Erroneous Solutions Research Articles

Two-Step AE Source location for Detecting Tendon Rupture inside PC Box-Girder in-Service

In order to identify tendon rupture inside a prestressed concrete (PC) girder, new acoustic emission (AE) location system is necessary to be practically applied. In PC girder of an in-service highway, PZT sensors are installed at a web and a deck of the PC girder, and elastic waves generated by tendon rupture is simulated by steel ball impact. AE source location assuming the homogeneous velocity distribution is applied in a development view of the box-girder. Then to verify the accuracy of the location results, the effect of elastic-wave propagation at a joined corner between the web and the deck is simulated by FDM. As a result, the attenuation of first-arrival P waves was observed at the joined corner. It implies that wave energy is so attenuated that apparent velocity decreases. Finally, AE locations lead to erroneous solutions in the development view solved with a constant velocity. To solve the problem, a twostep location system is developed. In the first step, two-dimensional plane, where the tendon rupture is to be identified, is selected from the 1st and 2nd arrivals of AE Hits. Then, in the 2nd step, AE locations are determined from remaining AE sensors located on this plane. By applying this system, the location errors are within 5 % at the both web and deck in a 15 m long PC box-girder.

How to Make Computer-Based Feedback More Productive: The Power of Erroneous Solutions

This research aims to expand our understanding of how to facilitate student feedback engagement processes in a computer-based formative assessment environment. In the present research, we designed a new type of elaborated feedback in terms of combining the correct solution and the erroneous solution, and the erroneous solution matched the student’s initial answer. Furthermore, we analyzed whether this feedback had a stronger positive effect than the other three types of feedback containing different complexities of correct information (i.e., Knowledge of Correct Response, Problem-Solving Cues, or Complete Correct Solutions). As predicted, students who received correct and erroneous solutions experienced more positive feedback perceptions, perceived lower extraneous cognitive load and higher germane cognitive load, and achieved higher transfer performance. This research is one of the first that provides empirical evidence for the positive impact of incorporating students’ errors into the feedback design, and this novel insight can extend current theories on how to optimize feedback design to promote students’ active processing and use of feedback.

German-to-Basque Translation Analysis of Multiword Expressions in a Learner Translation Corpus

This paper presents the results of the annotation in a learner translation corpus consisting of German source texts and student translations into Basque. The analysis was carried out with the purpose of identifying trainee translators’ strengths and weaknesses when translating multiword expressions, such as compounds, collocations, and idioms. The data comprised eight German source texts and sixty-eight Basque translations from undergraduate students enrolled at the University of the Basque Country. From the total number of annotations (1214), which include not only errors but also cases of interference from the source language and positive outcomes, around 27 % are related to multiword expressions. The results of the translation analysis show that there are variables — such as the use of machine translation systems, the level of specialisation of the source text, the type of multiword expression to be translated or the absence of a literal counterpart in the target language — that may affect the translation of such units and lead to erroneous solutions and/or interference in the outputs produced by the trainee translators. From a pedagogical point of view, these findings will have a direct impact on the translation classes and will be very valuable for designing corpus-based in-class activities

On the Spatiotemporal Pattern Formation in Nonlinear Coupled Reaction–Diffusion Systems

Nonlinear coupled reaction–diffusion (NCRD) systems have played a crucial role in the emergence of spatiotemporal patterns across various scientific and engineering domains. The NCRD systems considered in this study encompass various models, such as linear, Gray–Scott, Brusselator, isothermal chemical, and Schnakenberg, with the aim of capturing the spatiotemporal patterns they generate. These models cover a diverse range of intricate spatiotemporal patterns found in nature, including spots, spot replication, stripes, hexagons, and more. A mixed-type modal discontinuous Galerkin approach is employed for solving one- and two-dimensional NCRD systems. This approach introduces a mathematical formulation to handle the occurrence of second-order derivatives in diffusion terms. For spatial discretization, hierarchical modal basis functions premised on orthogonal scaled Legendre polynomials are used. Moreover, a novel reaction term treatment is proposed for the NCRD systems, demonstrating an intrinsic feature of the new DG scheme and preventing erroneous solutions due to extremely nonlinear reaction terms. The proposed approach reduces the NCRD systems into a framework of ordinary differential equations in time, which are addressed by an explicit third-order TVD Runge–Kutta algorithm. The spatiotemporal patterns generated with the present approach are comparable to those found in the literature. This approach can readily be expanded to handle large multi-dimensional problems that appear as model equations in developed biological and chemical applications.

