Integral Solution Research Articles

IoT Forensics-Based on the Integration of a Permissioned Blockchain Network

The proliferation of Internet of Things (IoT) devices has facilitated the exchange of information among individuals and devices. This development has introduced several challenges, including increased vulnerability to potential cyberattacks and digital forensics. IoT forensic investigations need to be managed in a forensically sound manner using a standard framework. However, adopting traditional digital forensics tools introduces various challenges, such as identifying all IoT devices and users at the crime scene. Therefore, collecting evidence from these devices is a major problem. This paper proposes a permissioned blockchain integration solution for IoT forensics (PBCIS-IoTF) that aims to observe data transactions within the blockchain. The PBCIS-IoTF framework designs and tests Hyperledger blockchains simulated with a Raspberry Pi device and chaincode to address the challenges of IoT forensics. This blockchain is deployed using multiple nodes within the network to avoid a single point of failure. The authenticity and integrity of the acquired evidence are analysed by comparing the SHA-256 hash metadata in the blockchain of all peers within the network. We further integrate webpage access with the blockchain to capture the forensics data from the user’s IoT devices. This allows law enforcement and a court of law to access forensic evidence directly and ensures its authenticity and integrity. PBCIS-IoTF shows high authenticity and integrity across all peers within the network.

The Use of Google Translate in the Arabic-English Classroom

This study examines the uses, perceived quality, and ethical and policy considerations of the use of Google Translate (GT) among Saudi college students majoring in English language and translation, as well as on the part of their instructors. Using separate surveys for students and instructors, the findings indicate widespread use of GT by both students and instructors, who acknowledge its effectiveness for translation tasks. However, a misalignment exists between the actual use of GT and formal academic policies. Course specifications do not mention GT, and traditional dictionary use continues to be the primary focus of translation training. Most instructors have not integrated GT into their teaching activities nor provided guidelines or policies regarding its effective use, despite recognizing its benefits. The study concludes by discussing the pedagogical implications of these findings and suggests solutions for better integration of modern translation tools such as GT into the curriculum. The study highlights the gap between current academic practices and the real-world workplace, which has already integrated Machine Translation (MT) extensively. The study advocates for clear policies and for the structured teaching of MT to enhance the relevance and effectiveness of translation training in the evolving professional landscape.

Assessment of Vehicle-Integrated Photovoltaics: A financial and environmental perspective

Integrating photovoltaic (PV) technology into electric vehicles (EVs) promises an environmentally friendly transportation solution by increasing the energy efficiency of vehicles. On the other hand, the limited integration area of the vehicle causes PVs to have relatively lower power output. This situation creates a discussion about how reasonable a solution for PV-EV integration is from various perspectives. This study aims to provide a realistic assessment of PV-EV integration using manufacturer-provided data on solar-assisted EVs in the market. Assessments are examined in three categories: financial assessment based on payback period, environmental assessment based on carbon emissions, and usage-based assessment based on charging dependency. The findings indicate that the PV systems integrated into contemporary solar-assisted market vehicles demonstrate a return on investment within 8.7 years. From an environmental perspective, hybrid vehicles can provide up to a 12 % reduction in carbon emissions, while fully EVs can achieve reductions of up to 32.5 %. Usage-based assessments showed that PV-EV integration is especially advantageous for countries with low daily travel distances. According to the assessment, the use of PV panels in vehicles can potentially extend the usage time without recharging by up to 170 %.

Using Patient-Generated Health Data more efficient and effectively to facilitate the implementation of Value-Based Healthcare in the EU – Innovation Report

Healthcare services and products are rapidly changing due to the development of new technologies, offering relevant solutions to improve patient outcomes. Patient-Generated Health Data and knowledge-sharing across the European Union (EU) has a great potential of making healthcare provision more effective and efficient by putting the patient at the centre of the healthcare process. While such initiatives have been taken before, a uniting and overarching approach is still missing. The EU-funded IMPROVE project will develop an evidence-based and actual framework to effectively leverage the added value of people-centred integrated healthcare solutions, using predominantly PROMs, PPI, PREMs, and other Patient-Generated Health Data (PGHD). As a result, the project facilitates the effective and efficient implementation of Value-Based Healthcare across the EU by putting the patient central in the healthcare process.

