Correct Solution Research Articles

The Effectiveness of Feedback Provided by Middle School Mathematics Teachers and Preservice teachers on Student Solutions: An Evaluative Study

The aim of this study is to reveal the suggestions of middle school mathematics teachers and preservice mathematics teachers that can both correct errors in students’ incorrect solutions and contribute to the advancement of students who have provided correct solutions. The study is based on the case study method. Initially, six problems related to proportional reasoning were posed to middle school students in a public school, and the solutions obtained from the students were classified according to their proportional reasoning strategies. These solutions were then examined by the students' mathematics teachers and by preservice mathematics teachers. Two questions were asked to mathematics teachers and preservice mathematics teachers during these examinations. After the examination, interviews were conducted to discuss the suggestions made to (1) correct the errors in incorrect solutions and (2) advance the proportional reasoning skills of students who obtained correct solutions. The findings indicate that both mathematics teachers and preservice mathematics teachers were adequate in providing suggestions to correct errors in students’ incorrect solutions. However, it was also found that both groups had difficulties in making suggestions to further the advancement of students who provided correct solutions.

Vision-based target localization and online error correction for high-precision robotic drilling

Abstract This article presents a detailed examination of circular target localization techniques for measuring robot pose and performing online pose correction. The investigated target localization methods include centroiding, ellipse fitting with point data and gradient information, and ellipse fitting methods with augmented and corrected input data. The performance of each method is evaluated in terms of accuracy and precision of measurements through experimental comparison with a laser tracker. This study provides technical and practical insights for selecting an appropriate target localization method in robotic applications. It also introduces a vision-based solution for robot relative error correction, comprising the calibration procedure and a closed-loop control with a proportional–integral-derivative controller for pose correction. Results show enhanced accuracy in robot positioning relative to workpiece, highlighting the effectiveness of the proposed solution in robotic drilling applications.

Geotechnical Justification for Designing Landslide Prevention Measures

Abstract When designing anti-landslide measures, slope stability assessment is an important factor and is determined by conducting comprehensive engineering and geological studies on a slope with potential landslide risks. The results of correct engineering and geological justification for the design of anti-landslide measures lead to the preservation of the structure and safe operation of infrastructure facilities. Our experience shows that to eliminate the negative effects of landslide processes, it is necessary to accurately determine the engineering and geological conditions of the slope, including the stability of the slope, taking into account natural dynamic phenomena (seismicity of the territory and tectonic processes) and, if possible, to see the complete elimination of the causes that lead to landslide processes when developing anti-landslide measures. To achieve these goals, the geotechnical justification of the design is the only correct solution. Geotechnical justification of protective measures intended to protect the structural elements of the Baku-Russian Federation State Border highway, which is part of the north-south transport corridor and passes through the foot of a potentially landslide-hazardous slope west of the city of Shabran, is one of the most important conditions that increase the effectiveness of these measures. On a slope located 1500 meters southwest of the current research area, the results of our scientific research were not properly utilized and many of our warnings were not heeded, resulting in a landslide during construction, leading to serious damage to the road's structural elements (Fig. 1) and additional costs. This event once again confirms that landslides are the most common natural and man-made processes that pose a threat to the safe operation of infrastructure facilities, civil and industrial construction in mountainous and foothill areas (Shiraliyev et al., 2024)

Solving large-scale instances of the urban transit routing problem with a parallel artificial bee colony-hill climbing optimization algorithm

Swarm Intelligence simulates the collective behavior of decentralized and self-organized swarms. One of the main relevant methods is the Artificial Bee Colony (ABC) algorithm which simulates the foraging behavior of bee swarms in a colony to produce efficient solutions to various problems. The Urban Transit Routing Problem (UTRP) involves finding an efficient set of routes in a transit network to satisfy travel demand subject to operational and budget constraints. It is a complex, NP-Hard problem, in which otherwise correct solutions can be rejected because of impracticability. In this study, a hybrid algorithm consisting of a parallel ABC and Hill Climbing was used to find quality solutions to the UTRP. Thorough comparative results on Mandl’s well-known instance and Mumford’s large-scale instances demonstrate that the proposed algorithm outperforms existing techniques, achieving high levels of direct trip coverage in small computational times. Remarkably, when applied to the most extensive benchmark comprising over 6 million trips and 60 bus routes, the proposed algorithm demonstrates an impressive 11 % enhancement in direct coverage over the previously best-reported results, allowing the design of real-world bus networks in under 3 hours.