Quantum Regularized Least Squares

Linear regression is a widely used technique to fit linear models and finds widespread applications across different areas such as machine learning and statistics. In most real-world scenarios, however, linear regression problems are often ill-posed or the underlying model suffers from overfitting, leading to erroneous or trivial solutions. This is often dealt with by adding extra constraints, known as regularization. In this paper, we use the frameworks of block-encoding and quantum singular value transformation (QSVT) to design the first quantum algorithms for quantum least squares with general ℓ2-regularization. These include regularized versions of quantum ordinary least squares, quantum weighted least squares, and quantum generalized least squares. Our quantum algorithms substantially improve upon prior results on quantum ridge regression (polynomial improvement in the condition number and an exponential improvement in accuracy), which is a particular case of our result.To this end, we assume approximate block-encodings of the underlying matrices as input and use robust QSVT algorithms for various linear algebra operations. In particular, we develop a variable-time quantum algorithm for matrix inversion using QSVT, where we use quantum eigenvalue discrimination as a subroutine instead of gapped phase estimation. This ensures that substantially fewer ancilla qubits are required for this procedure than prior results. Owing to the generality of the block-encoding framework, our algorithms are applicable to a variety of input models and can also be seen as improved and generalized versions of prior results on standard (non-regularized) quantum least squares algorithms.

ПОРІВНЯННЯ АЛГОРИТМІВ КЛАСИФІКАЦІЇ BIG DATA МЕТОДАМИ ІМІТАЦІЙНОГО МОДЕЛЮВАННЯ

With the development of information transmission and storage technologies, the volumes of data that require processing and analysis are growing rapidly. Therefore, the task of developing algorithms for solving various artificial intelligence problems for Big Data volumes is urgent. In our works, this informal term "Big Data" refers to situations when known processing algorithms do not allow solving a problem in a practically acceptable time. With regard to classification tasks, such conditions are possible when the first place is not even high reliability (that is, the minimum number of errors), but productivity (classification speed). The well-known method of nearest neighbors is one of the most productive. However, the indicator of the order of growth (the number of typical operations) for it is K x M x N, where K is the number of nearest neighbors, M is the number of classes, N is the typical number of class elements. Along with this, we propose to consider algorithms based on the principles of M-means, where classes are replaced by only a small number of their characteristics. Among such algorithms, the article considers: the algorithm of class centers and the algorithm of adaptive rules. The order of growth for these algorithms is only M according to the number of classes. The comparative analysis of these algorithms is performed by the method of simulation modeling. Simulation models are implemented by the Adaptive Metrics program, developed at the Department of Software Engineering at DUITZ. In this program, the classification problem is solved using the example of the dichotomy problem for classes A and B. The program has the possibility of very flexible setting of models. Problems can be solved in 1-dimensional, 2-dimensional,..., 6-dimensional spaces. The distribution of factor values for classes A and B can have quite different statistical characteristics - from uniform and triangular distribution functions to functions approaching a normal distribution. The graphical interface of the program allows you to dynamically observe the solution of the classification problem in one-dimensional, two-dimensional and 6-dimensional projections. As a result of multiple runs of the program, it was established that the algorithms of the nearest neighbors slightly outperform the algorithms of class centers and adaptive rules according to the criterion of reliability, and also comply with the principle of compactness (concentration of the largest number of erroneous solutions in the hypercube of errors). Algorithms based on M-means principles significantly outperform this algorithm in terms of performance. Also, the algorithm of adaptive rules best corresponds to the principle of equality of classes and is the most productive of the considered ones.

