MDPI publications
Permanent URI for this collectionhttps://hdl.handle.net/10657/15459
This collection gathers materials published by University of Houston authors in MDPI journals
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Item 3D VSP Imaging Using DAS Recording of P- and S-Waves in Vertical and Lateral Well Sections in West Texas(2024-05-11) Wang, Yin-Kai; Stewart, Robert R.A 3D vertical seismic profiling (VSP) survey was acquired using a distributed acoustic sensing (DAS) system in the Permian Basin, West Texas. In total, 682 shot points from a pair of vibroseis units were recorded using optical fibers installed in a 9000 ft (2743 m) vertical part and 5000 ft (1524 m) horizontal reach of a well. Transmitted and reflected P, S, and converted waves were evident in the DAS data. From first-break P and S arrivals, we found average P-wave velocities of approximately 14,000 ft/s (4570 m/s) and S-wave velocities of 8800 ft/s (3000 m/s) in the deep section. We modified the conventional geophone VSP processing workflow and produced P–P reflection and P–S volumes derived from the well’s vertical section. The Wolfcamp formation can be seen in two 3D volumes (P–P and P–S) from the vertical section of the well. They cover an area of 3000 ft (914 m) in the north–south direction and 1500 ft (460 m) in the west–east direction. Time slices showed coherent reflections, especially at 1.7 s (~11,000 ft), which was interpreted as the bottom of the Wolfcamp formation. Vp/Vs values from 2300 ft (701 m) –8800 ft (2682 m) interval range were between 1.7 and 2.0. These first data provide baseline images to compare to follow-up surveys after hydraulic fracturing as well as potential usefulness in extracting elastic properties and providing further indications of fractured volumes.Item A Deep Learning Approach to Lunar Rover Global Path Planning Using Environmental Constraints and the Rover Internal Resource Status(2024-01-28) Tanaka, Toshiki; Malki, HeidarThis research proposes a novel approach to global path and resource planning for lunar rovers. The proposed method incorporates a range of constraints, including static, time-variant, and path-dependent factors related to environmental conditions and the rover’s internal resource status. These constraints are integrated into a grid map as a penalty function, and a reinforcement learning-based framework is employed to address the resource constrained shortest path problem (RCSP). Compared to existing approaches referenced in the literature, our proposed method enables the simultaneous consideration of a broader spectrum of constraints. This enhanced flexibility leads to improved path search optimality. To evaluate the performance of our approach, this research applied the proposed learning architecture to lunar rover path search problems, generated based on real lunar digital elevation data. The simulation results demonstrate that our architecture successfully identifies a rover path while consistently adhering to user-defined environmental and rover resource safety criteria across all positions and time epochs. Furthermore, the simulation results indicate that our approach surpasses conventional methods that solely rely on environmental constraints.Item A Multiuser, Multisite, and Platform-Independent On-the-Cloud Framework for Interactive Immersion in Holographic XR(2024-03-01) Neeli, Hosein; Tran, Khang Q.; Velazco-Garcia, Jose Daniel; Tsekos, Nikolaos V.Background: The ever-growing extended reality (XR) technologies offer unique tools for the interactive visualization of images with a direct impact on many fields, from bioinformatics to medicine, as well as education and training. However, the accelerated integration of artificial intelligence (AI) into XR applications poses substantial computational processing demands. Additionally, the intricate technical challenges associated with multilocation and multiuser interactions limit the usability and expansion of XR applications. Methods: A cloud deployable framework (Holo-Cloud) as a virtual server on a public cloud platform was designed and tested. The Holo-Cloud hosts FI3D, an augmented reality (AR) platform that renders and visualizes medical 3D imaging data, e.g., MRI images, on AR head-mounted displays and handheld devices. Holo-Cloud aims to overcome challenges by providing on-demand computational resources for location-independent, synergetic, and interactive human-to-image data immersion. Results: We demonstrated that Holo-Cloud is easy to implement, platform-independent, reliable, and secure. Owing to its scalability, Holo-Cloud can immediately adapt to computational needs, delivering adequate processing power for the hosted AR platforms. Conclusion: Holo-Cloud shows the potential to become a standard platform to facilitate the application of interactive XR in medical diagnosis, bioinformatics, and training by providing a robust platform for XR applications.Item A New Insight into the Design Compressive Strength of Ultra-High Performance Concrete(2023-11-22) Pourbaba, Masoud; Chakraborty, Rajesh; Pourbaba, Majid; Belarbi, Abdeldjelil; Yeon, Jung HeumCompressive strength is one of the most critical mechanical