A hybrid fixed point theorem for product of two operators in a lattice-ordered Banach algebra with applications to quadratic integral equations

We prove a hybrid fixed point theorem for the product of two operators in a latticeordered Banach algebra and apply to nonlinear hybrid quadratic integral equations of mixed type for proving the existence of maximal and minimal positive integrable solutions under certain mixed conditions of Lipschitzicity and monotonicity of the nonlinear functions. Our main existence result is illustrated with a numerical example as well as with an application to IVPs of nonlinear first-order discontinuous quadratically perturbed ordinary differential equations.

Automated Machine Learning: A Survey of Tools and Techniques

Automated Machine Learning (AutoML) has revolutionized the field of machine learning by automating complex and time-intensive tasks such as data preprocessing, model selection, and hyperparameter tuning. This study explores the capabilities, limitations, and practical applications of six widely used AutoML tools: Auto-sklearn, TPOT, H2O.ai, Google Cloud AutoML, Microsoft Azure AutoML, and Amazon SageMaker Autopilot. By evaluating these tools across diverse datasets—spanning tabular data, time series, image classification, and text sentiment analysis—the research highlights their predictive performance, computational efficiency, scalability, and explainability. Proprietary tools demonstrated superior scalability and efficiency through cloud integration, while open-source platforms provided more interpretability and flexibility. However, challenges such as lack of transparency in advanced neural architecture search mechanisms and ethical considerations, including bias mitigation, remain prevalent. This study concludes that while AutoML tools significantly lower the barrier to entry for machine learning, ongoing advancements are required to balance performance, usability, and ethical standards, making AutoML an integral solution for real-world applications.

Finite basis topologies for multiloop high-multiplicity Feynman integrals

In this work, we systematically analyze Feynman integrals in the ‘t Hooft-Veltman scheme. We write an explicit reduction resulting from partial fractioning the high-multiplicity integrands to a finite basis of topologies at any given loop order. We find all of these finite basis topologies at two loops in four external dimensions. Their maximal cut and the leading singularity are expressed in terms of the Gram determinant and Baikov polynomial. By performing an integration-by-parts reduction without any cut constraint on a numerical probe for one of these topologies, we show that the computational complexity drops significantly compared to the conventional dimensional regularization scheme. Formally, our work implies an upper bound on the rigidity of special functions appearing in the iterated integral solutions at each loop order in perturbative quantum field theory. Phenomenologically, the integrand-level reduction we present will substantially simplify the task of providing high-precision predictions for future high-multiplicity collider observables. Published by the American Physical Society 2024

A Comparative Analysis of Twelve Research Paradigms Across Six Knowledge Acquisitions and Twelve Sources of Knowledge: A Philosophical Discourse

This study investigates whether a single research paradigm can dominate knowledge acquisition across empirical and interpretive domains or if a multi-paradigm approach is essential for achieving a holistic understanding. Twelve paradigms, including Positivism, Pragmatism, Hermeneutics, and Feminism, were evaluated across six domains: Science, Philosophy, History, Art, Religion, and Culture. The methodology employed comparative analysis, factor analysis, sensitivity testing, and inter-rater reliability assessment to quantify paradigm performance. The findings confirm Positivism's strength in empirical fields like Science and Philosophy but reveal its limitations in addressing ethical, cultural, and interpretive dimensions, where paradigms like Hermeneutics and Feminism excel. Pragmatism and Critical Realism bridge empirical rigor with interpretive depth, offering integrative solutions for interdisciplinary challenges. By applying statistical tools within a philosophical inquiry, this research highlights the necessity of humility and open-mindedness in selecting paradigms to address complex questions. The study concludes that no single paradigm suffices across all domains, advocating for a multi-paradigm approach to foster collaboration, inclusivity, and a more comprehensive understanding of knowledge production. These insights have implications for interdisciplinary research, education, and policymaking, emphasizing the importance of integrating diverse epistemological perspectives.

