Regularization Principle Research Articles

Dream housing: Exploring effective factors on housing livability in the neighborhood from the perspective of residents

The purpose of this study is to develop a new concept of livability as "livable housing" in order to identify the factors that determine the subjective satisfaction of residents with the internal and surrounding environment of the housing and to estimate its level among urban neighborhoods with subjective and objective data. In order to fill the knowledge gap in livability studies, especially housing livability, the present study has looked at the link between livability and housing indicators and has evaluated this link among the residents of urban neighborhoods with different socio-economic contexts. This study has been evaluated the indicators of livable housing in an empirical analysis among the neighborhoods of Karaj metropolitan area (as a leading city) with the cluster sampling method and choosing 8 neighborhoods (as the scope of the research) as well as 402 cases (as a sample statistics derived from Cochran's formula).In this evaluation, the questionnaire with (72 sub-indicators in 15 groups) is the main criterion for data collection, and the analyzes are using statistical and spatial combined methods. The statistical analysis of the questionnaire includes preparing the data for weighting and determining the important and influential factors with the exploratory factor analysis method in the SPSS environment. The stratification of neighborhoods is done with the multi-criteria decision-making model (TODIM) by combining the raw data and the weight of indicators extracted from the EFA method. Also, the accuracy of the results has been measured with the RMS method and the use of spatial methods in (GIS).The results showed environmental, social, economic and physical macro-factors respectively have the greatest effects on the livability of housing. The indicators of facilities and infrastructures, open and public space, cleanliness and pollution were the indicators of increasing livability and satisfaction, and the indicators of place connection and belonging, access and transportation, personal and social security were the indicators of decreasing livability. In general, the neighborhoods are in different conditions of housing livability and without continuity and principles of regularity. This difference in the different effects of indicators in neighborhoods is due to the inherent differences of neighborhoods and people's mental filters. The (89%) overlap obtained from the validation of the results indicates the existence of a very insignificant difference and acceptable agreement of the results of the two methods of spatial-spatial analysis. Considering the importance of the relationship between man and the urban environment and the quality of human life, it is recommended to pay special attention to community-orientedness and local assets and a bottom-up approach in livability surveys at any scale. Also, this study suggests important policy implications for achieving urban sustainability by improving housing livability.

Geological analysis of the hydro-mechanical responses of Opalinus claystone to excavation-induced damage via engineering

In the realm of engineering geology, specifically concerning the containment of high-level radioactive waste, this study examines the excavation-induced damage zone (EDZ) in underground drifts and its evolution, which is critical for the effectiveness of underground repositories. The focus is on the self-sealing capability of the EDZ in Opalinus claystone (OPA) under mechanical compression and hydration induced by a bentonite core sealing component post-nuclear waste emplacement. This core applies a swelling pressure of 5 MPa to the drift walls during resaturation, affecting repository integrity. Using numerical modeling, this study pioneers the simulation of real-time self-sealing mechanisms in OPA, a crucial geological barrier in nuclear waste containment. The approach integrates a plastic damage model with an auxiliary deformation model and Biot’s model to accurately depict moisture-dependent OPA deformation. This modeling is essential for understanding claystone geomechanics in nuclear waste repositories. Detailed post-analysis of crack features and unsaturated fractured OPA permeability, following fracture energy regularization principles and the cubic law, provides insights into the geotechnical properties of the EDZ, enhancing the accuracy of geological forecasts in nuclear waste management. The model’s reliability is confirmed through various numerical simulations, including triaxial compression tests, observations of swelling deformations due to moisture variations, and comprehensive water permeability tests assessing the self-sealing efficiency of fractured OPA during water injection. In situ experiments at the Mont Terri Rock Laboratory support these findings, particularly regarding EDZ self-sealing under combined mechanical and hydration conditions. Comparative analysis of numerical results and experimental data validates the model’s ability to replicate fractured OPA self-sealing behavior, crucial for assessing nuclear waste repository safety and effectiveness. Effective self-sealing is underscored by reduced water permeability in the EDZ during resaturation, affirming the model’s relevance in evaluating nuclear waste containment strategies. Moreover, insights from this model extend to assessing CO2 migration, given claystones’ role as caprocks in CO2 geological sequestration schemes, thereby enhancing its importance in long-term environmental safety evaluations for both nuclear waste and CO2 storage scenarios.

