Method that provides a distinct solution framework for analysis of the subsystem-induced parametric resonance. With the time-domain system partition and state mapping, the proposed method reconfigures the coupled system with a sequence of state space equations and solves them chronologically. The proposed method relaxes the single-subsystem-assumption in its original form and applies to a general scenario where the subsystems travel with arbitrary characteristic period. With the proposed method, occurrences of the subsystem-induced parametric resonance are precisely predicted via a set of analytical stability criteria and the steady state response is determined in an exact analytical form.

A two-step approach for deploying heterogeneous vessels and designing reliable schedule in liner shipping services

Schedule reliability is a crucial metric for measuring liner container shipping service. Due to the inherent uncertainties at sea and ports, schedule delays and unreliable on-time performance have long plagued shipping companies. In practice, the heterogeneity of container vessels also creates challenges for deployment and schedule optimization. To address the problem, we develop a two-step approach with two programming sub-models. In the first step, we tackle the challenges of ship deployment and scheduling by considering heterogeneous vessels and capturing the interarrival time between adjacent ports of call. In the second step, we use the conditional value-at-risk (CVaR) to address the uncertainty risk avoidance in schedule design. To solve the stochastic programming models, we employ a solution framework based on the outer linear approximation method and the risk measure method, where CVaR is specified as the risk measure. We illustrate the application of our model on a case study concerning a real route operated by COSCO Shipping Lines. The results show that the total cost of liner shipping service with heterogeneous fleet on the route can be reduce by 4.77% compared with homogeneous fleet. And the cost of risk with the reliable schedule can be decreased by 8.04% compared with the ideal schedule. The research conclusions can provide some useful decision-making references for shipping companies to deploy heterogeneous vessels and design reliable schedules.

A joint solution framework for the optimal operation and evaluation of integrated energy systems based on exergy

Exergy analysis provides a unified scale for evaluating the quality and quantity of energy, and is suitable and essential for scientifically and rationally guiding the optimization and evaluation of integrated energy systems with intricate multi-component configurations. The present work proposes an exergy analysis model and joint solution framework for integrated energy systems based on exergy, and presents an efficient and accurate solution method. The exergy analysis model is analogous to the energy-based model and possesses a succinct form. This model is then applied to establish an input exergy model defining the exergy of inputs, a destroyed exergy model defining the exergy lost due to the conversions, transmissions, and storages, and a benefit exergy model defining the remaining useful exergy for the loads. The joint solution framework optimizes the system from the basis of exergy conservation, and evaluates the destroyed exergy of each link and the prices of the various exergy products from an economic perspective based on the established exergy analysis model. The complexity of the framework is then reduced by establishing a sequential optimization and evaluation model. The optimization model is solved accurately and efficiently using a stringent cutting plane method to address the problem of relaxation inaccuracy, and piecewise linearization to accommodate the non-convex constraints. Numerical computations on a 97-node system demonstrate the accuracy of the proposed models in exergy-based optimization, destruction, and price evaluation, preventing substantial deviations (e.g., a 23% discrepancy in total destroyed exergy). The adopted cost allocation method based on energy quality reflects fair pricing, rectifying conventional pricing disparities (e.g., a 47.56% underestimation of the electric load using energy-based pricing). Therefore, the accuracy and efficiency of the developed exergy analysis model, solution framework, and solution method are validated.

RFWBS Model: Multilevel Hybrid Mapping Solution Framework for Designing Neurorehabilitation Physiotherapy Devices

Healthcare services and rehabilitation equipment have entered a phase of rapid development driven by user requirements. However, the development of corresponding design models for rehabilitation equipment is lacking. A general framework and development process are urgently needed for neurorehabilitation physiotherapy equipment. To address problems such as inadequate knowledge representation in the design process and difficulties in modeling the functional structure of the product, we combined a decomposition topology model of neurorehabilitation physiotherapy equipment with the modular design method. We proposed a general model for the design of neurorehabilitation physiotherapy equipment comprising the following modules: requirements (R), function (F), principle workspace (W), behavior (B), and structure (S), i.e., the RFWBS model. Using the neurorehabilitation robotic glove as an example for design practice, in terms of kinematics, the mechanism is analyzed by establishing a Lagrangian coordinate system for resolution. The mechanism has three degrees of freedom and can achieve the natural flexion and extension angles of each finger joint. In terms of dynamics, during the entire finger extension, the angular acceleration is almost zero, and the average angular velocity is approximately 30~50°/s. This indicates that the mechanism is suitable for wearable use, validating the scientific and effective nature of the RFWBS expanded model.