An in-depth study of sorting algorithms

Sorting algorithms are very popular fundamental algorithms in the field of computer science. Its job is sorting statistics so that they are arranged according to certain rules. In this paper, the kinds of sorting algorithms and their research method of them will be discussed. It will consist of discussing bubble sort, selection sorting, insertion sorting, hill sorting, and merge sorting. Those of them are that arrange a group of elements according to a certain number of ones. They are widely used in computer science and data processing in all walks of life. The most common sorting methods are numerical order and lexicographic order. Efficient sorting algorithms are significant in some of the algorithms, such as search and merge algorithms, so that they can arrive at the correct solution. Dealing with textual data and producing readable output are also important applications of sorting. The outcome is a permutation or recombination of the original input. So learning about the principles of those sorting algorithms by recognizing the code or reading pictures is significant. It is also necessary to be familiar with the applications of those algorithms which are beneficial to the daily life.

Impact performance of egg‐box core sandwich panels made from sisal fibers and castor‐oil‐based polymer

AbstractDeveloping sustainable composites for engineering applications is essential for minimizing environmental impacts and ensuring the long‐term viability of infrastructure and technological advancements. In this context, this work focuses on the manufacture and evaluation of the structural integrity of a sandwich structure composed of aluminum faces and egg‐box‐shaped, sisal fiber‐reinforced epoxy (SFE) or castor‐oil polyurethane (SFC‐O) composites. The sandwich panel is filled with a biobased foam and subjected to dynamic load (drop‐tower) test. For comparison, the base materials SFE and SFC‐O molded into the egg‐box‐shaped cores are also evaluated using Charpy impact tests to establish a potential correlation between their Charpy performance and the drop‐tower behavior of egg‐box sandwich structures. The findings reveal that SFC‐O laminates demonstrate superior Charpy impact resistance (~49%) compared to SFE laminates. Similarly, sandwich structures composed of egg‐box‐castor‐oil composite cores absorb approximately 42.5% more energy than those made with egg‐box‐epoxy cores. The impact behavior of the sandwich structures correlates directly with the impact resistance of the sisal fiber laminates. Overall, the results indicate that the castor‐oil polymer can effectively replace the epoxy polymer matrix phase, enhancing impact absorption and providing an environmentally correct and sustainable solution for fabricating sandwich panels.Highlights Castor‐oil polymer provides laminates with lower density relative to epoxy. Sisal‐castor‐oil‐based laminates possess higher impact resistance than those based on epoxy. Sisal‐castor‐oil‐based panels achieve higher absolute and specific drop‐tower impact properties. Panels subjected to drop‐tower impact tests reveal skin delamination, wrinkling and indentation. Debonding between the foam and egg‐box core is a typical failure mode for epoxy sandwich panels.

A concept of controlling Grover diffusion operator: a new approach to solve arbitrary Boolean-based problems

A controlled-diffusion operator for Boolean oracles is designed as a new approach for Grover’s algorithm to search for solutions for arbitrary logical structures of such oracles, since the Grover diffusion operator is not able to find correct solutions for some logical structures of Boolean oracles. We also show that the Phase oracles do not work sometimes correctly using the Grover diffusion operator. Our proposed controlled-diffusion operator relies on the states of output qubit, as the reflection of Boolean decisions from a Boolean oracle without relying on the phase kickback. We prove that on many examples of Boolean and Phase oracles the Grover diffusion operator is not working correctly. The oracles in these examples are constructed using different structures of POS, SOP, ESOP, CSP-SAT, and XOR-SAT. Our mathematical models and experiments prove that the proposed controlled-diffusion operator successfully searches for all solutions for all Boolean oracles regardless of their different logical structures.