Can a dialetheist stay regular?

For a dialetheist, it is rational to believe that true contradictions exist. However, we argue that a dialetheist faces a complex dilemma given some bridge principles for rational beliefs that connect possibility and probability, including the so-called ‘Regularity Principle’. Either her belief is not doxastically possible even for her, or she must assign positive credence to the proposition that dialetheia exists. The former makes her belief prima facie self-defeating. The latter seems to compel her to choose between several more fine-grained options, each of which seems undesirable for a regular and rational probability theory. It is unclear how a dialetheist would stay rationally regular, so we pose this challenge, seeking a response from a dialetheist.

Study on Ill-Conditioned Total Least Squares Load Identification Method Based on the IGG Weight Function

To address the ill-conditioned problem and unknown noise interference in ship load identification, this study proposes the ill-conditioned Total Least Squares (TLS) load identification method using the anti-error principle of the IGG weight function (IGG-TLS). First, the weight factor is iteratively updated through the IGG weight function. The weight matrix is constructed adaptively by multiplying the weight factor with the initial unit weight matrix. Then, the regularization criterion for the ill-conditioned IGG-TLS model is established based on the Tikhonov regularization principle. And the Lagrange multiplier is employed to solve the IGG-TLS method. Finally, the load identification accuracies of the IGG-TLS method are investigated through the simulation analysis and experimental verification of the rectangular plate under different noise and SNR conditions. The results demonstrate that the IGG-TLS method can achieve high accuracy in load identification without the need to pre-construct the weight matrix, even when the SNR is unknown. Additionally, the IGG-TLS method can effectively correct the identification errors in the TLS method, demonstrating high accuracy and noise immunity under conditions of equal-weight and unequal-weight noise.

Barely Supervised Learning for Graph-Based Fraud Detection

In recent years, graph-based fraud detection methods have garnered increasing attention for their superior ability to tackle the issue of camouflage in fraudulent scenarios. However, these methods often rely on a substantial proportion of samples as the training set, disregarding the reality of scarce annotated samples in real-life scenarios. As a theoretical framework within semi-supervised learning, the principle of consistency regularization posits that unlabeled samples should be classified into the same category as their own perturbations. Inspired by this principle, this study incorporates unlabeled samples as an auxiliary during model training, designing a novel barely supervised learning method to address the challenge of limited annotated samples in fraud detection. Specifically, to tackle the issue of camouflage in fraudulent scenarios, we employ disentangled representation learning based on edge information for a small subset of annotated nodes. This approach partitions node features into three distinct components representing different connected edges, providing a foundation for the subsequent augmentation of unlabeled samples. For the unlabeled nodes used in auxiliary training, we apply both strong and weak augmentation and design regularization losses to enhance the detection performance of the model in the context of extremely limited labeled samples. Across five publicly available datasets, the proposed model showcases its superior detection capability over baseline models.

On the nonstandard maximum principle and its application for construction of monotone finite-difference schemes for multidimensional quasilinear parabolic equations

UDC 517.9 We consider the difference maximum principle with input data of variable sign and its application to the investigation of the monotonicity and convergence of finite-difference schemes (FDSs). Namely, we consider the Dirichlet initial-boundary value problem for multidimensional quasilinear parabolic equation with an unbounded nonlinearity. Unconditionally monotone linearized finite-difference schemes of the second-order of accuracy are constructed on uniform grids. A two-sided estimate for the grid solution, which is completely consistent with similar estimates for the exact solution, is obtained. These estimates are used to prove the convergence of FDSs in the grid L 2 -norm. We also present a study aimed at constructing second-order monotone difference schemes for the parabolic convection-diffusion equation with boundary conditions of the third kind and unlimited nonlinearity without using the initial differential equation on the domain boundaries. The goal is a combination of the assumption of existence and uniqueness of a smooth solution and the regularization principle. In this case, the boundary conditions are directly approximated on a two-point stencil of the second order.

