Flawed Analysis Research Articles

A Note on Related-Tweakey Impossible Differential Attacks

In this note we review the technique proposed at ToSC 2018 by Sadeghi et al. for attacks built upon several related-tweakey impossible differential trails. We show that the initial encryption queries are improper and lead the authors to misevaluate a filtering value in the key recovery phase. We identified 4 other papers (from Eurocrypt, DCC, and 2 from ToSC) that follow on the results of Sadeghi et al. and in three of them the flawed technique was reused. We thus present a careful analysis of these types of attacks and give generic complexity formulas similar to the ones proposed by Boura et al. at Asiacrypt 2014. We apply these to the aforementioned papers and provide patched versions of their attacks. The main consequence is an increase in the memory complexity. We show that in many cases (a notable exception being quantum impossible differentials) it is possible to recover the numeric time estimates of the flawed analysis, and in all cases we were able to build a correct attack reaching the same number of rounds.

Parcel level temporal variance of remotely sensed spectral reflectance predicts plant diversity

Over the last two decades, considerable research has built on remote sensing of spectral diversity to assess plant diversity. The spectral variation hypothesis (SVH) proposes that spatial variation in reflectance data of an area is positively associated with plant diversity. While the SVH has exhibited validity in dense forests, it performs poorly in highly fragmented and temporally dynamic agricultural landscapes covered mainly by grasslands. Such underperformance can be attributed to the mosaic-like spatial structure of human-dominated landscapes with fields in varying phenological and management stages. Therefore, we argued for re-evaluating SVH’s flawed window-based spatial analysis and underutilized temporal component. In particular, we captured the spatial and temporal variation in reflectance and assessed the relationships between spatial and temporal components of spectral diversity and plant diversity at the parcel level as a unit that relates to management patterns. Our investigation spanned three grasslands on two continents covering a wide spectrum of agricultural usage intensities. To calculate different components of spectral diversity, we used multi-temporal spaceborne Sentinel-2 data. We showed that plant diversity was negatively associated with the temporal component of spectral diversity across all sites. In contrast, the spatial component of spectral diversity was related to plant diversity in sites with larger parcels. Our findings highlighted that in agricultural landscapes, the temporal component of spectral diversity drives the spectral diversity-plant diversity associations. Consequently, our results offer a novel perspective for remote sensing of plant diversity globally.

Technical language processing for Prognostics and Health Management: applying text similarity and topic modeling to maintenance work orders

AbstractModern manufacturing paradigms have incorporated Prognostics and Health Management (PHM) to implement data-driven methods for fault detection, failure prediction, and assessment of system health. The maintenance operation has similarly benefitted from these advancements, and predictive maintenance is now being used across the industry. Despite these developments, most of the approaches in maintenance rely on numerical data from sensors and field devices for any sort of analysis. Text data from Maintenance Work Orders (MWOs) contain some of the most crucial information pertaining to the functioning of systems and components, but are still regarded as ‘black holes’, i.e., they store valuable data without being used in decision-making. The analysis of this data can help save time and costs in maintenance. While Natural Language Processing (NLP) methods have been very successful in understanding and examining text data from non-technical sources, progress in the analysis of technical text data has been limited. Non-technical text data are usually structured and consist of standardized vocabularies allowing the use of out-of-the-box language processing methods in their analysis. On the other hand, records from MWOs are often semi-structured or unstructured; and consist of complicated terminologies, technical jargon, and industry-specific abbreviations. Deploying traditional NLP to such data can result in an imprecise and flawed analysis which can be very costly. Owing to these challenges, we propose a Technical Language Processing (TLP) framework for PHM. To illustrate its capabilities, we use text data from MWOs of aircraft to address two scenarios. First, we predict corrective actions for new maintenance problems by comparing them with existing problems using syntactic and semantic textual similarity matching and evaluate the results with cosine similarity scores. In the second scenario, we identify and extract the most dominant topics and salient terms from the data using Latent Dirichlet Allocation (LDA). Using the results, we are able to successfully link maintenance problems to standardized maintenance codes used in the aviation industry.