properties of various types of concrete and is the main input variable for structural concrete design. Recently, with the advances in concrete technology, applications of fiber-reinforced concrete (FRC), including ultra-high performance concrete (UHPC), have grown rapidly. These new types of concrete are well known to exhibit superior mechanical characteristics such as compressive strength, fracture toughness, and durability compared to conventional concrete and thus are popularly used in urgent repair jobs where compressive strength is an important parameter to determine the required curing time until open to the public. Considering the importance of compressive strength in practice, this study aims to evaluate the effect of age and maturity on the compressive strength characteristics of three different types of concrete, namely UHPC with micro and macro steel fibers, FRC, and plain concrete, and to propose a new design strength criterion for UHPC. To this end, 180 concrete cube specimens were tested at 12 different ages between 3 and 126 days. The results indicated that irrespective of the type and presence of fibers, UHPC gained more than 90% of their ultimate compressive strength after only 21 days, while FRC and plain concrete specimens required a longer time (i.e., 28 days) to achieve 90% of their ultimate strength. Therefore, UHPC may adopt a 21-day compressive strength as a design input instead of a 28-day compressive strength commonly required for structural concrete specified by many codes of practice. Moreover, the obtained experimental results were compared with existing compressive strength predictive models in the codes of practice.Item A Study of Convergence of Sixth-Order Contraharmonic-Mean Newton’s Method (CHN) with Applications and Dynamics(2024-01-10) Singh, Manoj K.; Argyros, Ioannis K.; Regmi, SamundraWe develop the local convergence of the six order Contraharmonic-mean Newton’s method (CHN) to solve Banach space valued equations. Our analysis approach is two fold: The first way uses Taylor’s series and derivatives of higher orders. The second one uses only the first derivatives. We examine the theoretical results by solving a boundary value problem also using the examples relating the proposed method with other’s methods such as Newton’s, Kou’s and Jarratt’s to show that the proposed method performs better. The conjugate maps for second-degree polynomial are verified. We also calculate the fixed points (extraneous). The article is completed with the study of basins of attraction, which support and further validate the theoretical and numerical results.Item A Systematic Review of the Effects of Interactive Telerehabilitation with Remote Monitoring and Guidance on Balance and Gait Performance in Older Adults and Individuals with Neurological Conditions(2024-05-06) Park, Catherine; Lee, Beom-ChanRecognizing the growing interests and benefits of technology-assisted interactive telerehabilitation in various populations, the aim of this review is to systematically review the effects of interactive telerehabilitation with remote monitoring and guidance for improving balance and gait performance in older adults and individuals with neurological conditions. The study protocol for this systematic review was registered with the international prospective register of systematic reviews (PROSPERO) with the unique identifier CRD42024509646. Studies written in English published from January 2014 to February 2024 in Web of Science, Pubmed, Scopus, and Google Scholar were examined. Of the 247 identified, 17 were selected after initial and eligibility screening, and their methodological quality was assessed with the National Institutes of Health Quality Assessment Tool for Observational Cohort and Cross-sectional Studies. All 17 studies demonstrated balance and gait performance improvement in older adults and in individuals with stroke, Parkinson’s disease, and multiple sclerosis following 4 or more weeks of interactive telerehabilitation via virtual reality, smartphone or tablet apps, or videoconferencing. The findings of this systematic review can inform the future design and implementation of interactive telerehabilitation technology and improve balance and gait training exercise regimens for older adults and individuals with neurological conditions.Item Accelerating Elastic Property Prediction in Fe-C Alloys through Coupling of Molecular Dynamics and Machine Learning(2024-01-26) Risal, Sandesh; Singh, Navdeep; Yao, Yan; Sun, Li; Risal, Samprash; Zhu, WeihangThe scarcity of high-quality data presents a major challenge to the prediction of material properties using machine learning (ML) models. Obtaining material property data from experiments is economically cost-prohibitive, if not impossible. In this work, we address this challenge by generating an extensive material property dataset comprising thousands of data points pertaining to the elastic properties of Fe-C alloys. The data were generated using molecular dynamic (MD) calculations utilizing reference-free Modified embedded atom method (RF-MEAM) interatomic potential. This potential was developed by fitting atomic structure-dependent