Assessment of the double-parameter iterative Tikhonov regularization for single-epoch measurement model-based precise GNSS positioning

The double-parameter iterative Tikhonov regularization is assessed for strengthening the single-epoch model-based precise GNSS positioning within the framework of cognitive meanings. The simultaneous iterative Tikhonov regularization of the least-squares (LS) estimators of the parameters of interest in the single-epoch GNSS model is analyzed to enhance their accuracy properties. Regularization parameters (RP) are collected in the regularization operator, which can play a standardizing role in the regularization principle. Thus, the double-parameter approach can consider the heteroscedasticity of the LS estimators of interest in the regularization principle. This approach employs the quality-based mean squared error (mse) matrix trace minimization criterion to select optimal double-RP values simultaneously. Then, the unconstrained LS estimation is iteratively regularized, obtaining regularized float solutions. The numerical tests indicate that the double-parameter approach successfully strengthens the single-epoch GNSS measurement models due to considering the heteroscedasticity of the LS estimators of interest in the regularization principle. The regularized variance–covariance (vc) matrix describes float solutions of improved precision properties at the cost of losing the LS estimator’s unbiasedness. The accuracy is thus superior in the sense of mse. Therefore, the regularized LS estimator is well-scaled but with a biased localization. It also provides a more peaked probability density function (PDF) of real-valued ambiguities, obtaining a lower failure rate (FR) of integer least-squares (ILS) ambiguity resolution (AR). In this way, the regularized ILS estimator performs well in the ambiguity domain with the presence of regularized bias.

Adaptation of athletes to execution of specific sports loads

The article provides a theoretical understanding of the nature of multi-level adaptation of subjects of sports activities to specific physical and psychological loads in the field of sports of the highest achievements. In particular, the outstanding features and characteristics of sports activity as a special type of human activity were revealed, a detailed analysis of the specific features of sports of the highest achievements as the area of the occurrence of extreme loads for a person was implemented, the phenomenon of adaptation in sports and the factors affecting it were operationalized, the main characteristics of specific loads in sports activities.
 Sport was considered as a specific human activity that has the structure of game activity, in particular, is subject to artificially created rules and contains an element of competition, which is based on the assessment and comparison of the physical and intellectual abilities of its subjects. The characteristics and factors of sports activity that provoke the emergence of extreme loads on the physical and mental apparatus of athletes and require the intensification of adaptation processes, in particular, high requirements for sports achievements, its publicity, social significance, a limited number of attempts to demonstrate the result, a constant change in the conditions of its implementation, are determined and their objective severity, the need to make operational decisions. Attention is focused on the fact that the key specificity of loads in sports of the highest achievements is their extremely high duration and intensity.
 It is proposed to distinguish such gradations of professional functioning of athletes as physical, psycho-emotional and cognitive levels, which made it possible to eliminate excessive focus only on their physical adaptation to sports activities. It has been proven that the proper level of adaptation of a sportsman is the basis of his high professional qualification and self- realization. The result of the theoretical review was the formation of a list of the most effective methods and techniques for ensuring the adaptation of athletes at various levels of their professional functioning. Among the methods and techniques for ensuring the proper level of adaptation of athletes, regular physical exercises are highlighted, the use of which is based on the principles of weight gain, consistency, regularity and cyclicity; psychotechniques for increasing the level of self-regulation and general stress resistance; ideomotor training as a means of ideal modeling of sports actions.