Planning for heat-resilient educational precincts: Framework formulation, cooling infrastructure selection and walkable routes determination

To create a heat-resilient education precinct, this study developed a framework for campus heat solutions to enhance the heat mitigation and adaptation capacity of campus stakeholders. The campus heat solution framework consists of preparation, mitigation and adaptation, thermal environment and comfort assessment, information-sharing platform, heat action plan, and post-assessment. An empirical study in Chongqing University, China based on field experiments, numerical simulations, and post-processing of outdoor thermal environments and comfort was conducted, to demonstrate the applicability of the framework in actual educational precincts. The results indicated the spatiotemporal variability of surface temperature and outdoor thermal comfort, exhibited the right time and proper cooling infrastructure selection, and identified the adaptive walkable paths. For instance, the universal thermal climate index (UTCI) with sun exposure had a mean value of 46.8 °C and a maximum value of 51.4 °C at 14:00, while the mean UTCI of the tree, sunshade and pavilion were 8.1 °C, 9.3 °C and 10.6 °C lower than that of the full exposure means, respectively. Therefore, before 10:00 or after 18:00, choosing locations under trees, sunshades, or pavilions can ensure better thermal comfort at high temperatures. In comparison, from 10:00 to 13:00, it is essential to choose sunshades or pavilions, and from 13:00 to 18:00, it is preferable to choose only pavilions. Moreover, a suitable walkable path was determined based on cumulative heat stress. Overall, this study is expected to provide a reference for building healthy and comfortable educational precincts and enhance the understanding of heat resilience planning.

Design of a novel intelligent computing framework for predictive solutions of malaria propagation model.

The paper presents an innovative computational framework for predictive solutions for simulating the spread of malaria. The structure incorporates sophisticated computing methods to improve the reliability of predicting malaria outbreaks. The study strives to provide a strong and effective tool for forecasting the propagation of malaria via the use of an AI-based recurrent neural network (RNN). The model is classified into two groups, consisting of humans and mosquitoes. To develop the model, the traditional Ross-Macdonald model is expanded upon, allowing for a more comprehensive analysis of the intricate dynamics at play. To gain a deeper understanding of the extended Ross model, we employ RNN, treating it as an initial value problem involving a system of first-order ordinary differential equations, each representing one of the seven profiles. This method enables us to obtain valuable insights and elucidate the complexities inherent in the propagation of malaria. Mosquitoes and humans constitute the two cohorts encompassed within the exposition of the mathematical dynamical model. Human dynamics are comprised of individuals who are susceptible, exposed, infectious, and in recovery. The mosquito population, on the other hand, is divided into three categories: susceptible, exposed, and infected. For RNN, we used the input of 0 to 300 days with an interval length of 3 days. The evaluation of the precision and accuracy of the methodology is conducted by superimposing the estimated solution onto the numerical solution. In addition, the outcomes obtained from the RNN are examined, including regression analysis, assessment of error autocorrelation, examination of time series response plots, mean square error, error histogram, and absolute error. A reduced mean square error signifies that the model's estimates are more accurate. The result is consistent with acquiring an approximate absolute error close to zero, revealing the efficacy of the suggested strategy. This research presents a novel approach to solving the malaria propagation model using recurrent neural networks. Additionally, it examines the behavior of various profiles under varying initial conditions of the malaria propagation model, which consists of a system of ordinary differential equations.

Controlled aggregation of Pt/PtH/Rh/RhH doped silver superatomic nanoclusters into 16-electron supermolecules.

The assembly of discrete superatomic nanoclusters into larger constructs is a significant stride towards developing a new set of artificial/pseudo-elements. Herein, we describe a novel series of 16-electron supermolecules derived from the combination of discrete 8-electron superatomic synthons containing interstitial hydrides as vertex-sharing building blocks. The symmetric (RhH)2Ag33[S2P(OPr)2]17 (1) and asymmetric PtHPtAg32[S2P(OPr)2]17 (2) are characterized by ESI-MS, SCXRD, NMR, UV-vis absorption spectra, electrochemical and computational methods. Cluster 1 represents the first group 9-doped 16-electron supermolecule, composed of two icosahedral (RhH)@Ag12 8-electron superatoms sharing a silver vertex. Cluster 2 results from the assembly of two distinct icosahedral units, Pt@Ag12, and (PtH)@Ag12. In both cases, the presence of the interstitial hydrides is unprecedented. The stability of the supermolecules is investigated, and 2 spontaneously transforms into Pt2Ag33[S2P(OPr)2]17 (3) with thermal treatment. The lability of the hydride within the icosahedral framework in solution at low-temperature was confirmed by the VT-NMR.