Estimation of electrical conductivity models using multi-coil rigid-boom electromagnetic induction measurements

Electromagnetic induction measurements from multi-coil configuration instruments are used to obtain information about the electrical conductivity distribution in the subsurface. The resulting inverse problem might not have a unique and stable solution. In that case, a local inversion method can be trapped in a local minimum and lead to an incorrect solution. In this study, we evaluate the well-posedness of the inverse problem for two and three-layered electrical conductivity models. We show that for a two-layered model, uniqueness is ensured only when both in-phase and quadrature data are available from the measurements. Results from a Gauss–Newton inversion and a lookup table demonstrate that the solution space is convex. Furthermore, we demonstrate that for even a simple three-layered model, the data contained in such measurements are insufficient to reach a correct or stable solution. For models with more than 2 layers, independent prior information is necessary to solve the inverse problem. The insights from the numerical examples are applied in a field case.

State-of-the-Art Power Factor Correction: An Industry Perspective

On 1 January 2001, the IEC 61000-3-2 regulation became effective. Since then, mitigating current harmonics has been essential to ensure that electronic equipment connected to single-phase power distribution lines conforms to electromagnetic compatibility directives. Today, high-quality rectification, commonly known as power factor correction (PFC), is a well-established technique widely adopted by the industry for powering various devices from the ac line. The topic has been studied by academia and industry since the mid-1980s; thus, an enormous amount of research has been published and countless solutions have been proposed since then. However, only a few of those solutions have encountered wide industrial usage. So, it is not the authors’ intention to provide a comprehensive review, but to take stock of the most used PFC techniques from an industry perspective. This paper will review the power factor theory with non-sinusoidal currents, the practical and regulatory aspects of using PFC, and the most common industry solutions for power factor correction in equipment operated from the single-phase, public, low-voltage supply system, with a special focus on boost PFC pre-regulators, their control methods, design procedures, and issues.

Two highly accurate and efficient numerical methods for solving the fractional Liénard’s equation arising in oscillating circuits

In this paper, we investigate the fractional model of the Liénard and Duffing equations with the Liouville-Caputo fractional derivative. These equations grow with the evolution of radio and vacuum tube technology, which describe oscillating circuits and generalize the spring–mass device equation. We compare two numerical approaches, namely Jacobi and Haar wavelet collocation methods. The given approaches are used to discretize and transform the equation into a system of algebraic equations, and the Broyden-Quasi Newton algorithm is applied to solve the resulting nonlinear system of equations. A complete error analysis and convergence rates for different grid sizes are derived for both methods, which are used to compare the accuracy and efficiency of the two approaches. While both approaches produce correct solutions, according to the numerical findings, the Jacobi collocation method is more efficient and accurate than the Haar wavelet collocation method.

How Iran’s Hospital Accreditation Program Meets the International Society for Quality in Health Care (ISQua)

Background: Hospital health service quality is a fundamental component of the health system. Hospital accreditation is a key approach to enhancing this quality, necessitating the correct implementation of processes. Objectives: This study aims to investigate the compliance of the executive processes of Iran’s hospital accreditation program with the requirements of the International Society for Quality in Health Care and to provide corrective solutions. Methods: This qualitative study uses an inductive content analysis technique. A checklist with seven axes was established by extracting and interpreting the requirements of the executive processes from the International Society for Quality in Health Care. By examining existing documents at the Ministry of Health’s Accreditation Office and conducting interviews with managers and experts in the field, challenges in the domain of the executive processes of Iran’s hospital accreditation program were identified using the relevant checklist. Corrective solutions were then gathered through semi-structured interviews with 19 experts, managers, and accreditation field specialists, categorized inductively, and presented using MAXQDA software. Results: Challenges in seven areas were identified, including governance; strategic, operational and financial management; risk management; human resources management; information management; survey and client management; and the granting of accreditation approval. Subsequently, solutions were categorized into five groups encompassing 26 concepts, focusing on reforming macro policies, addressing implementation challenges, fostering appropriate interactions, improving human resource management, and promoting evidence-based decision-making. Conclusions: The Iran hospital accreditation program’s adherence to International Society for Quality in Health Care standards is inadequate. Establishing a semi-autonomous, non-profit accreditation body that operates under government control and ensuring the independence of the accreditation office is essential for achieving higher compliance and receiving certification from International Society for Quality in Health Care.

ARCIMBOLDO at low resolution: Verification for coiled coils and globular proteins.

