Falsification Methods Research Articles

Image Quality Difference Perception Ability: A BIQA model effectiveness metric based on model falsification method

Blind Image Quality Assessment (BIQA) methods refer to algorithms that predict image quality scores without reference images. This challenging area is crucial for preprocessing and optimizing visual tasks. Since BIQA is a small-sample task, it has become a common practice to apply transfer learning by using models pre-trained on other visual tasks, such as semantic recognition, to BIQA. This paper is interested in whether a backbone that performs better in semantic recognition also improves predictive accuracy in BIQA tasks. Comparative experiments showed that different semantic backbones with varying precision exhibit minimal differences in PLCC (Pearson Linear Correlation Coefficient) and SRCC (Spearman Rank Order Correlation Coefficient). However, further comparison shows that the semantic backbone does enhance the model’s IQA abilities, which traditional metrics fail to capture due to their oversight of quality differences between images. We term this ability as Image Quality Difference Perception Ability (IQDP Ability). Based on this, we propose an IQDP comparison method and a new metric, which can effectively compare and measure a model’s IQDP Ability, supplementing traditional metrics and providing an effective means of identifying superior models.

The development of honey recognition models with broad applicability based on the association of isotope and elemental content with ANNs

Honey adulteration represents a worldwide problem, driven by the illicit economic gain that producers, traders, or merchants pursue. Among the falsification methods that can unfairly influence the price is the incorrect declaration of the botanical origin and harvesting year. Therefore, the present study aimed to test the potential given by the application of Artificial Neural Networks (ANNs) for developing prediction models able to assess honey botanical origin and harvesting year based on isotope and elemental fingerprints. For each classification criterion, significant focus was dedicated to the data preprocessing phase to enhance the models' prediction capability. The obtained classification performances (accuracy scores >86% during the test phase) have highlighted the efficiency of ANNs for honey authentication as well as the feasibility of applying the developed classifiers for a large-scale application, supported by their ability to recognize the correct origin despite considerable variability in botanical source, geographical origin, and harvesting period.

A Scalable Compositional Falsification Approach for Identifying Challenging Scenarios in Cyber-Physical Systems

This article presents a scalable approach for identifying system inputs and trajectories that lead to undesirable scenarios in a cyber-physical system (CPS). The proposed approach falls under the broad class of falsification methods. The objective in falsification is to find initial conditions and input signals resulting in trajectories that violate a system property expressed as a formal specification. The existing falsification methods are not suitable for handling systems where the input at a specific time depends on the state history of the system. Autonomous vehicle platoons and certain multi-agent systems that are required to maintain connectivity are some examples of such systems. In the first part of this article, we employ a graph-search-based motion planning algorithm to develop a falsification method capable of identifying falsifying inputs for the aforementioned class of systems. We demonstrate the effectiveness of the approach through a case study involving a vehicle platoon consisting of three autonomous vehicles, wherein one of the vehicles is tasked to execute a lane-change maneuver. In the second part, we extend the proposed approach to analyze a network of three unmanned underwater vehicles, wherein our objective is to identify system inputs resulting in trajectories that lead to a deadlock. The approach leverages the component-based structure inherent in the considered multi-agent system and employs a surrogate model in place of computationally demanding components present in the system. These modifications are shown to improve the scalability of the approach and reduce the computational time in finding falsifying trajectories.

Taste sensations: the role of sensory analysis in controlling the quality of food products

The aim of the study was to investigate the factors that affect a persons subjective perception of food safety. Normative legal acts and documents regulating society as a whole and food products in particular were used during the study. It was proven that preserving and enhancing the specific sensory properties of a food product by changing its chemical composition using falsification methods, cheaper and less nutritious components, is a dangerous direction in the development of food technologies and the evolution of the food system. This approach can lead to a dissonance between the perception of the product as tasty and its nutritional value, which determines its health-preserving effect. The objective assessment of food safety is currently ensured (or should be ensured) by instrumental methods of quality control of food products, which are used in a system that includes both internal (production) control and external (state veterinary and state sanitary and epidemiological) supervision.

The United States-The People's Republic of China relations: A systemic level impact analysis

Are the United States (the US)- the People's Republic of China (the PRC) relations inevitably headed for war? The US-the PRC relations constitute one of the most interesting topics in terms of international political studies. Precisely for this reason, the study of political relations between the US and the PRC is of the great importance in terms systemic level of the international political studies. The main purpose of this study is to show that the relations of the US and the PRC, as two influential acting units at the level of systemic international politics, are of competitive cooperation. In this study, Popperian falsification method was used in the context of political, economic and cultural data revealed by bilateral relations. The definition of the inevitably dragged into a war by the US-the PRC with a historicist perspective also brings with it an important problem in terms of international political studies. This point also creates an important opportunity to discuss the explanatory capacity of international political theories. Considering the Structural Realist Theory in the US-the PRC case, it is seen that military, economic and social relations are important in terms of influencing the structure as much as the formation of the structure. The US-the PRC relations, it is seen that a competitive cooperation structure has emerged rather than a process leading to war.