energies, forces, and stress tensors evaluated at ground state and finite temperatures using ab-initio. Various ML algorithms were subsequently trained and deployed to predict elastic properties. In addition to individual algorithms, super learner (SL), an ensemble ML technique, was incorporated to refine predictions further. The input parameters comprised the alloy’s composition, crystal structure, interstitial sites, lattice parameters, and temperature. The target properties were the bulk modulus and shear modulus. Two distinct prediction approaches were undertaken: employing individual models for each property prediction and simultaneously predicting both properties using a single integrated model, enabling a comparative analysis. The efficiency of these models was assessed through rigorous evaluation using a range of accuracy metrics. This work showcases the synergistic power of MD simulations and ML techniques for accelerating the prediction of elastic properties in alloys.Item Advancing Point-of-Care Diagnosis: Digitalizing Combinatorial Biomarker Signals for Lupus Nephritis(2024-03-18) Guo, Jiechang; Teymur, Aygun; Tang, Chenling; Saxena, Ramesh; Wu, TianfuTo improve the efficiency and patient coverage of the current healthcare system, user-friendly novel homecare devices are urgently needed. In this work, we developed a smartphone-based analyzing and reporting system (SBARS) for biomarker detection in lupus nephritis (LN). This system offers a cost-effective alternative to traditional, expensive large equipment in signal detection and quantification. This innovative approach involves using a portable and affordable microscopic reader to capture biomarker signals. Through smartphone-based image processing techniques, the intensity of each biomarker signal is analyzed. This system exhibited comparable performance to a commercial Genepix scanner in the detection of two potential novel biomarkers of LN, VISG4 and TNFRSF1b. Importantly, this smartphone-based analyzing and reporting system allows for discriminating LN patients with active renal disease from healthy controls with the area-under-the-curve (AUC) value = 0.9 for TNFRSF1b and 1.0 for VSIG4, respectively, indicating high predictive accuracy.Item An Extensive Investigation into the Use of Machine Learning Tools and Deep Neural Networks for the Recognition of Skin Cancer: Challenges, Future Directions, and a Comprehensive Review(2024-03-18) Hussain, Syed Ibrar; Toscano, ElenaSkin cancer poses a serious risk to one’s health and can only be effectively treated with early detection. Early identification is critical since skin cancer has a higher fatality rate, and it expands gradually to different areas of the body. The rapid growth of automated diagnosis frameworks has led to the combination of diverse machine learning, deep learning, and computer vision algorithms for detecting clinical samples and atypical skin lesion specimens. Automated methods for recognizing skin cancer that use deep learning techniques are discussed in this article: convolutional neural networks, and, in general, artificial neural networks. The recognition of symmetries is a key point in dealing with the skin cancer image datasets; hence, in developing the appropriate architecture of neural networks, as it can improve the performance and release capacities of the network. The current study emphasizes the need for an automated method to identify skin lesions to reduce the amount of time and effort required for the diagnostic process, as well as the novel aspect of using algorithms based on deep learning for skin lesion detection. The analysis concludes with underlying research directions for the future, which will assist in better addressing the difficulties encountered in human skin cancer recognition. By highlighting the drawbacks and advantages of prior techniques, the authors hope to establish a standard for future analysis in the domain of human skin lesion diagnostics.Item Analysis of Wildfire Susceptibility by Weight of Evidence, Using Geomorphological and Environmental Factors in the Marche Region, Central Italy(2024-04-24) Gentilucci, Matteo; Barbieri, Maurizio; Younes, Hamed; Rihab, Hadji; Pambianchi, GilbertoFires are a growing problem even in temperate climate areas, such as those in Central Italy, due to climate change leading to longer and longer periods of drought. Thus, knowing the fire susceptibility of an area is crucial for good planning and taking appropriate countermeasures. In this context, it was decided to use only causal factors of a geomorphological and environmental nature in order to obtain a fire susceptibility analysis that can also be applied to climatically under-sampled areas. Vector data of fires in Central Italy from 2005 to 2023 were collected, and the correct areal extent was calculated for each. At the same time, six factors were selected that could have an influence on fire development, such as ecological units, topographic wetness index (TWI), geology, slope, exposure, and altitude. The model was obtained by means of the weight of evidence statistical method, which takes into account past data by reinterpreting them in a future-oriented