Mathematical Model and Solution Algorithm for Virtual Localization Problem

Introduction. The optimization placement problem refereed to virtual localization is studied. This problem is motivated by the need to optimize the production of parts from near-net shape blanks using CNC machines. The known algorithms for solving the virtual localization problem come down to determining the location parameters of the part CAD model inside the point cloud obtained by scanning the workpiece surface. The main disadvantage of such algorithms is the use of criteria that are insensitive to the intersection of the surfaces of the part and the workpiece. In order to prevent such errors in production conditions, it is necessary to involve a human operator in conducting operations based on virtual localization. In this way, the virtual localization problem of complex shape objects is of paramount importance. The purpose of the paper is to propose a new approach for solving the virtual localization problem. Results. A new mathematical model of the virtual localization problem based on the phi-function technique is proposed. We developed a solution strategy that combines algorithm of generating feasible starting points with non-linear optimization procedure. The testing of the proposed approach was carried out for a two-dimensional case. The computational results illustrated with graphical illustrations are provided that show the efficiency of the proposed algorithm. Conclusions. The obtained results show that the use of the phi-functions technique prevents the occurrence of erroneous solutions with the intersection of the workpiece surfaces. An algorithm for solving the problem of virtual localization in a two-dimensional formulation for the case when the part and the workpiece are convex polygons has been developed. For the considered test problems, the solution time did not exceed 2.5 sec, which fully meets the requirements of industrial use. In the future, it is planned to extend the proposed method to the cases when the CAD model of the part has an arbitrary shape and is formed by Boolean operations on geometric primitives. Keywords: polygonal domain, phi-function technique, virtual localization, CNC machining.

Expanding the memory effect in scattering imaging by manipulating photon distributions

Speckle correlation techniques based on the memory effect can recover objects from multiple scattered light without the information of the scattering media. The existing methods, however, are limited by the inherent angular width of the memory effect, and the retrieval algorithms frequently converge to erroneous solutions. In this paper, we propose an autoshrinking algorithm to expand the field of view in scattering imaging. We also develop a pretreatment iteration scheme to achieve high accuracy reconstruction. The autoshrinking method improves the quality of the energy spectrum by adaptively shrinking the speckle autocorrelation to its expanded central peak region and enhancing the ratio of the ballistic photons to the scattered photons. In the pretreatment iteration, the Brenner gradient function of a short testing iteration is employed to select the initial random Fourier phase to ensure the iteration can quickly and accurately converge. Experiments and simulations successfully confirm the effectiveness of our method.

10 Years of Application of the Polish Act on Private International Law of 2011

The article presents the Polish courts’ application of the national Private International Law Act 2011 (PIL 2011) during the 10 years it has been in force. The analysis of jurisprudence is supplemented with observations on recent developments in Polish doctrine. The authors discuss correct and erroneous solutions adopted by courts, which are illustrated by provided examples of judgments regarding diverse legal issues. The article deals with mistakes consisting in ignoring the need to search for the applicable law. It also concerns, on the one hand, faulty perceptions and applications of newly introduced instruments (such as the so-called informative provisions or new conflict rules concerning issues that have not been regulated before in the conflictof- laws sphere) or of instruments shaped differently than in the past (such as renvoi). On the other hand, it considers problems that emerged in relation to mechanisms that are well known to Polish judges (such as the public policy exception). Challenges relating to delimiting PIL 2011 from other sources of PIL are also discussed.

Control of mathematical modeling process of dynamics of harmful substances concentrations on the basis of ontological approach

The problem of building a mathematical model of the dynamics of nitrogen dioxide concentrations at different parts of the city is considered in the paper. The peculiarities of the construction of such models on the basis of periodic measurement of concentrations of harmful substances and identification on the basis of the measurements obtained are considered. This paper also proposes an ontological approach as a control tool that greatly simplifies the systematic standardized methods of the models storage, the process of their construction and appropriate usage in practice. The use of the ontological model allows formalizing the process of obtaining, storing and using relevant knowledge and is suitable for more intelligent systems, such as identification of obviously erroneous solutions based on the model, predictive control of the model, optimization of the decision-making process based on knowledge and modeling of an appropriate technological flow chart. This paper also describes the features of the construction of the corresponding ontological model, the pattern of choice of a nonlinear model with "switching" to different conditions. Relevant experimental studies have also been conducted to confirm the effectiveness of the proposed approach.