Crystallography at low resolution must determine the atomic model from less experimental observations, which is challenging in the absence of a model. In addition, model bias is more severe when independent experimental data are scarce. Our methods solve the phase problem by combining the location of accurate model fragments using Phaser with density modification and interpretation of the resulting maps using SHELXE. From a partial, correct structure, the density modification process and the stereochemical constraints draw the rest of the structure, validating the result. This same principle is now exploited at low resolution. Coiled coils are important, ubiquitous structures but notoriously difficult to phase and to predict. Both correct solutions and incorrect ones are poorly discriminated by the crystallographic figures of merit as long as helices are correctly oriented. We incorporate coiled-coil verification, designed to set up competing, incompatible structural hypotheses to probe both the results and establish the power of the data to discriminate them. Efficiency of coiled-coil phasing and validation in test cases from 3 to 4 Å is demonstrated in ARCIMBOLDO_LITE, placing single helices, and in ARCIMBOLDO_SHREDDER, with fragments derived from AlphaFold models. SHELXE tracing at low resolution has been enhanced, maintaining its local character but extending the environment assessment. For non-helical structures, verification is demonstrated in the fragment location process. Its use is exemplified with the solution of the VSR1 structure at 3.5 Å, depending on LLG optimization and the emergence of new features in the electron density. Relying on verification, we have extended the use of the ARCIMBOLDO software to low resolution.

Patient-Specific Rods in Adolescent and Adult Spinal Deformity Surgery: A Narrative Review.

Spinal deformity surgery often requires complex surgical interventions that can have a drastic effect on both patient quality of life and functional capacity. Modern-day corrective solutions for these deformities include spinal osteotomies, pedicle screw instrumentation, and dual/multirod constructs. These solutions are efficacious and are currently considered standard practice for spinal surgeons, but they lack individualization. Patient-specific rods (PSRs) are a novel technology that attempts to offer a personalized approach to spinal deformity correction based on preoperative computerized tomography scans. Moreover, PSRs may offer several advantages to conventional rods, which include achievement of desired rod contour angles according to surgical planning alignment goals, reduced operative time, and reduced blood loss. In adolescent idiopathic scoliosis, those instrumented with PSR have observed coronal Cobb reductions up to 74%. In adult spinal deformity, PSRs have offered superior correction in radiographic parameters such as sagittal vertical axis and pelvic incidence minus lumbar lordosis. However, there still remains a paucity of research in this area, mainly in health care expenditure, cost-effectiveness, and longitudinal clinical outcomes. The purpose of this article is to survey the current body of knowledge of PSR instrumentation in both adolescent and adult spinal deformity populations. The current strength, limitations, and future directions of PSRs are highlighted throughout this article.

How to support self-assessment through standards in dissimilar-solution-tasks

BackgroundProviding learners with standards, which represent correct solutions to a task, is a promising means to support self-assessment. To date, however, the evidence in support of standards mainly stems from studies that used tasks for which correct solutions are very similar to each other in terms of both structural and surface features. By contrast, for tasks for which correct solutions are similar to each other only in terms of structural features, empirical evidence is scarce. AimsThe goals of the present study were to investigate the effects of standards in tasks for which correct solutions are similar to each other only in terms of structural features. SamplesParticipants were NExp1 = 139 and NExp2 = 170 university students. MethodsUsing the task of generating examples that illustrate previously encountered declarative concepts, we varied whether in self-assessing the quality of their examples learners received standards (with vs. without) and structural comparison/processing support (with vs. without) that supported learners in processing the critical structural features of the standards and their own examples. ResultsStandards increased self-assessment accuracy and performance. The effects concerning self-assessment accuracy could be enhanced by additionally providing structural comparison support. ConclusionsWe conclude that standards are a promising means to support self-assessment accuracy in tasks for which correct solutions are similar to each other only in terms of structural features. However, their effectiveness depends on the degree to which learners compare their products and the standards in terms of structural features, which needs to be supported.