A VNS-based approach for solving the Manhattan metric straddle carrier routing problem with buffer areas

This paper presents a metaheuristic approach for solving an optimization problem that arises at container terminals where straddle carriers (SCs) transport containers between the stacking areas and the seaside. In such container terminals, operational efficiency depends mainly on SC routing. SCs routes should consider the order in which containers are unloaded and loaded at the quay cranes (QCs), taking into account the limited capacity of the buffer area of each QC where containers are temporarily stored after being handled by a QC or an SC. Besides the precedence relations (i.e., container sequences) and buffer capacities, the solution framework considers safety constraints. Efficient routing of SCs directly contributes to minimizing the idle time of QCs, thereby improving their overall productivity and minimizing the turnaround time of vessels, which is the objective of the problem. Specifically, we present two different variants of the Variable Neighborhood Search (VNS) algorithm. Each variant is initialized in both a greedy and a random manner. These algorithms address the problem by incorporating four LS operators commonly utilized in vehicle routing problems. We perform a comparative analysis of the results of these four approaches against each other and against solutions generated by an exact solver. Our numerical experiments show that the proposed algorithms perform better than the used solver, especially for bigger instances. A comparison with the results from the literature is also given and shows that the proposed VNS-based approach provides competitive results.

Revisiting Diffusive Representations for Enhanced Numerical Approximation of Fractional Integrals

This study reexamines diffusive representations for fractional integrals with the goal of pioneering new variants of such representations. These variants aim to offer highly efficient numerical algorithms for the approximate computation of fractional integrals. The approach seamlessly aligns with established techniques used in addressing problems involving integer-order operators, contributing to a unified framework for numerical solutions.

Інноваційні технології у фінансовій сфері: узагальнення світового досвіду

The introduction of innovations makes it possible to ensure a stable economic situation for the business entity – both at the level of the national financial sector and in the international financial services market. The spread of financial technologies in the world continues to evolve through the emergence of new products and services. Despite different approaches to the development of enterprises and organizations in the financial sector, the common features remain the desire for innovation, ensuring the security of the financial system and protecting consumers. The contemporary tendency towards the introduction of flexible models of response to changes in the economic environment is one of the major strategies for creating favorable conditions for the development of innovative technologies in the financial sector. The aim of the publication consists in a theoretical generalization of the international experience in the implementation of financial innovations and to develop recommendations for its implementation in domestic practice. Financial innovation technologies are an important component of the development of the national economy of Ukraine. Our country has significant potential for the development of financial technologies, but its regulatory framework still needs significant changes to create a favorable environment for innovation. Unlike the UK or the EU, where regulations are aimed at accelerating the introduction of financial technologies, in Ukraine this process is just beginning. The article analyzes the international experience in the introduction of innovative technologies in the financial sector. The experience of fintech innovations in the USA, Great Britain, China, Singapore, South Korea is considered, the features of implementation and the possibility of their adaptation to activities of the business entities in Ukraine are determined. The existing regulatory obstacles to the possibilities of generation of fintech startups in Ukraine are identified. The National Bank of Ukraine (NBU), which is the key regulator of the national financial sector, is gradually introducing new rules and conditions for the development of financial technologies. However, at present, the limited legal framework for cryptocurrencies, blockchain technologies and other innovative solutions remains a problem, which hinders the development of such instruments. An analysis of the experience of implementing innovative technologies in the leading countries of the world proves that Ukraine already has a fairly flexible regulatory system, which creates potential advantages for the generation of financial startups, but at the same time there are certain risks of an imperfect regulatory system.

A General Framework for the Power Flow Solution in Radial and Meshed AC/DC Microgrids

A General Framework for the Power Flow Solution in Radial and Meshed AC/DC Microgrids

The Adaptation of Digital Health Solutions During the COVID-19 Pandemic in Hungary: A Scoping Review.