Counterfactual mobility network embedding reveals prevalent accessibility gaps in U.S. cities

Living in cities affords expanded access to various resources, infrastructures, and services at reduced travel costs, which improves social life and promotes systemic gains. However, recent research shows that urban dwellers also experience inequality in accessing urban facilities, which manifests in distinct travel and visitation patterns for residents with different demographic backgrounds. Here, we go beyond simple flawed correlation analysis and reveal prevalent accessibility gaps by quantifying the causal effects of resident demographics on mobility patterns extracted from U.S. residents’ detailed interactions with millions of urban venues. Moreover, to efficiently reveal micro neighborhood-level accessibility gaps, we design a novel Counterfactual RANdom-walks-based Embedding (CRANE) method to learn continuous embedding vectors on urban mobility networks with confounding effects disentangled. Our analysis reveals significant income and racial gaps in mobility frequency and visitation rates to sports and education venues. Besides, bachelor’s degree holders experience greater mobility reduction during the COVID-19 crisis. With extensive experiments on neighborhood-level accessibility prediction and visualizing accessibility gaps with embeddings vectors, we demonstrate that the counterfactual mobility network embeddings can improve the explanatory capacity and robustness of revealed accessibility gaps by extending them from aggregate statistics to individual neighborhoods and allowing for cross-city knowledge transfer. As such, urban mobility networks can reveal consistent accessibility gaps in the U.S., calling for urgent urban design policies to fill in the gaps.

Oduduwa: Through the Eyes of a Wood Carver

History is the chronological and integrated account of relationship between man, event, person, time and places. The Yoruba history has long been at the mercy of the West due to the disinterest of the Yoruba people in the preservation and propagation of their Tradition, Culture and Religion. This has led to the publication of volumes of misinterpretations, flawed and shallow analysis of Yoruba religion for which the Yoruba could only be grateful. Oduduwa is one of the most important Yoruba Progenitor in the history of the Yoruba tribe in Nigeria. He was a powerful leader under whom the nucleus of the Yoruba race migrated into this land from their original home in Ile-Ife. He was a man of great leadership skills, understanding and repute. He is one of the most discussed Yoruba Deity with different point of view because various scholars have not come to a conclusion of who he was. Unfortunately, from our oral Yoruba traditional history there is no descriptive analysis of how Oduduwa looked like but, however, a sculptor in person of Lamidi Fakeye, a traditional wood carver, carried out a commissioned work of Oduduwa in wood carving, describing what he looks like through a story which surrounds the creation of the world. The paper intends to discuss the life of Oduduwa and a conceptual analysis of the wood carving executed in his form. The background data for this paper came largely from textbooks, articles, field work, documentation, archival records, and observation of physical artefacts.

Artificial intelligence SoS framework for sustainable agricultural production

Iraq’s population will have reached 50 million by 2030, according to the Ministry of Planning. This population growth must be handled by ensuring food security stability in the face of expected obstacles resulting from global warming. The agricultural sector encounters limitations due to ineffective detection of persistent agricultural obstacles like pathogens, flawed soil analysis, insect infestations, inadequate irrigation, and drainage. More proven farming strategies must be transferred using modern technological leaps from this vantage point. It is clear from the outset that this paper aims to discuss how artificial intelligence might aid in the growth of conventional methods in agriculture. This involves tracking and guiding each stage of agriculture through the adoption of an intelligent system, which in turn includes managing a set of intelligent systems that control and supervise the rest of the processes (System of Systems or SoS), beginning with ploughing, crop pattern, type of fertilizer, and the appropriate type of irrigation. On the other hand, this technology collection could give farmers an accurate view of market trends and customer preferences, resulting in greater output. This paper gives an insight into the concept of a SoS and the application of artificial intelligence in various fields of agricultural engineering in Iraq. It also proposes an intelligence framework model for self-cultivation and incorporates competitive strategies to develop a decent ecosystem to transform traditional agriculture into smart and accurate agriculture.

The Yom Kippur intelligence failure after fifty years: what lessons can be learned?

ABSTRACT Extensive research has been published about the failure of Israeli intelligence in the Yom Kippur War in 1973, mainly in the context of flawed analysis and strategic surprise. Fifty years after the war, the current article uses an intelligence studies lens to describe major lessons which can be learned from this failure of early warning. Such lessons include the required focus of strategic intelligence on identifying change rather than continuity, the need for explicit analytical methodology beyond inductive reasoning, the importance of integrating assessment of adversary intentions and capabilities, the risk of over-reliance on raw information, and the need for a culture encouraging contrarian thinking.