way on the basis of the identified factors and classes. The model was validated with a test sample and shows an area under the curve (AUC) value of 0.72 with a reliability that can be described as good considering the total absence of climatic factors that are known to play a major role in fire development. Furthermore, the identified causal factors were divided into classes, and these were carefully weighted in order to define their relative influence in the study area. Particularly Ecological Units with characteristic and well-defined contrast (C) values, which could lead to a more complete definition of forests that tend to increase fire susceptibility and those that tend to decrease it, allowing the latter to be exploited as a hazard mitigation agent.Item Analyzing the Performance of Millimeter Wave MIMO Antenna under Different Orientation of Unit Element(2023-10-24) Islam, Tanvir; Alsunaydih, Fahad N.; Alsaleem, Fahd; Alhassoon, KhaledIn this paper, a compact and simplified geometry monopole antenna with high gain and wideband is introduced. The presented antenna incorporates a microstrip feedline and a circular patch with two circular rings of stubs, which are inserted into the reference circular patch antenna to enhance the bandwidth and return loss. Roger RT/Duroid 6002 is used as the material for the antenna, and has overall dimensions of WS × LS = 12 mm × 9 mm. Three designs of two-port MIMO configurations are derived from the reference unit element antenna. In the first design, the antenna element is placed parallel to the reference antenna, while in the second design, the element is placed orthogonal to the reference element of the antenna. In the third design, the antenna elements are adjusted to be opposite each other. In this study, we analyze the isolation between the MIMO elements with different arrangements of the elements. The MIMO configurations have dimensions of 15 mm × 26 mm for two of the cases and 15 mm × 28.75 mm for the third case. All three MIMO antennas are made using similar materials and have the same specifications as the single element antenna. Other significant MIMO parameters, including the envelope correlation coefficient (ECC), diversity gain (DG), channel capacity loss (CCL), and mean effective gain (MEG), are also researched. Additionally, the paper includes a table summarizing the assessment of this work in comparison to relevant literature. The results of this study indicate that the proposed antenna is well-suited for future millimeter wave applications operating at 28 GHz.Item Androgen Receptor in Hormone Receptor-Positive Breast Cancer(2023-12-29) Khan, Ashfia Fatima; Karami, Samaneh; Peidl, Anthony S.; Waiters, Kacie D.; Babajide, Mariam Funmi; Bawa-Khalfe, TasneemBreast cancer subtypes expressing hormone receptors (HR+ BCa) have a good prognosis and respond to first-line endocrine therapy (ET). However, the majority of HR+ BCa patients exhibit intrinsic or acquired ET resistance (ET-R) and rapid onset of incurable metastatic BCa. With the failure of conventional ET, limited targeted therapy exists for ET-R HR+ BCa patients. The androgen receptor (AR) in HR-negative BCa subtypes is emerging as an attractive alternative target for therapy. The AR drives Luminal AR (LAR) triple-negative breast cancer progression, and LAR patients consistently exhibit positive clinical benefits with AR antagonists in clinical trials. In contrast, the function of the AR in HR+ BCa is more conflicting. AR in HR+ BCa correlates with a favorable prognosis, and yet, the AR supports the development of ET-R BCa. While AR antagonists were ineffective, ongoing clinical trials with a selective AR modulator have shown promise for HR+ BCa patients. To understand the incongruent actions of ARs in HR+ BCa, the current review discusses how the structure and post-translational modification impact AR function. Additionally, completed and ongoing clinical trials with FDA-approved AR-targeting agents for BCa are presented. Finally, we identify promising investigational small molecules and chimera drugs for future HR+ BCa therapy.Item Application of Natural-Resource-Based View to Nature-Based Tourism Destinations(2024-03-13) Wang, Xi; Kim, Jewoo; Kim, Jaewook; Koh, YoonThe present study investigates the impact of natural environments on tourism destinations in a holistic approach. Specifically, the impact of accessibility to beaches and environmental quality aspects (temperature, visibility, air quality, and water quality) on tourism businesses can be accessed based on a natural-resource-based view. Dynamic panel estimation is employed to analyze the financial performance of U.S. coastal hotels between 2008 and 2017. By employing the Generalized Method of Moments (GMM) analysis, this aims to estimate coefficients consistently and impartially, thereby addressing endogeneity issues. According to findings of the present study, as hotels are close to beaches, they earn higher revenues and higher revenue per-available-room. Also, all four environmental factors are significant on coastal hotels’ financial performance. These findings underscore the importance of beach and environmental factors as