Irrelevant Values Research Articles

Sustainable Reflexivities on Perennial Philosophy and Christian Education Management

The background of this research is the authors' anxiety in the midst of accelerating times in the education space as if to announce that the old educational values are outdated and irrelevant values. This thoughts are more to the prioritization of constructive philosophy, or something that is deconstructed. Meanwhile, the context of education cannot be universalized into one even though the regulations in education in a country cover the whole. Old values are meaningful and timeless values that are timeless. This kind of thinking is a thought that departs from the philosophy of perennialism. This is qualitative research with data search through data sourced from journals as previous research as a secondary source. Results show that the philosophy of perennialism here serves as an analytical and differentiating tool to look back at the philosophy of constructionism as a criticism as well as a realization for the world of education in the form of the importance of maintaining existing or embedded values so far.

Using best performance machine learning algorithm to predict child death before celebrating their fifth birthday

IntroductionChild morbidity and mortality in resource-limited settings is a major public health problem. The previous studies were mainly concerned with determining the prevalence of child deaths and identifying associated factors. Extracting knowledge and discovering insights from hidden patterns in child data through supervised machine learning algorithms is limited. Therefore, this study aimed to predict the under-five death of children using a best performance-supervised machine learning algorithm. MethodsA total of 1813 samples were used from the 2019 Ethiopian Demographic and Health Survey dataset. 70% and 30% of total instances were used for training the model and measuring the performance of each algorithm with 10-fold cross-validation techniques respectively. Five supervised machine learning algorithms were considered for model building and comparison. All the included algorithms were evaluated using confusion matrix elements. Information gain value was used to select important attributes to predict child deaths. The If/then logical association was used to generate rules based on relationships among attributes using Weka version 3.8.6 software. ResultsJ48 is the second-best performance algorithm next to the random forest to predict child death, with 77.8% and 93.9% accuracy, respectively. Late initiation of breastfeeding, mothers with no formal education, short birth intervals, poor wealth status of the mother, and unexposed to media were the top five important attributes to predict child deaths. A total of six associated rules were generated that could determine the magnitude of child deaths. Of these, if children were rural residents, had a short birth interval, and if born as multiples (twins), then the probability of child death was 83.6%. ConclusionsFive machine learning algorithms were included to predict child deaths and generate rules. Hence, the random forest algorithm was the best algorithm to predict child deaths. However, the study was limited since important attributes were not included in the data source, and irrelevant values were found. So, researchers are encouraged to use machine learning algorithms for future studies including important attributes that could predict child death. The current findings would be useful for stakeholders’ preparedness, and taking proactive childcare interventions. Encouraging women in education, media access, and economic development programs are essential interventions for child death reduction.

Data imputation in deep neural network to enhance breast cancer detection

AbstractBreast cancer is one of the most precarious cancers that claims many women's' lives every year. The existing automated systems for mammography datasets are designed to detect the abnormalities and classify them as benign or malignant. However, these systems ignore the incompleteness of data due to missing or irrelevant values in the dataset, which severely impede the automated system's reliability. To enhance the reliability of the decision outcomes, this study proposes a composite imputed multilayer fully connected deep networks (MFCN) that can replace the incomplete values in the dataset to augment the efficient feature learning for breast cancer classification. The data imputation techniques and one‐hot encoding transformation applied to the dataset are proved to improve the feature representation. The imputed features extracted from the instances are fed into the MFCN to classify malignant and benign by utilizing mammographic mass (MM) and INbreast datasets. The performance of the proposed missing data imputation treated MFCN (MdI‐MFCN) is compared with competitive machine learning (ML) classifiers by incorporating stratified 6‐fold cross‐validation. The experimental results of the models are evaluated with and without imputed data using the five performance metrics, namely, accuracy, precision, recall, F1‐score, and specificity. The performance of the proposed MdI‐MFCN has outperformed the competitive classifiers with the highest accuracy of 93% and 98% of the area under the receiver operating characteristic (ROC) curve on MM and INbreast datasets, respectively. The simplicity and reliability of this proposed approach its potential in characterizing mammography datasets during breast cancer diagnosis.

Using alignment-free methods as preprocessing stage to classification whole genomes

In bioinformatics systems, the study of genetics is a popular research discipline. These systems depend on the amount of similarity between the biological data. These data are based on DNA sequences or raw sequencing reads. In the preprocessing stage, there are several methods for measuring similarity between sequences. The most popular of these methods is the alignment method and alignment-free method, which are applied to determine the amount of functional matching between sequences of nucleotides DNA, ribosome RNA, or proteins. Alignment-based methods pose a great challenge in terms of computational complexity, In addition to delaying the time to search for a match, especially if the data is heterogeneous and its size is huge, and thus the classification accuracy decreases in the post-processing stage. Alignment-free methods have overcome the challenges of alignment-based methods for measuring the distance between sequences, The size of the data used is 1000 genomes uploaded from National Center for Biotechnology Information (NCBI), after eliminating the missing and irrelevant values, it becomes 860 genomes, ready to be segmented into words by the k-mer analysis, after which the frequency of each word is counted for each query. The size of a word depends on a value of k. In this paper we used a value of k =3 ….8, for each iteration will count times of frequencies words.