The Portable Urban Garden as an integrative solution to the lack of space for cultivation in large metropolises

The Portable Urban Garden as an integrative solution to the lack of space for cultivation in large metropolises

A novel uncertainty quantification method for electricity performance of building photovoltaic systems from multiple weather data sources

Distributed photovoltaic (PV) systems on buildings offer a promising solution for local renewable energy integration. As interest in sustainable energy grows, the demand for building PV systems is increasing. However, a significant challenge lies in accurately quantifying the uncertainty associated with building PV performance, particularly when considering multiple weather data sources. This study proposes a novel uncertainty quantification method to address this challenge. A case study of a building PV system with a PV wall and roof in Tianjin, China, is utilized to demonstrate the proposed method. Three types of weather data from different sources are considered: typical meteorological year data, multi-year historical data, and climate change projections. Uncertainty is quantified using a weighted-mean approach, incorporating weights based on recency, period, and accuracy of the data sources. Results indicate that the proposed method effectively integrates uncertainties from various data sources, providing reliable long-term energy yield estimates for PV systems. The variation coefficient of annual yield for the PV wall and roof system across ten typical meteorological year files is approximately 10 %. This study contributes to a comprehensive understanding of uncertainty in building PV performance, enabling informed decision-making in sustainable building design and energy management.

Novel (3 + 1)-dimensional variable-coefficients Boussinesq-type equation: exploring integrability, Wronskian, and Grammian solutions

Abstract In this paper, we introduce a novel (3 + 1)-dimensional variable-coefficients Boussinesq-type equation. We analyze its integrability using the Painlevé test and the N -soliton solution, demonstrating that both tests yield identical conditions. Using the Hirota bilinear form of the equation, we derive Wronskian and Grammian determinant solutions utilizing Plücker relations and the Jacobi identity for determinants. In particular, we use elementary transformation and long wave limit to get the determinant expression of mth-order lump solutions from the 2mth-order Wronskian determinant solutions. Furthermore, we reveal a variety of novel semi-rational solutions using the Hirota method and Grammian determinant techniques.

Thermal stress intensity factors in composite plates with cracks arising from a circular hole

In the present study, a novel analytical solution is introduced for the determination of thermal Stress Intensity Factors (SIFs) for a composite plate containing a cracked circular hole subjected to a uniform heat flux. Therefore, an analytical approach, based on the Complex Variable Method (CVM), is provided for the first time, employing the Schwartz integration method. To facilitate the solution of complex integrals using Schwartz’s theorem, a novel representation of mapping function is offered, providing a more straightforward solution. Thermal SIFs are calculated for circular holes containing one or two cracks. Also, the influence of factors like fiber orientation and dissimilar crack lengths is investigated. To verify the accuracy of outcomes derived from the current analytical solution, a comparison with results obtained through the Finite Element Method (FEM) is conducted. The comparative analysis highlights the robust accuracy of the present solution. In scenarios where fibers align with the crack length and the heat flux acts perpendicular to the crack direction, the Mode-I of SIF becomes neglected. However, when the fibers do not align with crack length, the Mode-I SIF deviates from zero. Furthermore, an increase in the length of one crack is observed to augment the SIF of another crack.

Muddy Waters: Design Thinking for Understanding the Multi-Organizational Problem Space of the Water Sector