Mysterious Neutrosophic Linear Models

Operations research often shortened to the initialism O.R., is a discipline that deals with the development and application of advanced analytical methods to improve decision-making. It is sometimes considered to be a subfield of mathematical sciences. The term management science is occasionally used as a synonym. It has the ability to express the concepts of efficiency and scarcity in a well-defined mathematical model for a specific issue. It has the ability to use scientific methods to solve complex problems in managing large scale systems for factories, institutions, and companies, and enables them to make optimal scientific decisions for the functioning of Its work. Employing techniques from other mathematical sciences, such as modelling, statistics, and optimization, operations research arrives at optimal or near-optimal solutions to complex decision-making problems. Because of its emphasis on practical applications, operations research has overlapped with many other disciplines, notably industrial engineering. Operations research is often concerned with determining the extreme values of some real-world objective: the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost). Originating in military efforts before World War II, its techniques have grown to concern problems in a variety of industries. The mathematical model is the simplified image of expressing a practical system from a real life problem or an idea put forward for an executable system, as the mathematical models consist of a goal function through which we search for the maximum or minimum value subject to restrictions. Linear mathematical programming is one of the most important topics in the field of operations research due to their frequent use in most areas of life. When studying linear programming, the first step is to identify the various types of linear models and how to transition from one to the next. We realize that the ideal solution of the linear model is influenced by the coefficients of the variables of objective function that describes a profit if the model is a maximizing model or represents a cost if the model is a minimization model, which is affected by environmental conditions. The fixed values that represent the right side of the inequalities (constraints), which express the available capital, time, raw resources, and so on, have an impact on the optimum solution. They are also affected by environmental conditions. We used to take these values as fixed values in classical logic, which does not correspond to reality and leads to erroneous solutions to the problems described by the linear model. As a result, it was essential to reformulate the classical linear models' problems, taking into consideration all probable scenarios and changes in the work environment. In this study, we will look into linear models and their kinds in view of neutrosophic logic, which takes into account all of the data and all of the changes that may occur in the issue under investigation, as well as the uncertainty that is encountered in the problem's data. We'll also look at it if the coefficients of the variables in the objective function are neutrosophic values, and the accessible options are neutrosophic values because we'll reformulate the existing linear mathematical models using neutrosophic logic, and show how to convert from one to another using some examples.

Swept volumes via spacetime numerical continuation

Given a solid 3D shape and a trajectory of it over time, we compute its swept volume - the union of all points contained within the shape at some moment in time. We consider the representation of the input and output as implicit functions, and lift the problem to 4D spacetime, where we show the problem gains a continuous structure which avoids expensive global searches. We exploit this structure via a continuation method which marches and reconstructs the zero level set of the swept volume, using the temporal dimension to avoid erroneous solutions. We show that, compared to other methods, our approach is not restricted to a limited class of shapes or trajectories, is extremely robust, and its asymptotic complexity is an order lower than standards used in the industry, enabling its use in applications such as modeling, constructive solid geometry, and path planning.

An Efficient Approach to Initialization of Visual-Inertial Navigation System using Closed-Form Solution for Autonomous Robots