Epic Battles in Two-Sided Markets

Epic Games, the developer of the enormously popular Fortnite, sued Apple for allegedly violating §1 and §2 of the Sherman Act. The central issue was Apple’s requirement that iPhone-compatible apps be purchased in its App Store. Because Apple collects a 30 percent ad valorem tax on each transaction, Epic Games offered an alternative payment option to iPhone owners through the Fortnite app so that consumers could avoid Apple’s 30% fee. When Apple expelled Epic Games from its App Store, Epic sued. In this article, we examine the flawed analysis of the District Court, which can be traced to a fundamental misunderstanding of economic principles.

The Better Angels of Our Nature: Why Violence Has Declined

Pinker’s goal to provide evidence that accounts for the falling homicide and violent combat death rates in the modern world is insufficient and, more often than not, misguided. The main issue being his failure to set up a productive analytical approach that lives up to his remarkably overarching research question: today’s level of global violence is the lowest in history. While he has attempted to present the violence levels typically in the past by coupling empirical and archeological data of the prehistory mankind, he lacks the credibility to do so for mainly two reasons: the sheer limitation of archeological evidence prior to the development of modern nation-state along with his flawed statistical analysis, and his persistence to treat war mortalities as merely an empirical variable. Similarly, though this article makes only remote attempts to examine the actual trend in civilizational and cultural conflict over a longer time period, it has brought into attention the demand to incorporate constructivist approach into the study of violence in order to better comprehend its complexities which have been largely driven by the development in the new wars. For the reasons mentioned above, Pinker has and will continue to get the violence levels wrong, and the world is as violent as ever.

Severe publication bias contributes to illusory sleep consolidation in the motor sequence learning literature.

We explored the possibility of publication bias in the sleep and explicit motor sequence learning literature by applying precision effect test (PET) and precision effect test with standard errors (PEESE) weighted regression analyses to the 88 effect sizes from a recent comprehensive literature review (Pan & Rickard, 2015). Basic PET analysis indicated pronounced publication bias; that is, the effect sizes were strongly predicted by their standard error. When variables that have previously been shown to both moderate the sleep gain effect and substantially reduce unaccounted for effect size heterogeneity were included in that analysis, evidence for publication bias remained strong. The estimated postsleep gain was negative, suggesting forgetting rather than facilitation, and it was statistically indistinguishable from the estimated postwake gain. In a qualitative review of a smaller group of more recent studies we observed that (a) small sample sizes-a major factor behind the publication bias-are still the norm, (b) use of demonstrably flawed experimental design and analysis remains prevalent, and (c) when authors conclude in favor of sleep-dependent consolidation, they frequently do not cite the articles in which those methodological flaws have been demonstrated. We conclude that there is substantial publication bias, that there is no consolidation-based, absolute performance gain following sleep, and that strong conclusions regarding the hypothesis of less forgetting after sleep than after wakefulness should await further research. Recommendations are made for reducing publication bias in future work. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Blind dates: Exploring uncertainty in the radiocarbon evidence on the emergence of animal husbandry in the Dutch wetlands

The emergence of animal husbandry in the Netherlands remains the subject of much speculation. Challenges in identifying domesticated animals among the faunal remains, inconsistent excavation documentation, and flawed radiocarbon analysis have resulted in questionable chronologies. This paper examines the available radiocarbon evidence from selected sites which are the mainstay of early examples of domesticated animals in the Netherlands, between 5000 and 4000 BCE.1All radiocarbon dates given in this paper, denoted as BCE, are calibrated unless stated otherwise.1 We approach the legacy data in two ways: by employing principles of chronometric hygiene to reassess the radiocarbon datasets of selected sites and by exploring the use of such data for future studies in chronology by means of Bayesian chronological modelling. The latter is demonstrated with a case study, whereby we employ legacy data from Hardinxveld-Giessendam De Bruin in Bayesian models to demonstrate that, despite their shortcomings, such dates remain a valuable resource for much needed future chronological analysis.