Geometric Factor Correction Algorithm Based on Temperature and Humidity Profile Lidar

Due to the influence of geometric factors, the temperature and humidity profile of lidar’s near-field signal was warped when sensing the air environment. In order to perform geometric factor correction on near-field signals, this article proposes different correction solutions for the Mie and Raman scattering channels. Here, the Mie scattering channel used the Raman method to invert the aerosol backscatter coefficient and correct the extinction coefficient in the transition zone. The geometric factor was the ratio of the measured signal to the forward-computed vibration Raman scattering signal. The aerosol optical characteristics were reversed using the corrected echo signal, and the US standard atmospheric model was added to the missing signal in the blind zone, reflecting the aerosol evolution process. The stability and dependability of the proposed algorithm were validated by the consistency between the visibility provided by the Environmental Protection Agency and the visibility acquired via lidar retrieval data. The near-field humidity data were supplemented by the interpolation method in the Raman scattering channel to reflect the water vapor transfer process in the temporal dimension. The measured transmittance curve of the filter, the theoretical normalized spectrum, and the sounding data were used to compute the delay geometric factor. The temperature was retrieved and the near-field signal distortion issue was resolved by applying the corrected quotient of the temperature channel. The proposed algorithm exhibited robustness and universality, enhancing the system’s detection accuracy compared to the temperature and humidity data constantly recorded by the probes in the meteorological gradient tower, which have a high correlation with the lidar observation data. The comparison between lidar data and instrument monitoring data showed that the proposed algorithm could effectively correct distorted echo signals in the transition zone, which was of great value for promoting the application of lidar in the meteorological monitoring of the urban canopy layer.

ANALISIS KEMAMPUAN PEMECAHAN MASALAH MATEMATIKA PADA MATERI PERSAMAAN DAN PERTIDAKSAMAAN LINEAR SATU VARIABEL

This study was conducted with the primary aim of evaluating and deeply understanding students' abilities in solving mathematical problems, specifically focusing on Linear Equations and Inequalities with One Variable (SPLSV). A qualitative approach was chosen because it allows researchers to delve deeper into students' thought processes and how they approach given mathematical problems. Descriptive analysis was used to interpret data systematically and in detail, enabling researchers to identify specific patterns in test data and interviews. Adab Kesuma Bangsa Junior High School in Natar, South Lampung, was selected as the research site because it was considered representative of the student population being studied. A total of 32 students participated in this study, selected through Purposive Sampling method. The research instruments used included written tests and in-depth interviews. The main indicators focused on in this research were: (1) understanding of the problem, which measured how well students could identify and comprehend key elements of mathematical problems; (2) solution planning, which assessed students' ability to formulate effective strategies or steps to solve problems; (3) solution implementation, which observed to what extent students could apply their plans in practice and achieve correct solutions; and (4) re-evaluation, which evaluated students' ability to reflect on their processes and outcomes, identifying errors or areas for improvement. The research findings indicated that only a small proportion of students (21.5%) demonstrated high problem-solving abilities. Approximately 11.5% were at a moderate level, while the majority of students (67%) exhibited low problem-solving abilities. These findings provide valuable insights for educators and policymakers regarding the need for more effective educational interventions to enhance students' mathematical problem-solving abilities

Atomic resolution coherent x-ray imaging with physics-based phase retrieval

Coherent x-ray imaging and scattering from accelerator based sources such as synchrotrons continue to impact biology, medicine, technology, and materials science. Many synchrotrons around the world are currently undergoing major upgrades to increase their available coherent x-ray flux by approximately two orders of magnitude. The improvement of synchrotrons may enable imaging of materials in operando at the atomic scale which may revolutionize battery and catalysis technologies. Current algorithms used for phase retrieval in coherent x-ray imaging are based on the projection onto sets method. These traditional iterative phase retrieval methods will become more computationally expensive as they push towards atomic resolution and may struggle to converge. Additionally, these methods do not incorporate physical information that may additionally constrain the solution. In this work, we present an algorithm which incorporates molecular dynamics into Bragg coherent diffraction imaging (BCDI). This algorithm, which we call PRAMMol (Phase Retrieval with Atomic Modeling and Molecular Dynamics) combines statistical techniques with molecular dynamics to solve the phase retrieval problem. We present several examples where our algorithm is applied to simulated coherent diffraction from 3D crystals and show convergence to the correct solution at the atomic scale.