Beyond Numbers: An Ambiguity–Accessibility–Applicability Framework to Explain the Attraction Effect

Abstract The attraction effect (AE) occurs when the addition of an inferior alternative (i.e., a decoy) to a choice set increases the choice share of the alternative to which it is most similar (i.e., a target), a phenomenon that violates the regularity principle. The AE occurs reliably when the attribute values are represented numerically, but not when the stimuli are perceptual. Such conceptual replication failures indicate a lack of clarity about the mechanisms that produce the AE. The present research develops a framework—the 3A framework—that specifies the distinct functions of ambiguity, accessibility, and applicability in the choice process. These factors, and their attendant mechanisms, explain when and why the AE emerges. They also specify conditions under which the AE is attenuated. Seven main experiments and four supplementary experiments examine when and why the AE emerges with perceptual stimuli, provide support for the 3A framework, and offer insights about how to produce the AE in choice contexts involving perceptual stimuli.

Symmetry-based regularization in deep breast cancer screening.

Breast cancer is the most common and lethal form of cancer in women. Recent efforts have focused on developing accurate neural network-based computer-aided diagnosis systems for screening to help anticipate this disease. The ultimate goal is to reduce mortality and improve quality of life after treatment. Due to the difficulty in collecting and annotating data in this domain, data scarcity is - and will continue to be - a limiting factor. In this work, we present a unified view of different regularization methods that incorporate domain-known symmetries in the model. Three general strategies were followed: (i) data augmentation, (ii) invariance promotion in the loss function, and (iii) the use of equivariant architectures. Each of these strategies encodes different priors on the functions learned by the model and can be readily introduced in most settings. Empirically we show that the proposed symmetry-based regularization procedures improve generalization to unseen examples. This advantage is verified in different scenarios, datasets and model architectures. We hope that both the principle of symmetry-based regularization and the concrete methods presented can guide development towards more data-efficient methods for breast cancer screening as well as other medical imaging domains.

Smoothing of the Time-Resolved Spectral Matrix Obtained by a Streak Camera: Estimation of the Fluorescence Band Parameters

A new method based on singular value decomposition (SVD) was applied to the denoising of the time-resolved spectral matrix (TRSM), which was obtained by a streak camera. The least informative principal components (PCs) were filtered out using the Tikhonov regularization principle. A method for determining the quasi-optimal regularization parameter was suggested. The SVD method was compared with the moving average time direction (MATD) smoothing of the TRSM. Numerical simulations and experimental study of the 3-aminophthalimide (3AP) solution in acetonitrile showed that the SVD smoothing allowed for accurate measurement of signals in peak maximum. Fitting the polynomial modified Gaussian to the smoothed fluorescent bands decreased the measurement errors of the maximum peak position and its width. This method allowed us to obtain kinetics data of the fluorescence band parameters of the 3AP spectrum in an acetonitrile solution. Flexible selection of the quasi-optimal processing parameters and a better time resolution are the main advantages of the SVD method over MATD.

Gas Turbine Model Identification Based on Online Sequential Regularization Extreme Learning Machine with a Forgetting Factor

Due to the advantages of high convergence accuracy, fast training speed, and good generalization performance, the extreme learning machine is widely used in model identification. However, a gas turbine is a complex nonlinear system, and its sampling data are often time-sensitive and have measurement noise. This article proposes an online sequential regularization extreme learning machine algorithm based on the forgetting factor (FOS_RELM) to improve gas turbine identification performance. The proposed FOS_RELM not only retains the advantages of the extreme learning machine algorithm but also enhances the learning effect by rapidly discarding obsolete data during the learning process and improves the anti-interference performance by using the regularization principle. A detailed performance comparison of the FOS_RELM with the extreme learning machine algorithm and regularized extreme learning machine algorithm is carried out in the model identification of a gas turbine. The results show that the FOS_RELM has higher accuracy and better robustness than the extreme learning machine algorithm and regularized extreme learning machine algorithm. All in all, the proposed algorithm provides a candidate technique for modeling actual gas turbine units.