Sample preparation and quantitative UHPLC-MS/MS analysis in an accredited high-throughput environment: Tips and tricks to improve your success ratio

Ultra-High Performance Liquid Chromatography coupled to tandem Mass Spectrometry (UHPLC-MS/MS) is often the technique of choice for quantitative toxicological analysis. Though accessible at face-value, routine application with consistent performance requires a good framework (quality management system, QMS) including thoroughly validated methods, trained analysts and regularly serviced hardware. Even in such contained environments, unforeseen complications can occur. Therefore rapid, accurate troubleshooting to identify swift corrective actions are needed to ensure day-to-day lab continuity. Based on our personal experience, we present a practical non-limitative guide to help troubleshoot and evade common problems when performing quantitative UHPLC-MS/MS analysis. The laboratory of toxicology at Belgium's National Institute for Criminalistics and Criminology (NICC) performs large volumes of quantitative UHPLC-MS/MS analysis of illicit drugs in blood and oral fluid (> 15 000 samples/year). The laboratory and methods used are ISO 17025 accredited. The QMS requires every deviation to be described and a root cause analysis to be performed. When troubleshooting a flawed analysis, the most important aspect is identifying whether the extraction process itself or the UHPLC-MS/MS equipment is at the origin. Therefore, before the injection of any extracted sample batch, a system suitability test (SST) should be performed. We recommend a three-way SST consisting of (1) ‘no inject’ (2) reconstitution solvent and (3) a test solution. The ‘no inject’ consists of the UHPLC running the programmed gradient without injecting a sample. Unanticipated peaks at this stage originate from within the UHPLC-MS/MS system itself. Injection of the reconstitution solvent helps to identify possible contaminations or an increased baseline in the chromatogram. The test vial contains a non-extracted solution of known composition. The resulting areas, signal-to-noise ratios, peak shapes, resolutions should be tracked as a function of time for as long as the method is routinely used. Deviations in the SST point to non-compliant equipment. In general, retention shifts and unacceptable peak shapes will originate from the UHPLC. Both can be caused by normal column wear, therefore track the amount of column injections and define an in-house maximum. Sensitivity issues in the test warrant further investigation of the MS system. The regularity and thoroughness of MS maintenance/cleaning will depend on the applications and should be determined in-house. Note that not all analytes will be affected in the same way by a poorly maintained system. If the UHPLC-MS/MS equipment functions properly but the batch analysis does not meet acceptation criteria, it's likely due to an error in the extraction process. At this stage on should evaluate whether all compounds or a certain kinds is affected. Typical examples are: amphetamines lost due to volatility, esters hydrolysing and instabilities in highly organic elution solvent. Blank's containing analytes indicate contamination. Before troubleshooting a contamination: look back at the system suitability test (no inject) and evaluate the potential presence of a highly concentrated sample in the batch (carry-over and/or system contamination). Subsequently, consider which analytes are present (all, just one, or parent + metabolite) and in which vials they are present (e.g. in each vial or only a few). If a parent and it's metabolite are present as a contamination, it may be traced to a highly concentrated sample recently processed in the lab. A practical guide is presented to assist in troubleshooting when performing quantitative UHPLC-MS/MS analysis. A well thought-out SST is most valuable. Pinpointing the extraction, the LC or the MS as the source of the problem is vital. The source of error during the extraction process can be hinted at by the amount of vials and the type of compounds affected.

Comment on ‘Quantum gravity evolution in the Hawking radiation of a rotating regular Hayward black hole’

We review the derivations and conclusions made in Ali et al. (2022), and show that the metric derived there is not a valid rotating solution yielding a flawed analysis throughout the paper.

Automatic missing value imputation for cleaning phase of diabetic’s readmission prediction model

Recently, the industry of healthcare started generating a large volume of datasets. If hospitals can employ the data, they could easily predict the outcomes and provide better treatments at early stages with low cost. Here, data analytics (DA) was used to make correct decisions through proper analysis and prediction. However, inappropriate data may lead to flawed analysis and thus yield unacceptable conclusions. Hence, transforming the improper data from the entire data set into useful data is essential. Machine learning (ML) technique was used to overcome the issues due to incomplete data. A new architecture, automatic missing value imputation (AMVI) was developed to predict missing values in the dataset, including data sampling and feature selection. Four prediction models (i.e., logistic regression, support vector machine (SVM), AdaBoost, and random forest algorithms) were selected from the well-known classification. The complete AMVI architecture performance was evaluated using a structured data set obtained from the UCI repository. Accuracy of around 90% was achieved. It was also confirmed from cross-validation that the trained ML model is suitable and not over-fitted. This trained model is developed based on the dataset, which is not dependent on a specific environment. It will train and obtain the outperformed model depending on the data available.