Context and motivation: Climate change is manifested by climate variability, rising temperatures (and thus evaporation), and extreme events such as droughts and floods, which have a profound effect on the availability of natural resources, for example, high-quality water. While several technologies for addressing these challenges are available, their adoption is not widespread. In this study, a design thinking (DT) approach was applied to understand the problem space of floods and their handling by the Israeli water sector. Specifically, we aim at addressing the following question: What are the gaps in and barriers to adopting solutions that address sewerage flooding during extreme heavy rainfall events? The DT approach exposed major problems in the conduct of the water sector, including a lack of communication among organizations, the ill-defined distribution of responsibility, unclear and conflicting guidance, and insufficient funds and technological solutions, all hindering the possibility of adopting an integrative solution. This study demonstrates the role that DT plays in understanding a complex, multi-organizational problem space, in our case, the climate change readiness of the water sector, before delving into technological development. Any solution development should involve participants from the various organizations involved in the challenge. It is vital to address not only each organization’s requirements but also its technology adoption barriers and to initiate a comprehensive discussion, ultimately resulting in a shared understanding of all the facets of the challenge that can impact solution development and deployment.

Residual symmetry and interactions between solitons and periodic waves of the Drinfeld–Sokolov–Satsuma–Hirota system

In this paper, the Drinfeld–Sokolov–Satsuma–Hirota (DSSH) system is studied by using residual symmetry and the consistent Riccati expansion (CRE) method, respectively. The residual symmetry of the DSSH system is localized to Lie point symmetry in a properly prolonged system, based on which we get a new Bäcklund transformation for this system. New symmetry reduction solutions of the DSSH system are obtained by applying the classical Lie group approach on the prolonged system. Moreover, the DSSH system proves to be CRE integrable and new interesting interaction solutions between solitons and periodic waves are generated and analyzed.

A Real-Time Associative Feature-Based Customer Relationship Management and Enterprise Resource Planning Integration Model for Small- and Medium-Sized Enterprises

Abstract Customer relationship management (CRM) and enterprise resource planning (ERP) have been extensively discussed in the research literature respectively. However, existing studies do not reach a complete agreement on the CRM/ERP integration method, especially for small- and medium-sized enterprises (SMEs). Generally, this work proposed a novel method for CRM/ERP integration approach via associative feature technology. A new feature type, Real-time Data Link Board (RDLB), is developed and detailed as a generic information carrier solution for multisystem integration between CRM and ERP packages. Valuable data elements are mapped into such data boards dynamically and synchronized across different data sources, structures, and databases. The contribution of this work is to present a well-defined and generically reusable data carrier definition, alongside related methods for ensuring consistent data modeling during the system integration phase across various digitalization engineering implementation projects. With this approach, the consistent management of data integration across intricate systems is achievable throughout application lifecycles, supported by the object-oriented software engineering foundation.

Radial Kernels Collocation Method for the Solution of Volterra Integro-Differential Equations

Radial kernel interpolation is an advanced method in approximation theory for the construction of higher order accurate interpolants for scattered data up to higher dimensional spaces. In this manuscript, we formulate a radial kernel collocation approach for solving problems involving the Volterra integro-differential equations using two radial kernels: The Generalized Multi-quadrics and the linear Laguerre-Gaussians. This was achieved by simplifying the Volterra integral problem's solution to an algebraic system of equations. The impact of the shape parameter present in every kernel on the method's accuracy is examined and found to be significant. Two examples were used to illustrate the process; the numerical results are shown as tables and graphs. MATLAB 2018a was employed in the process.

Solving recurrence relations for multiloop integrals in the limit of large values of the dimensional regularization parameter

A method for calculating the 1/d expansion coefficients for solutions of integration by parts relations for Feynman integrals is presented. The idea is to use linear substitutions to transform these relations to an explicitly recursive form. A possible type of such substitutions is proposed for the case of vacuum integrals. Its applicability is shown for several families of massless (with one massive line) vacuum integrals up to the 7-loop level.