How formal is the ethics of responsibility?

Max Weber’s last in his life publications give grounds to correct the traditional notions of the ethics of responsibility as purely calculative and one that subordinates the ethical goal to the right means of achieving it and the strictness of its observance. For Weber devotion to certain values is ultimately the basis of any possible ethics: in the ethics of conviction, this devotion is contrasted with taking into account all the results of the ethical act, and in the ethics of responsibility these results seek to take into account what should make certain values more reliable. Passionate commitment to political goals that express the interests of the community, rather than the selfish and vain intentions of the politician is a solid basis for the responsibility of the politician. The passionate pursuit of truth directs the scientist’s well-thought-out research pro- gram. In economics, the pursuit of personal gain, which is inherent for the “economic man”, requires consideration of the common economic good both for those with whom the man makes his business and for the community, which is his lifeworld and creates the necessary conditions for any possible economic activity. In any social sphere, each social system has its own logic of calculating success, but each time this calculation involves respecting and protecting the basic values for this system. In everyday life we observe numerous deviations from this clear and transparent logic of the ethics of responsibility, which create the illusion of its dysfunction. Similarly, insincere and inconsistent adherence to declared beliefs can give the wrong impression of the whole ethics of conviction. It is these deviations from the intrinsic integrity of the ethics of responsibility and the ethics of persuasion that create the false impression of them as mutu- ally exclusive behavioral strategies. In their conscientious pursuit, the ethics of conviction and the ethics of responsibility complement each other. The formalism of the ethics of responsibility makes sense only for a stricter and more impartial protection of the values that are important to the adherents of this ethic. This formalism is a denial only of all other, irrelevant values, and not a designation of responsibility for a particular ethical commitment as a value-empty, indifferent form. Weber points to the prospect of recognition as a path to a collective ethic of responsibility in its positive sense — as a conscious commitment by a community of like-minded people to commit to values that are significant to them.

Anchoring-and-Adjustment During Affect Inferences.

People can easily infer the thoughts and feelings of others from brief descriptions of scenarios. But how do they arrive at these inferences? Three studies tested how, through anchoring-and-adjustment, people used semantic and numerical anchors (irrelevant values provided by experimenters) in inferring feelings from scenario descriptions. We showed that in a between-subject design, people’s inference was biased toward anchoring information (Studies 1 and 2). People made fewer adjustments (anchoring increased) under time pressure in the high-anchor condition but not in the low-anchor condition (Study 3). When inferring affect from scenario descriptions, not only did people integrate their inference with the context, they adjusted away from the initial anchors provided by the experimenters. However, time pressure discouraged people from making adequate adjustments.

Temporal Cognition Can Affect Spatial Cognition More Than Vice Versa: The Effect of Task-Related StimulusSaliency.

Cognition of space and time affect each other; a line with longer length appears to be longer in exposure duration (space on time), and a line with longer exposure duration appears to be longer in length (time on space). This cognitive interaction is known to be asymmetric; the effect of space on time is larger than that of time on space. We conjectured that this asymmetry is not intrinsic but may depend on the saliency of relevant signals. Participants were asked to judge the visual exposure duration of lines that varied in length or the lengths of the lines with different exposure times. The ranges of task-relevant and -irrelevant stimulus values were the same in the spatial and temporal tasks. Task difficulty was also evaluated by subjective rating. We found that duration affected the judgment of length more than vice versa, when the spatial task was significantly more difficult than the temporal task. Together with our previous results that showed the opposite effect, our conjecture is supported that the saliency of stimuli should affect the balance of interactions.

In Situ Wettability Characterization of Chemically Heterogeneous Surfaces Probed by Ionic Liquid Contact Angle in Vacuum: Pentacene on Single-Crystal SrTiO3(001)

Intrinsic surface wettability of pentacene thin films with different island coverages grown on single-crystal SrTiO3(001) was investigated by an in situ contact angle measurement in a high vacuum using ionic liquid as a probe fluid. The contact angle at the quasi-equilibrium state, which was measured at a certain time after its fast decay depending on the liquid viscosity, increased with the deposition amount of pentacene and saturated when the surface was fully covered with pentacene islands. The observed island coverage dependence of the in situ contact angle was well-fitted by a three-component Cassie equation composed of surface areas of not only the bare substrate and island pentacene but also adsorbed pentacene. The importance of the in situ contact angle measurement was confirmed by the result of an air exposure experiment, where the contact angle took almost irrelevant values to the integral coverage of pentacene, suggesting the significant effects of airborne contaminants on the surface wettability.