EFSA Strikes Again: A Commentary on Flawed Analysis

In 2009, Marcia Angell, the former editor-in-chief of the New England Journal of Medicine, wrote that it was simply no longer possible to believe much of the clinical research that is published, or to rely on the judgement of trusted physicians or scientific authorities both to develop and to interpret data. We are concerned that this rather stunning indictment may increasingly describe some of the work of the regulatory agencies tasked to oversee public health, and in particular food safety. In the foregoing commentary we focus upon one recent and as yet unsettled instance involving the recommendations made by the European Food Safety Authority about food products containing Aloe vera gel and associated hydroxyanthracene (HAD) compounds. It is not our intention to suggest avenues for future research; rather, it is a call for more rigorous and precise interpretation of the best available science in support of decisions about safety. Moreover, it is our hope that the analysis of this case will illuminate the ways in which even the finest regulatory body may be prone to a significant error in a rush to judgment about novel products.

Critical Response to "A Short History of K-12 Public School Spending in British Columbia"

In Issue 196 of the Canadian Journal of Educational Administration and Policy (CJEAP), the journal published an article by Jason Ellis, A Short History of K-12 Public School Spending in British Columbia, 1970-2020 that claimed “K-12 public education spending in British Columbia – adjusted for inflation – is 250 percent higher in 2020 than it was in 1970” (Ellis, 2021, p. 102). We illustrate how this claim lacks a theoretical framework, is based on weak data sources, a flawed research method and skewed analysis that results in a misleading understanding of resource allocations in BC. We present alternative ways to understand spending on education in BC in an effort to correct the scholarly and public record.

Crossing Birthweight-Specific Mortality Curves: How a Puzzling Clinical Observation Led to an Important Advance in Epidemiologic Methods.

Clinicians have long noted that although African-American neonates were more likely than white neonates to weigh <2500 grams at birth (low birthweight), among low birthweight infants African-Americans were more likely than whites to survive. However when born at normal weight, African-American infants were substantially less likely to survive. The observation generated much physiological speculation, and several clever mathematical manipulations were devised to "uncross the mortality curves." With the development and dissemination of Directed Acyclic Graphs in the early 2000s, methodologists focused on perinatal epidemiology showed graphically, in an early use of Directed Acyclic Graphs, that birthweight was a "collider", and that controlling for birthweight, whether by regression, stratification or restriction, introduced confounding of the race-mortality association by all unmeasured common causes of birthweight and mortality. These investigations showed that the crossing curves could be explained as an artifact of a conceptually flawed analysis. These results have applicability beyond perinatal epidemiology, including to the "obesity paradox."

Multi-Aspect Streaming Tensor Ring Completion for Dynamic Incremental Data

As the volume of real-world data with numerous missing entries continues to grow rapidly, tensor completion has been a powerful tool to enhance such flawed data analysis. While existing methods mainly consider static data, there is a great need to deal with streaming data. In this letter, a multi-aspect streaming tensor ring completion (MASTR) method is proposed, where the low-rank tensor ring (TR) model is exploited to capture subspace information and transfer high-order correlations between multiple sub-tensors. Experimental results on synthetic data, hyperspectral data and video data demonstrate superior recovery performance compared to state-of-the-art methods.

Regulated Inequity: How Regulators’ Acceptance of Flawed Financial Analysis Inflates the Profit of Public Utility Companies in the United States

Regulated Inequity: How Regulators’ Acceptance of Flawed Financial Analysis Inflates the Profit of Public Utility Companies in the United States

Watching North Korea from the sky: Remote sensing and documenting human rights in the Democratic People's Republic of Korea

For organisations committed to documenting human rights abuses in North Korea, gathering data is an ongoing challenge. Faced with the lack of access to the country, as well as the problems inherent in verifying testimonies from North Korean escapees, some organisations have turned to hybrid methodologies, including pairing remote sensing (RS) technologies with testimonial data to better understand the people, places and institutions associated with human rights violations. In the case of North Korea, to date, remote sensing has been used primarily to monitor nuclear weapons and missile development sites. This work has at times sparked controversy, given the scope for analytical error and the high stakes associated with flawed analysis. Against this backdrop, this article discusses the application of remote sensing to augment human rights abuse investigations and calls for greater attention to the potential of remote sensing data to both assist in eliciting information in research interviews, and to generate data that may be used to support the pursuit of accountability for alleged violations of international law. Specifically, it considers the work of an ongoing project developed in South Korea using satellite imagery and Geographic Information Systems technology together with witness testimonies to document sites of state-led killings and burials in North Korea. The paper cites advantages to be had from developing hybrid methods of data-gathering in this context and describes some of the key methodological considerations involved, as well as the possible applications of the data in seeking justice and remedy in the future.