Modelling project activities for future teachers within the innovative infrastructure of pedagogical universities: integrative solutions

Introduction. In the quest to enhance the training of future teachers, particular emphasis is placed on identifying the educational potential of new learning environments within pedagogical universities under the Ministry of Education of Russia. These institutions have undergone infrastructure updates as part of federal programs designed to support education. Aim. The aim of this study is to develop an original model for organising the project activities of student teachers, taking into account the contemporary infrastructural capabilities of pedagogical universities under the Ministry of Education of Russia. Methodology, methods and techniques. The methodological foundation of this research is grounded in the principles of community development pedagogy and the design of evolving educational systems. The integration of integrative, synergetic, environmental, and system-activity approaches facilitated the identification and development of components within the author’s model for organising project activities for future teachers in the context of pedagogical technoparks, such as “Quantorium”, and technoparks focused on universal pedagogical competencies in higher education institutions under the Ministry of Education of the Russian Federation. The validation of the developed model was conducted through expert assessments. Results. The authors developed the model for organising project activities for future teachers within the innovative infrastructure of pedagogical universities. The main components of the model are outlined, including integrative objectives and anticipated outcomes of students’ project activities, interdisciplinary project content, and a technological component that facilitates the transformation of interdisciplinary project content into personally meaningful experiences through the technology of collaborative distributed project activities. The study identifies and justifies the conditions necessary for the effective implementation of the developed model, focusing on the management of processes, resources, and participants involved in interdisciplinary project activities. Scientific novelty. Integrative processes, within the context of this study, are regarded as a pedagogical phenomenon that reflects the interconnections among the objects, processes, and subjects involved in project activities. Practical significance. The research materials can be utilised in the development of programmes aimed at enhancing the infrastructure of pedagogical universities. They can also assist in the refinement of educational curricula for training teaching staff, particularly in disciplines that prepare future educators to effectively organise project-based activities within contemporary educational environments.

Energy Storage in Carbon Fiber-Based Batteries: Trends and Future Perspectives

Carbon fiber-based batteries, integrating energy storage with structural functionality, are emerging as a key innovation in the transition toward energy sustainability. Offering significant potential for lighter and more efficient designs, these advanced battery systems are increasingly gaining ground. Through a bibliometric analysis of scientific literature, the study identifies three primary research areas: (i) the development of anodes for lithium-ion batteries, tackling challenges such as dendrite formation and performance degradation; (ii) the creation of new carbon fiber-based cathodes with coatings of LiFePO4, LiCoO2, or other nanoparticles, alongside efforts to develop cobalt-free alternatives; and (iii) the advancement of solid electrolytes that achieve a balance between ionic conductivity and mechanical strength. These advancements position carbon fiber-based batteries as promising solutions for seamless integration into various structural applications. The analysis of publication trends, citation patterns, and collaboration networks provides critical insights into the ongoing technological developments, current research challenges, and emerging trends in this field. Moreover, the study highlights potential research directions, underscoring the importance of continuous innovation to fully realize the potential of carbon fiber-based energy storage technologies.

The asymptotic preserving unified gas kinetic scheme for the multi-scale kinetic SIR epidemic model

In this paper, we present an asymptotic preserving scheme for the two-dimensional space-dependent and multi-scale kinetic SIR epidemic model which is widely used to model the spread of infectious diseases in populations. The scheme combines a discrete ordinate method for the velocity variables and finite volume method for the spatial and time variables. The idea of unified gas kinetic scheme (UGKS) is used to construct the numerical boundary fluxes which needs the formal integral solutions of the model. Due to the coupling of the three transfer equations in the SIR model, it is difficult to obtain these integral solutions dependently. We decouple the system by constructing the fluxes in a separate way. Then following the framework of UGKS we can obtain the macro auxiliary quantities which is needed in the scheme. Thus the SIR model can be solved in the sequential way. In addition, we can show numerically that the scheme is second-order accurate both in space and time. Moreover, it can not only capture the solution of the diffusion limit equations without requiring the cell size and time step being related to the smallness of the scaling parameters, but also resolve the solution in hyperbolic regime in a natural way. Furthermore, the positive property of the UGKS is analyzed in detail, and through adding time step constraint conditions and applying nodal limiters together, the positive UGKS, called PPUGKS2−order, is obtained. Moreover, in order release the time step constraints in the diffusion regime, a temporal first-order accuracy positive preserving UGKS, called PPUGKS1−order, is proposed. Finally, several numerical tests are included to validate the performance of the proposed schemes.