Scholarly Research and Applied Approach to the Interdependence of Manufacture and Transportation of Products Based on Intermodality and Multimodality

Introduction. The integration processes of the transport system are an important factor in the economic development of Ukraine in conditions of increased competition for transit cargo flows. Therefore, it is necessary to develop multimodal transportation of products to ensure the competitiveness of Ukraine in the international transport market.Problem Statement. In the modern conditions of the development of the transport system of Ukraine, there have arisen theoretical and applied problems related to determining the most appropriate means for hybrid cargo transportation.Purpose. This study is aimed at identifying the interdependence of the sphere of manufacture and transportation of products in order to determine and justify the most efficient means of organization of intermodal and multimodal cargo transportation.Material and Methods. The review of existing scientific developments is based on systematic approach and comparative historical analysis of the transport economy, given the economic, geographical, and geopolitical position of Ukraine. The verification and falsification methods, as well as the economic and mathematical analysis and modeling have been used to substantiate the scholarly and applied approach.Results. The theoretical and practical problems of the transport economy development have been analyzed. The trends in the development of cargo transportation by various means of transport have been identified. The dependence of the products sold (goods, services) on the products transported by means of transport has been simulated. The types of activities, which require transport services and are significant for the national economy have been analyzed. The choice of the most appropriate means of transport for cargo transportation based on intermodality and multimodality, in particular rail, sea, and inland water transport, has been justified.Conclusions. The scholarly and applied approach has been proposed to identify the interdependence of manufacture, intermodal and multimodal cargo transportation of products. It can be used to increase the competitive advantages of Ukraine’s transit potential.

The role of falsification in the validation of numerical models

ABSTRACT Numerical modelling consists of simulating with informatic technologies the conditions of experiments that would require big resources in terms of time and costs. For example, structural engineering considers numerical models of structures because otherwise it would be too expensive to build and destroy a building to study its behaviour under collapse conditions. In this regard, numerical modelling has become a valid alternative to physical experiments since they fall within the scientific method as they need validation that consists in discarding models when the results are not considered reliable. The criterion of falsification is therefore the basis of the selection process not of the ‘most truthful’ model, but of the ‘model least’, that is, less affected by errors. The paper discusses the sources of errors at the base of numerical models by proposing the importance of validation as the application of the falsification method proposed by Karl Popper.

Testing Cyber–Physical Systems Using a Line-Search Falsification Method

Cyber-physical systems (CPSs) are complex and exhibit both continuous and discrete dynamics, hence it is difficult to guarantee that they satisfy given specifications, i.e., the properties that must be fulfilled by the system. Falsification of temporal logic properties is a testing approach that searches for counterexamples of a given specification that can be used to increase the confidence that a CPS does fulfill its specifications. Falsification can be done using random search methods or optimization methods, both of which have their own benefits and drawbacks. This article introduces two methods that exploit randomness to different degrees: 1) the optimization-free Hybrid-Corner-Random (HCR) and 2) the direct-search method Line-Search Falsification (LSF). HCR combines randomly chosen parameter values with extreme parameter values, which performs surprisingly well on benchmark evaluations. The gradient-free optimization-based LSF optimizes over line segments through a vector of inputs in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> -dimensional parameter space. The two methods are compared to the Nelder-Mead and SNOBFIT methods, using a well-known set of benchmark problems and LSF shows better performance than any of the evaluated methods.

Smart Cities and Transportation: Reviewing the Scientific Character of the Theories

The concept “smart city” nowadays designates a plethora of things. The multiple meanings associated with the smart city, and its imperfect synonym the “robotic city”, continue to provide a topic of debate. In this paper we aim to present an epistemologically grounded review of articles focused on the concept of “smart city” and its correlatives. The goal of this article is to ascertain whether the scientific character of the theories employed in such articles is discussed and/or ascertained. For this purpose, we used Popper’s method of falsification: a theory’s scientific character is determined by its falsifiability and eventual falsification. Papers from the literature were extracted using the PRISMA method, and 15 studies were assessed as eligible for analysis. Most conclusions and results expounded in the articles reviewed that claim to be scientific are arguably based on the unsound logic of verification and confirmation rather than falsification. This has the detrimental effect of reducing to the category of logically false universal instantiations the majority of conclusions about (a) smart city services and infrastructures, (b) intelligent transportation systems and (c) blockchain/Internet of Things.