location-specific tourism resources that provide a competitive advantage and demonstrate the application of natural-resource-based view to tourism destinations.Item Aspectual se and Telicity in Heritage Spanish Bilinguals: The Effects of Lexical Access, Dominance, Age of Acquisition, and Patterns of Language Use(2023-08-29) Martínez Vera, Gabriel; López Otero, Julio César; Sokolova, Marina Y.; Cleveland, Adam; Marshall, Megan Tzeitel; Sánchez, LilianaWhile differences in the production and acceptability of aspectual inflectional morphology between Spanish–English heritage and monolingually raised speakers of Spanish have been argued to support incomplete acquisition approaches to heritage language acquisition, other approaches have argued that differences in access (e.g., lexical access) to representations for receptive and productive purposes are at the core of some of the unique characteristics of heritage language data. We investigate these issues by focusing on the effects of lexical access, dominance, age of acquisition and patterns of language use in heritage Spanish–English bilinguals. We study aspectual se in Spanish, which yields telic interpretations, in expressions such as María se comió la manzana ‘María ate the apple (completely)’ and Maria ate the apple (where completion may not be reached). Our results indicate that se generates telic interpretations for the heritage and monolingually raised group with no group effect. Heritage speakers showed no English effects in terms of lexical access, age of acquisition, patterns of language use or dominance. This suggests that the heritage group did not differ from their monolingually raised counterparts and showed no evidence of incomplete acquisition of telicity.Item Asymptotically Newton-Type Methods without Inverses for Solving Equations(2024-04-02) Argyros, Ioannis K.; George, Santhosh; Shakhno, Stepan; Regmi, Samundra; Havdiak, Mykhailo; Argyros, Michael I.The implementation of Newton’s method for solving nonlinear equations in abstract domains requires the inversion of a linear operator at each step. Such an inversion may be computationally very expensive or impossible to find. That is why alternative iterative methods are developed in this article that require no inversion or only one inversion of a linear operator at each step. The inverse of the operator is replaced by a frozen sum of linear operators depending on the Fréchet derivative of an operator. The numerical examples illustrate that for all practical purposes, the new methods are as effective as Newton’s but much cheaper to implement. The same methodology can be used to create similar alternatives to other methods using inversions of linear operators such as divided differences or other linear operators.Item Attachment-Based Mentalization Profiles of Iranian Children: A Mixed-Method Approach(2024-02-17) Zandpour, Masoumeh; Lind, Majse; Sharp, Carla; Hasani, Jafar; Bagheri Sheykhangafshe, Farzin; Borelli, Jessica L.Mentalization, operationalized as reflective functioning (RF), is the ability to understand one’s own and another’s mental world implicitly or explicitly. RF is a newly discovered research field in Iran and is largely under-studied in Eastern cultures in general, underscoring the high need for cross-cultural studies in this field of research. A qualitative method was used to examine the ability to understand, process, and respond to high-arousal attachment situations in typical and clinical populations of Iranian children recruited from a Tehran primary school. A well-known semi-structured interview commonly used to assess RF in children was used to collect data. Required information on internalizing and externalizing symptoms, demographic information, and all formal diagnoses of children were collected by parents. The results indicated the identification of four different profiles of RF in children, one of which was adaptive, while the other three were maladaptive. Also, the results showed that typically developing children and those having a high social and economic status (SES) were characterized as having a more adaptive profile of RF, while children from the clinical population and those with a low SES reported a more maladaptive profile (passive mentalizing, helpless mentalizing, narcissistic mentalizing) of RF. The present study is an important step in increasing our understanding of the development of mentalization in children and has significant educational and clinical implications.Item CO2 Injection Monitoring: Enhancing Time-Lapse Seismic Inversion for Injected Volume Estimation in the Utsira Formation, Sleipner Field, North Sea(2023-11-30) Pelemo-Daniels, Doyin; Nwafor, Basil O.; Stewart, Robert R.This article presents an in-depth study of CO2 injection monitoring in the Sleipner Field, focusing on the Utsira Formation. The research leverages advanced time-lapse inversion techniques and 4D seismic data analysis to enhance the accuracy of volume estimations and provide a comprehensive understanding of the dynamic behavior of the injected CO2 plume. The analysis encompasses cross correlation, time shift, predictability, and other key elements to yield robust insights