Kyra Markham: Letters to Louis Sheaffer (1962–63)

Kyra Markham: Letters to Louis Sheaffer (1962–63)

Signal reconstruction from noisy multichannel samples

We consider the signal reconstruction problem under the case of the signals sampled in the multichannel way and with the presence of noise. Observing that if the samples are inexact, the rigorous enforcement of multichannel interpolation is inappropriate. Thus the reasonable smoothing and regularization corrections are indispensable. In this paper, we propose several alternative methods for signal reconstruction from noisy multichannel samples under different smoothing and regularization principles. We compare these signal reconstruction methods theoretically and experimentally in various situations. To demonstrate the effectiveness of the proposed methods, the probability interpretation and the error analysis for these methods are provided. Additionally, the numerical simulations as well as some guidelines to use the methods are also presented.

Implementation of Self-education Principles as a Background of Quality Professional Education

Education is an important component of the life of every society member. Studying in educational institutions alone is not, however, enough in order to be successful. This is the reason why self-education has become widespread. The aim of this work was to study the implementation of the self-education principles in specialized education, focusing on the principles of regularity, consistency, the relationship between selfeducation with education and self-education with professional activities. This aim was achieved through a pedagogical experiment conducted in general secondary and higher educational institutions, as well as through surveys of pupils, students, nursery school teachers, school teachers and lecturers/professors. Statistical data on the dynamics of the teaching staff of educational institutions were analysed through mathematical methods. The experiment found that the introduction of methods that contribute to the development of self-educational competence, self-control and self-organization in educational institutions also has a positive effect on the academic performance of pupils and students. These methods improve cognitive activity and increase motivation of educational activities, social interaction and purposefulness, point out gaps in acquired knowledge and help to implement a differential approach. The study demonstrated that self-education should be consistent and regular, starting with general secondary education and accompanying specialists throughout their professional carriers. finding effective teaching methods that can be used in educational institutions at different levels and that contribute to the development of skills and abilities to independently improve acquired knowledge may be the subject of further research.

Zeroing Neural Network Approaches Based on Direct and Indirect Methods for Solving the Yang–Baxter-like Matrix Equation

This research introduces three novel zeroing neural network (ZNN) models for addressing the time-varying Yang–Baxter-like matrix equation (TV-YBLME) with arbitrary (regular or singular) real time-varying (TV) input matrices in continuous time. One ZNN dynamic utilizes error matrices directly arising from the equation involved in the TV-YBLME. Moreover, two ZNN models are proposed using basic properties of the YBLME, such as the splitting of the YBLME and sufficient conditions for a matrix to solve the YBLME. The Tikhonov regularization principle enables addressing the TV-YBLME with an arbitrary input real TV matrix. Numerical experiments, including nonsingular and singular TV input matrices, show that the suggested models deal effectively with the TV-YBLME.

New Framework for Evaluating Ecosystem Quality in Nature Reserves based on Ideal References and Key Indicators

With increasing numbers and types of nature reserves (NRs), objective evaluation and comparison of the effects of different nature NRs on conservation efforts are of great importance for protecting species diversity, ensuring reasonable national economic input, and adjusting government management schemes. Developing a method for the combined assessment of flagship or umbrella species and ecosystem quality will improve the evaluation of NRs. However, it is also important to establish a new framework for rapid evaluation of ecosystem quality, supported by the advantages of scientific, economic, and regular principles. Here, we proposed a new framework that incorporates the novel concept of ideal references into evaluation systems, which will facilitate the comparison of results from different periods and regions. Furthermore, from the perspective of making the framework as objective, rapid, and economical as possible, we recommended some key ecological indicators, such as net primary productivity, soil organic matter, plant diversity, for use in the new evaluation framework. The new framework, referred to as “ideal reference and key indicators” (IRKI), can sufficiently meet the requirements for the rapid evaluation of ecosystem quality both regionally and nationally. Furthermore, IRKI can identify the restoration potential and restoration periods of NRs, thus facilitating the rational distribution of resources and enhancing the protective effect. There are many types of NRs in China, and it is necessary to partially alter the assessment methods or parameters for different types of NRs. Overall, IRKI provides a simple, clear, and comparable framework that will strongly enhance the conservation of protected areas (PAs) and facilitate the standardization of management practices.