When do religion and science meet in uncertainty?

This study reports on the concept of uncertainty through the words of Agur in the Book of Proverbs about four observed objects, namely the way of an eagle in the air, the way of a serpent upon a rock, the way of a ship amid the sea, and the way of a man with a woman. The approach used to explore those words is the uncertainty theory by Heisenberg and the falsification method by Popper. It can be concluded that uncertainty is one of the themes of the Bible that unites science and religion in a dialogical manner. The finding strengthens the perspective that science can demonstrate and strengthen the Bible narrations through certain themes. The study also shows that the metaphysic statements of the holy book are not always normative and can be accepted as the source of knowledge supporting its own methodology.Intradisciplinary and/or interdisciplinary implications: This research strengthens the intersection of religion and science. Although the two methodologies are different, there are intersection points where the two can explain and confirm each other.

Top interpretable neural network for handwriting identification.

Machine learning (ML) has become one of the most promising tools in forensics, despite its dominant method of artificial neural networks (ANNs) suffering from the black-box problem. While forensic methodology demands explainability and evaluativity, neural networks are unexplainable, hence almost unfalsifiable. Our study was conducted to mitigate this problem in a case-like context, by creating a novel top interpretable neural network (TINN) for identification of the authors of handwritten documents. The idea of top interpretability assumes that it is irrelevant how the handwriting features are extracted from documents, as long as they are semantically sensible and the sole determinants of identification. The model was tasked with supervised extraction of handwriting characteristics and subsequent identification of the writers on that basis. The interpretable model not only outperformed all comparative models in terms of author identification, but also underperformed in terms of features extraction (achieving satisfactory results nonetheless). Visualizations of features-extracted by the model to perform its tasks-suggest that it considers rational and semantically sensible features of handwriting, but we are unable to determine whether it learned the exact features of handwriting we desired. The approach of top interpretability proved to be effective in terms of accuracy and interpretability. Furthermore, if we were to judge features extracted by such a network as unconvincing, then our approach is a highly efficient method of falsification. Lastly, the success of this study-performed on a small-scale identificational problem-suggests that a similar approach could yield better results on a large-scale identificational or verificational problem.

Manipulation of compromising information as a method of falsification during the investigation in the Great Terror (on the example of A. Hepler’s archival-criminal case)

Manipulation of compromising information as a method of falsification during the investigation in the Great Terror (on the example of A. Hepler’s archival-criminal case)

Reply to Comment by D. Jiang on “Pressure‐to‐Depth Conversion Models for Metamorphic Rocks: Derivation and Applications”

AbstractIn our study (Bauville &amp; Yamato, 2021, https://doi.org/10.1029/2020gc009280), we derived simple formulas for pressure‐to‐depth conversion that allow (or not) to take into account deviatoric stresses. We then tested them against a data set of pressure from high‐pressure (HP) metamorphic rocks. In his comment, Jiang argues that the classical pressure‐to‐depth conversion, which assumes negligible deviatoric stresses (i.e., lithostatic pressure assumption) (a) provides a better explanation of the data and (b) is the only acceptable pressure‐to‐depth conversion method from the point of view of rock mechanics. We disagree with both arguments because (a) although Jiang's explanation is plausible, it does not falsify alternative models. As we concluded in Bauville and Yamato, several models explain equally well the data, and pressure data alone is not enough to validate or falsify any of these models. (b) There is a growing corpus of evidence that even HP metamorphic rocks undergo large deviatoric stress and can record even transient events in their mineralogical assemblage. Finally, Jiang criticizes that we used terms related to deformation loosely to illustrate stress concepts, and that our proposed method of falsification based on markers of deformation may be infeasible for HP metamorphic rocks. We take here the opportunity to clarify all these aspects.

Enhancing static-load-test identification of bridges using dynamic data

In situ measurements have the potential to provide valuable information about the safety and the condition of bridges through implementation of system-identification methodology. A significant amount of research has focused on system identification using either dynamic or static measurements separately. Realizing the complementary relationship between static and dynamic measurements, traditional model updating methods adopt error functions to account for the residual between modeling and measured values for various types of measurements. Behavioral models may be inaccurate due to incomplete representation of modeling and measurement uncertainties. Furthermore, the normalization of error functions may bring additional uncertainty to the identification process. In this paper, an approach based on the model falsification method is proposed to combine both static and dynamic measurements with explicit consideration of both modeling and measurement uncertainties. A measurement selection strategy is also used to help detect abnormal measurements. The approach has been evaluated using a highway flyover bridge in Singapore. Dynamic measurement data include natural frequencies and mode shapes whereas static measurement data include inclinations, deflections and strains. By combining both static and dynamic measurements, this approach leads to falsification of additional model instances and obtains a more precise prediction of parameter values than approaches which interpret static measurements only.