into the reservoir’s response to CO2 injection. Cross-correlation analysis results of 60% to 100% outside the injection zone and less than 50% within the injection zone reveal a distinct dissimilarity between the injection and non-injection zones, emphasizing phase, time, and frequency content changes due to CO2 injection. Time shifts are meticulously calibrated globally on a trace-by-trace basis, to account for shallow statics and velocity changes, improving the overall alignment of seismic data. Predictability analysis results of 0 to 0.34 within the injection zone and 0.45 to 0.96 at the background further reinforce the findings, highlighting high predictability values in areas untouched by production and markedly lower values within the injection zone. These results provide a measure of the reliability of the seismic data and its ability to reflect the subtle changes occurring in the reservoir. Crucially, the time-lapse inversion process excels in capturing the evolving state of the CO2 plume within the Utsira Formation. The seismic data reveals the migration and expansion of the plume over time and the dynamic nature of the reservoir’s response to CO2 injection. Integrating various data facets reduces non-uniqueness in inversion results, allowing for more precise volume estimations.Item Comparison between Two Competing Newton-Type High Convergence Order Schemes for Equations on Banach Spaces(2023-10-30) Argyros, Ioannis K.; Singh, Manoj K.; Regmi, SamundraWe carried out a local comparison between two ninth convergence order schemes for solving nonlinear equations, relying on first-order Fréchet derivatives. Earlier investigations require the existence as well as the boundedness of derivatives of a high order to prove the convergence of these schemes. However, these derivatives are not in the schemes. These assumptions restrict the applicability of the schemes, which may converge. Numerical results along with a boundary value problem are given to examine the theoretical results. Both schemes are symmetrical not only in the theoretical results (formation and convergence order), but the numerical and dynamical results are also similar. We calculated the convergence radii of the nonlinear schemes. Moreover, we obtained the extraneous fixed points for the proposed schemes, which are repulsive and are not part of the solution space. Lastly, the theoretical and numerical results are supported by the dynamic results, where we plotted basins of attraction for a selected test function.Item Comparison of EV Fast Charging Protocols and Impact of Sinusoidal Half-Wave Fast Charging Methods on Lithium-Ion Cells(2024-02-06) Althurthi, Sai Bhargava; Rajashekara, Kaushik; Debnath, TutanIn electric vehicle fast charging systems, it is important to minimize the effect of fast charging on the grid and it is also important to operate the charging system at high efficiencies. In order to achieve these objectives, in this paper, a sinusoidal half-wave DC current charging protocol and a sinusoidal half-wave pulsed current charging protocol are proposed for the fast charging of Li-ion batteries. A detailed procedure is presented for implementing the following proposed methods: (a) a pre-defined half-sine wave current function and (b) a pulsed half-sine wave current method. Unlike the conventional full-wave sinusoidal ripple current charging protocols, the proposed study does not utilize any sinusoidal full-wave ripple. The performance of these new charging methods on Ni-Co-Al-type Li-cells is studied and compared with the existing constant current and positive pulsed current charging protocols, which have been discussed in the existing literature. In addition, the changes in the electrochemical impedance spectrograph of each cell are examined to study the effects of the applied charging methods on the internal resistance of the Li cell. Finally, the test results are presented for 250 life cycles of charging at 2C (C: charging rate) and the degradation in cell capacities are compared among the four different methods for the Ni-Co-Al-type Li cell.Item Convergence of Derivative-Free Iterative Methods with or without Memory in Banach Space(2023-09-19) George, Santhosh; Argyros, Ioannis K.; Regmi, SamundraA method without memory as well as a method with memory are developed free of derivatives for solving equations in Banach spaces. The convergence order of these methods is established in the scalar case using Taylor expansions and hypotheses on higher-order derivatives which do not appear in these methods. But this way, their applicability is limited. That is why, in this paper, their local and semi-local convergence analyses (which have not been given previously) are provided using only the divided differences of order one, which actually appears in these methods. Moreover, we provide computable error distances and uniqueness of the solution results, which have not been given before. Since our technique is very general, it can be used to extend the applicability of other methods using linear operators with inverses along the same lines. Numerical experiments are also provided in this article to illustrate the theoretical results.