Structural Bone Grafting with Reverse Shoulder Arthroplasty for Osteoarthritis with Severe Glenoid Bone Loss: outcomes using a long post

Severe posterior glenoid bone loss with glenohumeral osteoarthritis with an intact rotator cuff can be managed with reverse shoulder arthroplasty but requires lateralization and version correction to avoid potential complications, such as instability, notching and implant failure. Angled bone grafting with humeral head autograft can provide durable glenoid bone stock, but results have been mixed. The purpose of this study was to evaluate patient-reported and objective outcomes as well as complication and failure rates for patients who underwent angled humeral head autografting for severe retroversion. All patients who underwent a primary RSA with angled humeral head autograft and Stryker Tornier long central post baseplate for severe glenoid bone loss in the setting of glenohumeral osteoarthritis with an intact rotator cuff at our institution between November 2018 and February of 2022 were identified. Individuals with a primary diagnosis of osteoarthritis and preoperative glenoid retroversion of ≥30° were included. Patients undergoing revision procedures, planned two-stage arthroplasty were excluded. Differences in pre- and postoperative range of motion, as well as patient-reported outcomes were assessed. Intraoperative complications, postoperative complications, and re-operation rates were analyzed. A total of 24 shoulders in 23 patients (61% male), with a mean age of 65.6 years were included. Average preoperative retroversion was 37.4° (range: 30° - 51°). Mean follow-up was 2.9 years (range: 2 - 4.3 years). Significant improvements were found in flexion, abduction, and external rotation. Patient-reported subjective outcomes were excellent, with average ASES score of 93.6 and average SSV 93.8%. Sixteen (67%) shoulders received postoperative CT scans and all were found to have incorporated. Complications included one shoulder hematoma requiring incision and drainage without revision, and a post-traumatic fracture of the inferior glenoid screw at 11 months, requiring revision RSA with bone grafting. No atraumatic catastrophic failures occurred due to component loosening. This study suggests that using angled humeral head bone grafting is a good solution for version correction in extreme posterior glenoid bone loss. Significant improvements are reported in ROM, pain, and subjective functional scores, with excellent graft incorporation rates and a low complication profile at early follow-up. Further work should focus on gathering higher levels of evidence, detailed radiographic analyses and exploring humeral head bone grafting for other indications.

Implementation of a Drift Flux Model into SAM with Development of a Verification and Validation Test Suite for Modeling of Noncondensable Gas Mixtures

The advanced thermal-hydraulic system code, System Analysis Module (SAM), was originally developed for the modeling of single-phase flow in advanced reactors. It has since been expanded to include a four-equation drift flux model for the modeling of two-phase flows containing a noncondensable gas. The model was expanded to support the modeling of molten salt reactor (MSR) designs in which the fuel is directly dissolved in the circulating coolant. These designs have shown that circulating gas bubbles can play an important role in the management of fission products and the operational behavior of the reactor. A drift flux model was implemented to more accurately capture the localized behavior of the void in the core and its impact on the mass transfer of fission products. A thorough assessment of the new model was performed by developing a verification and validation test suite. Verification problems were designed to test all major terms in the new governing equations. The new model converged to the correct solution at the expected order of accuracy for all verification cases. The validation cases included a wide range of flow and void conditions in different pipe geometries. Although higher void experiments show a slight underprediction of void by the drift flux model, experiments that aim to reproduce Molten Salt Reactor Experiment (MSRE) experimental conditions show good agreement with the model. The gas transport model was activated for a SAM model of the MSRE to demonstrate that it can be used in a more complex model. This gas transport model will be used along with an interfacial area transport equation being implemented in SAM for the prediction of mass transport behavior in MSR conditions.

Atmospheric Turbulence Phase Reconstruction via Deep Learning Wavefront Sensing.

The fast and accurate reconstruction of the turbulence phase is crucial for compensating atmospheric disturbances in free-space coherent optical communication. Traditional methods suffer from slow convergence and inadequate phase reconstruction accuracy. This paper introduces a deep learning-based approach for atmospheric turbulence phase reconstruction, utilizing light intensity images affected by turbulence as the basis for feature extraction. The method employs extensive light intensity-phase samples across varying turbulence intensities for training, enabling phase reconstruction from light intensity images. The trained U-Net model reconstructs phases for strong, medium, and weak turbulence with an average processing time of 0.14 s. Simulation outcomes indicate an average loss function value of 0.00027 post-convergence, with a mean squared error of 0.0003 for individual turbulence reconstructions. Experimental validation yields a mean square error of 0.0007 for single turbulence reconstruction. The proposed method demonstrates rapid convergence, robust performance, and strong generalization, offering a novel solution for atmospheric disturbance correction in free-space coherent optical communication.