Before the pandemic, digital health was merely a potential alternative to established systems of healthcare provision in Hungary. The technology was available but there was no governmental strategy regarding digital health use and development. The legal framework for digital solutions in healthcare was fragmented. COVID-19 created conditions in which digital solutions became the most feasible form of healthcare provision. We present the legislative and policy-making activities of the Hungarian government during the pandemic aimed at enhancing the organised and systematic use of these technologies. The core method used in our research is a review of legislation using the principles and methods of a systematic literature review. We searched the National Legislation Database for digital health related legislation for the period January 31, 2020 - June 1, 2022. To provide the context for the analysis, other relevant documents were identified through desk research. Although established in 2017, the electronic health records (EHRs) were only widely used after the onset of the pandemic. Hungary used temporary state of emergency regulations to facilitate an increase in the number of teleconsultations. Our search identified 7 pieces of legislation that enabled healthcare providers to put digital solutions to instant use. They defined the conditions healthcare providers must meet for teleconsultations, set what interventions may be done, what can be reimbursed and dealt with security issues. The National Health Informatics Strategy of July 2021 is complex but mainly deals with technical issues. The three basic principles of the strategy are people centeredness, digital transformation and integrated care. Hungarian digital health solutions and policies fare well in international comparison. This is due to the intensive legislative activity of the pandemic period. The National Health Informatics Strategy ensures that the digital health solutions implemented during the pandemic outlive COVID-19.

Skepticism, Straight Solution and Linguistic Frameworks

The article considers the straight solution of S. Kripke’s skeptical problem concerning the stability of linguistic meaning proposed by E.V. Borisov’s. The distinction between two kinds of introspection related to the knowledge of linguistic meaning is analyzed. The moderate solution of the skeptical problem as a basis for the straight solution is explored. It is suggested that R. Carnap’s conception of linguistic frameworks can be useful for the solution of skeptical problem.

Challenges to Deploy Augmented Reality in Manufacturing

Augmented Reality (AR) has the potential to revolutionise manufacturing by incorporating digital technologies into day-to-day activities. Nevertheless, its adoption in the industry remains slow. Although most research has focused on understanding the barriers to adoption and its impact on industry, only a limited number of studies have discussed how to deploy AR in manufacturing. This paper investigates the industry’s perceived challenges when deploying AR in manufacturing. Off-the-shelf and customised AR applications were analysed to understand how AR has been implemented in manufacturing. Additionally, 89 industry workers were surveyed to validate the observed deployment challenges and identify possible solutions. The survey showed that AR has a significant entry barrier due to its complexity and limited personalisation possibilities. Finally, an initial solution framework to address implementation issues is presented and discussed. It includes a module to match industry needs with AR capabilities, AR authoring tools, and off-the-shelf AR infrastructure.

Tree-Based Solution Frameworks for Predicting Tunnel Boring Machine Performance Using Rock Mass and Material Properties

Tree-Based Solution Frameworks for Predicting Tunnel Boring Machine Performance Using Rock Mass and Material Properties

Fast and Generic Energy Flow Analysis of the Integrated Electric Power and Heating Networks

Energy flow analysis is a fundamental tool to determine the network states of the integrated energy systems (IES). For the widely deployed IES with coupled power grids (PG) and heating networks (HN), we still lack a generic tool that can be easily employed to calculate the quasi-dynamic energy flows of it. In this paper, we have developed a generic code package (named as MATHN) for energy flow analysis of the quality-regulated HN. After that, a generic solution framework that leverages MATPOWER and MATHN to realize decomposed energy flow calculation of PG and HN is proposed. Behind the MATHN tool, a model reformulation technique is proposed to eliminate the massive indirect variables of the basic HN model discretized by finite difference, which finally derives a compact matrix formulation (similar to the network equation of power grid: I=YU) for generic description of any HN and also slashes the original model scale by around 20 times. Moreover, the solution strategy behind the MATHN tool further converts this matrix formulation into a standard system of non-homogeneous linear equations, with which some existing well-recognized algorithms can be directly applied for efficient and accurate solution. Case studies on three different scales of test systems demonstrate the generality, efficiency and accuracy of our methods. All the codes and input data are packaged into the MATHN tool and are made open-source for non-commercial use.