The visual-inertial navigation system using a single camera and IMU requires an accurate initialization without increasing the processing cost and complexity for real-time deployment. The processing cost in the existing solutions can be traced to the gyroscopic bias estimation using 1) Closed-form solutions (Martinelli, Int. J. Comput. Vis. 106(2), 138–152, 2014; Kaiser et al., IEEE Robot. Autom. Lett. 2(1), 18–25, 2017 and 2) Loosely coupled schemes using visual-inertial alignment (Mur-Artal and Tardos IEEE Robot. Autom. Lett. 2(2), 796–803 2017); Qin, IEEE Trans. Robot. 34(4), 1004–1020 2018). The complexity arises because of the non-linear nature of the system to estimate the gyro bias, which is solved either by directly solving the non-linear, non-convex problem or by decoupling the vision and IMU measurements using linear models. The termination conditions are based on condition number or covariance of the estimated variables, which varies from one experiment to another. The present paper seeks to improve the closed-form solution with higher accuracy and less processing cost per frame. The proposed method separates the gyroscope bias estimation from the closed-form solution using tightly coupled but linear models with reduced number of variables in the closed-form solution. This paper also addresses the problem inherent to the closed-form solutions, which requires sufficient motion in the initialization window with a minimum number of common features. Towards this, a novel method of propagating the past information into the present initialization window is presented. This reduces the total processing cost per frame by limiting the initialization window to 10 frames ≈ 1s without compromising the motion inside the window. We also present a common and intuitive termination criteria which is independent from the experiment scenario. This helps to increase the robustness in the initialization by removing erroneous solutions. The proposed method is evaluated with EuRoC Micro Aerial Vehicle (MAV) dataset (Burri et al. 2016) sequences. We compare the proposed method with a recently proposed loosely coupled method, which shows the improved accuracy, processing cost and robustness in the initialization.

Pade-Approximation Based Behavioral Modeling for RF Power Amplifier Design

Radio frequency (RF) power amplifier (PA) design using Gallium Nitride (GaN) transistor technology requires accurate device models in order to maximise performance and reduce development time. The current state-of-the-art frequency-domain behavioural models focus on linear and quadratic approximations to the polyharmonic distortion (PHD) formalism. However, the linear approximation suffers from poor accuracy under load mismatch conditions, while the quadratic approximation suffers from poor extrapolation beyond the measured range, leading to erroneous predictions of the optimum load impedances for maximum output power and maximum drain efficiency. In this work, a rational Padé-based approximation is proposed as the model core, and it is shown, through experimental validation, that the Padé approximation-based model can provide superior results in a more scalable format. It can mitigate problems found in the existing PHD models when applied to the matching problem. Specifically, the proposed model produces fewer erroneous solutions for the optimum load points, due to the well-behaved nature of Padé approximants. In addition, for the first time, results are reported on using the behavioural model to determine the optimum impedance for maximum transducer gain in a two-port device model. All results show the Padé model has high potential when compared to the established PHD-derived models in RF PA design.

Coherent Ising Machines with Error Correction Feedback

AbstractA nonequilibrium open‐dissipative neural network, such as a coherent Ising machine based on mutually coupled optical parametric oscillators, has been proposed and demonstrated as a novel computing machine for hard combinatorial optimization problems. However, there is a challenge in the previously proposed approach: The machine can be trapped by local minima which increases exponentially with a problem size. This leads to erroneous solutions rather than correct answers. In this paper, it is shown that it is possible to overcome this problem partially by introducing error detection and correction feedback mechanism. The proposed machine achieves efficient sampling of degenerate ground states and low‐energy excited states via its inherent exploration property during a solution search process.

Learning from troubleshooting activities when contrasting erroneous examples with worked examples in the physics classroom

Research indicates that troubleshooting activities that require students to reflect on pre-prepared erroneous examples, i.e. erroneous solutions to problems that correspond to common naïve ideas, impact their learning positively. These include asking students to diagnose erroneous examples; in other words, detect the conceptual errors and then explain why these errors are wrong. One of the major challenges is to determine the best ways to support student learning with troubleshooting activities. One suggestion involves contrasting erroneous examples with worked examples through a step-by-step demonstration of how to solve a problem. Here, a new troubleshooting activity designed to prompt students to learn more effectively from erroneous examples is described and assessed. The worked examples only constitute one part of the rubric, and students are required to both diagnose erroneous examples and then score them. Six 8th grade classes from three schools (two classes each from a different school taught by the same teacher) completed a pre-test/intervention/post-test after finishing a unit in simple electric circuits. In the intervention, in each school, one class was randomly assigned to the new activity (45 students) and the other class to the traditional troubleshooting activity with worked examples without rubrics (46 students). The findings suggest that the new activity enabled more students to learn from the erroneous examples than the traditional activity, regardless of whether the students’ naïve ideas resembled the ones committed in the erroneous examples, and confirm the effectiveness of the new activity in 8th graders studying simple electric circuits. In a companion study by the first author (under review), the findings confirmed the effectiveness of the new activity in 10th graders studying geometric optics. Taken together, the findings of both studies may suggest that regardless of grade level or topic, the potential of learning from troubleshooting activities can be exploited effectively by implementing scoring erroneous examples along with a rubric portraying worked examples.