A study on the model of fact-finding in criminal investigation

Fact-finding, as the foundation of a judicial decision, has been an important consideration in China's judicial reform. This study introduces the theory of evidence-based information and falsification methods in the fact-finding procedure of criminal investigations and proposes a paradigm for fact-finding using combined pairs of approaches: individual evidence examination and global analysis, the objective basis and subjective perception of fact-finders, and methods of verification and falsification. The working procedure of the paradigm is illustrated with the objective of making a contribution to the improvement of the existing model of fact-finding in the criminal justice process.

Macroeconomic Research, Present and Past

What is the state of macroeconomics? We answer this question by hand collecting information about the epistemological approaches, theoretical and empirical methods, and data sources used by macroeconomists in their research. During the past 40 years there has been an increasing reliance on mathematical theory, particularly DSGE models, with theory-based papers now occupying the majority of space in macro journals. This shift is mirrored by a decline in the use of empirical falsification methods testing theoretical predictions. Microeconometric techniques have displaced time series methods, and empirical papers increasingly rely on micro and proprietary data sources. We document a decline and subsequent resurgence of financial frictions appearing in macro theory. Finally, we find that topics outside of macroeconomics are studied in more than three fourths of macro field journal publications.

Reachability Analysis for One Dimensional Linear Parabolic Equations

Partial differential equations (PDEs) mathematically describe a wide range of phenomena such as fluid dynamics, or quantum mechanics. Although great achievements have been accomplished in the field of numerical methods for solving PDEs, from a safety verification (or falsification) perspective, methods are still needed to verify (or falsify) a system whose dynamics is specified as a PDE that may depend not only on space, but also on time. As many cyber-physical systems (CPS) involve sensing and control of physical phenomena modeled as PDEs, reachability analysis of PDEs provides novel methods for safety verification and falsification. As a first step to address this challenging problem, we propose a reachability analysis approach leveraging the well-known Galerkin Finite Element Method (FEM) for a class of one-dimensional linear parabolic PDEs with fixed but uncertain inputs and initial conditions, which is a subclass of PDEs that is useful for modeling, for instance, heat flows. In particular, a continuous approximate reachable set of the parabolic PDE is computed using linear interpolation. Since a complete conservativeness is hardly achieved by using the approximate reachable set, to enhance the conservativeness, we investigate the error bound between the numerical solution and the exact analytically unsolvable solution to bloat the continuous approximate reachable set. This bloated reachable set is then used for safety verification and falsification. In the case that the safety specification is violated, our approach produces a numerical trace to prove that there exists an initial condition and input that lead the system to an unsafe state.

Rdrobust: Software for Regression-discontinuity Designs

We describe a major upgrade to the Stata (and R) rdrobust package, which provides a wide array of estimation, inference, and falsification methods for the analysis and interpretation of regression-discontinuity designs. The main new features of this upgraded version are as follows: i) covariate-adjusted bandwidth selection, point estimation, and robust bias-corrected inference, ii) cluster–robust bandwidth selection, point estimation, and robust bias-corrected inference, iii) weighted global polynomial fits and pointwise confidence bands in regression-discontinuity plots, and iv) several new bandwidth selection methods, including different bandwidths for control and treatment groups, coverage error-rate optimal bandwidths, and optimal bandwidths for fuzzy designs. In addition, the upgraded package has superior performance because of several numerical and implementation improvements. We also discuss issues of backward compatibility and provide a companion R package with the same syntax and capabilities.

Why the Objectivist Interpretation of Falsification Matters

The article distinguishes between subjectivist and objectivist interpretations of scientific method, links subjectivism with good reasons, and argues its uselessness for our understanding of science. It applies the distinction to the method of falsification, explains why objectivism regards falsification to be conjectural, immune to the Duhem–Quine thesis, and immune to the problem of underdetermination. It confronts the falsifying mode of inference with the fallacy of begging the question and with the paradox of inference, and suggests how modus tollens helps scientists to find out that a tested theory is false, in spite of the fact that the falsity of the theory is asserted in its premises.

Falsification of Financial Statements: Historical and Evolutionary Aspect

Both Russian and foreign researchers devote their studies to the nature of falsification of financial statements. This subject was under interest of Russian accounting specialists since the beginning of the XX century. Therefore, the objective of the paper was to track historical development of the notion of financial statement falsification and its definition. This improves our understanding of falsification methods and helps to throw light to ways to prevent it. DOI: 10.5901/mjss.2014.v5n24p41