Atomicity and Regularity Principles Do Not Ensure Full Resistance of ECC Designs against Single-Trace Attacks.

Elliptic curve cryptography (ECC) is one of the commonly used standard methods for encrypting and signing messages which is especially applicable to resource-constrained devices such as sensor nodes that are networked in the Internet of Things. The same holds true for wearable sensors. In these fields of application, confidentiality and data integrity are of utmost importance as human lives depend on them. In this paper, we discuss the resistance of our fast dual-field ECDSA accelerator against side-channel analysis attacks. We present our implementation of a design supporting four different NIST elliptic curves to allow the reader to understand the discussion of the resistance aspects. For two different target platforms—ASIC and FPGA—we show that the application of atomic patterns, which is considered to ensure resistance against simple side-channel analysis attacks in the literature, is not sufficient to prevent either simple SCA or horizontal address-bit DPA attacks. We also evaluated an approach which is based on the activity of the field multiplier to increase the inherent resistance of the design against attacks performed.

ЭТАПЫ РАЗРАБОТКИ И АРХИТЕКТУРНО-ГРАДОСТРОИТЕЛЬНАЯ ЗНАЧИМОСТЬ ПЕРВОГО ГЕНЕРАЛЬНОГО ПЛАНА АСТРАХАНИ (1767–1769 ГГ.)

The history of a large-scale program of urban reconstruction and construction on model projects in the second half of the 18th century has been sufficiently studied in the fundamental works of Soviet researchers. However, the local context of regulating the planning structure of border towns continues to be actual topic due to new discoveries and the rapid degradation of the historical and architectural environment. This article summarizes and refines information about the creation of the first Highly approved general plan of Astrakhan in 1760s based on a comprehensive analysis of written and iconographic sources. Stages of development and authors of design solutions are identified. New archival materials and their description are introduced into scientific circulation. The share of participation and contribution of the architect Andrey Menshov, the Astrakhan governor Beketov N.A. and Kvasov A.V. – the chief architect of the “Commission for the Stone Construction in Saint Petersburg and Moscow” is specified. The analysis of the process of designing the general plan in urban planning and architectural aspects with indicating of recommendations and regulations for construction of residential buildings based on principles of regularity and ensemble is presented.

ПРИНЦИПИ ФОРМУВАННЯ ЕКОЛОГІЧНОЇ КОМПЕТЕНТНОСТІ МАЙБУТНІХ УЧИТЕЛІВ БІОЛОГІЇ У ПРОЦЕСІ ФАХОВОЇ ПІДГОТОВКИ

The research results of the problem of definition of the principles of the ecological competence formation of the future biology teachers during the professional training have been defined in the article. It has been specified, that the conception of the ecological competence formation of the future biology teachers is based on general pedagogical and specific principles that are normative guidelines, basic foundations for organization and performing the professional training of students. We have highlighted the fact, that the effectiveness of the implementation of the system of the students' ecological competence is achieved due to clear compliance with the chosen principles and approaches to the process of the future teachers' training. In this article the principles of the ecological competence formation of the future biology teachers are considered as the most common starting points that define the strategic ways and tactic for the professional training of higher-education students of the qualification mentioned above in order to form the studied quality of personality. The author has defined general pedagogical (principles of science, regularity and sequence, unity of consciousness, activity and self-discipline, connection of studying with practical activity and life's realities) and specific principles of ecological competence formation (principles of interdisciplinary integration, the creation of the ecologically friendly educational environment, professional orientation, variability, the relationship of local, emotional values of perception of the natural environment in practice, regional and global approaches in the educational process). It has been pointed out, that the specific principles of the ecological competence formation of the future biology teachers have been defined by the author based on the synergetic connection of the principles of the professional education, competence approach, the principles of ecological education and upbringing, which have points of intersection for individual positions. We have highlighted the fact, that these principles are used during the professional training of the future biology teachers as interconnected and complementary elements of a single pedagogical system.