Students' Difficulties in Identifying the Use of Ternary Relationships in Data Modeling

The present study examines the difficulties novice data modelers face when asked to provide a data model addressing a given problem. In order to map these difficulties and their causes, two short data modeling problems were given to 82 students who had completed an introductory course in database modeling. Both problems involve three entity sets with relationships between them, either ternary or binary. The students' solutions were classified according to the types of errors they committed. More than half of the students provided faulty solutions. After an analysis of these results, open interviews were conducted with a selected group of students in order to figure out the reasons underlying the students' erroneous decisions regarding the data model. Among the reasons for their erroneous solutions were insufficient experience, lack of reflection on their solution, and lack of immediate feedback. In addition, the authors suggest instructional modifications derived from the research results.

Causes of erroneous expert diagnostic solutions to hearing loss from noise exposure

Covers the main expert diagnostic errors diagnostic and examination for hearing loss from exposure to noise, imperfection of normative and regulatory documentation, inadequate attention to the criteria the Association of the disease with the profession, lack of qualified health workers

ГОТУЄМОСЬ ДО МАТЕМАТИЧНИХ КОНКУРСІВ: ЗАДАЧНА СЕРІЯ НА МЕТРИЧНІ СПІВВІДНОШЕННЯ У ЧОТИРИКУТНИКУ

Solving of competitive problems by pupils and students is a good foundation and preparation for future practical and scientific activities, as mastering the methods of solving competitive problems requires them to work hard, actively and focused, as well as develops their creativity and raises level of interest in mathematics. The article reveals the mathematical aspects of preparing students to solve competitive problems on the example of one geometric problem (the ratio between the areas of triangles formed by the intersection of diagonals of a convex quadrilateral), which is the basis of many competitive problems in geometry; the problem is solved using the facts of elementary mathematics, available to students of the eighth form of secondary school; an analysis of the range of competitive problems of various mathematical competitions, for which the considered reference problem is a key subtask in the solution. An author's competitive problem for high school students has been created, which allows integrating a purely theoretical-numerical problem into the geometric shell with the study of simplicity of elements, divisibility of a product by a prime number, mutual simplicity of elements, with the need to find solutions of Diophantine equations in natural numbers. The article combines a problem series of a large number of different competitive geometric problems around one reference problem, presents the methodological aspects of preparing students to solve competitive problems on the example of this problem; attention is paid to checking the correctness of the obtained results, which avoids erroneous solutions; the tasks which urge to find and realize ways of their fulfillment are analyzed; examples of different tasks in terms of age capabilities of researchers are selected; the problems of competitions of regional levels with geometric and theoretical-numerical filling are considered; the competitive task on the given subject is created. Further research will be aimed at creating a broader series of tasks for the considered reference problem, including problems with integration into related competitive topics. The article emphasizes the problem content and structuring according to the age capabilities of students on the research topic.

Competencia textual y comunicativa en la traducción jurídica del inglés al checo: un estudio de caso

The study addresses communicative and textual competence using empirical data obtained in a translation experiment conducted with professional translators and advanced translation students. Specifically, it explores stylistic and grammatical errors in translations of legal texts from English into Czech, which account for more than a half of all errors identified in the analysed sample. The results show that terminology and legal phraseology are a frequent source of difficulty not only in terms of meaning, but also from the grammatical and stylistic point of view. Another large group of erroneous solutions was identified at the syntactic level, including defects of overall textual coherence. Professional translators achieved better results than translation trainees both in terms of the overall quality and average number of errors; however, as regards the numbers of stylistic and linguistic errors, the performance of both groups was more balanced than in other categories.