Distribution-centric 3-parameter thermodynamic models of partition gas chromatography

If both parameters (the entropy, ΔS, and the enthalpy, ΔH) of the classic van’t Hoff model of dependence of distribution coefficients (K) of analytes on temperature (T) are treated as the temperature-independent constants then the accuracy of the model is known to be insufficient for the needed accuracy of retention time prediction. A more accurate 3-parameter Clarke-Glew model offers a way to treat ΔS and ΔH as functions, ΔS(T) and ΔH(T), of T. A known T‐centric construction of these functions is based on relating them to the reference values (ΔSref and ΔHref) corresponding to a predetermined reference temperature (Tref). Choosing a single Tref for all analytes in a complex sample or in a large database might lead to practically irrelevant values of ΔSref and ΔHref for those analytes that have too small or too large retention factors at Tref. Breaking all analytes in several subsets each with its own Tref leads to discontinuities in the analyte parameters. These problems are avoided in the K‐centric modeling where ΔS(T) and ΔS(T) and other analyte parameters are described in relation to their values corresponding to a predetermined reference distribution coefficient (KRef) − the same for all analytes. In this report, the mathematics of the K‐centric modeling are described and the properties of several types of K‐centric parameters are discussed. It has been shown that the earlier introduced characteristic parameters of the analyte-column interaction (the characteristic temperature, Tchar, and the characteristic thermal constant, θchar) are a special chromatographically convenient case of the K‐centric parameters. Transformations of T‐centric parameters into K‐centric ones and vice-versa as well as the transformations of one set of K‐centric parameters into another set and vice-versa are described.

A Bayesian approach for estimating hexabromocyclododecane (HBCD) diastereomer compositions in water using data below limit of quantification.

We developed a statistical model that quantitatively incorporated the stochastic fluctuations of values, which were estimated as Bayesian credible intervals (BCIs), to analyze environmental monitoring data. We used α-hexabromocyclododecane (α-HBCD) diastereomer compositions of water samples that included data points below limit of quantification. To avoid replacing "not detected (ND)" values with irrelevant values in data analysis, we substituted ND with observed values from the measurement system upon examination of the model. In our study, it was assumed that the magnitude of stochastic fluctuations of observed values in environmental samples was identical to that in iterative measurements of a standard solution at the lowest concentration. Using this model, α-HBCD diastereomer compositions could be estimated along with BCIs even for samples collected from sites where concentrations of α-HBCD were ND or near limit of quantification. The brackish areas in our study showed relatively wide ranges in composition for the 95% BCIs compared with samples from fresh water areas. In the brackish areas, concentrations of HBCD were frequently ND or near limit of quantification. Using this model, it was unnecessary to replace ND with zero or limit of quantification in data analysis, and an environmental assessment could be achieved using all of the data. Therefore, this model is considered to be a widely applicable approach in the analysis of environmental monitoring data including ND.

Association Between Food and Drugs: Antimicrobial and Synergistic Activity of Annona muricata L.

Annona muricata L. is used in traditional medicine due its biological activities. This study analyzes the antimicrobial and synergistic activity of hydroalcoholic extract of the leaves of A. muricata. These activities were assayed using the microdilution method. The phytochemical prospection was based on tests observing substrate precipitations and color modifications. The hexane extract of Annona muricata showed the presence of several metabolites, mainly tannins, flavones, and flavonoids, all substances related with antimicrobial and modulatory activity. The extract demonstrated growth inhibition against the tested bacteria with minimal inhibitory concentration clinically irrelevant values of ≥1024 μg.mL−1. However, when combined with aminoglycosides, the extract enhanced the activity of antibiotics. A. muricata L., therefore, can be a promising source of products to control multiresistant bacteria.

Parallactic movement beats binocularity in the presence of external visual noise

Binocular vision provides a considerable advantage over monocular vision when stationary particles partly obstruct the view. Such situations occur in real life, e.g., when drivers are trying to identify objects through a windshield dotted with snowflakes. In the process of driving, any bumpiness of the road will bring about a parallactic movement of particles on the windshield with respect to the visual object. We investigated whether this parallactic movement diminishes the advantage of binocular over monocular vision. Using computer graphics, we simulated a driving situation with snowflakes represented by noise particles on the windshield. Ten observers tried to identify a Landolt ring (8 possible orintations, gap always 2.5 arcmin) presented for 2 s at a viewing distance of 2 m. The partly obstructing noise particles, either stationary or moving vertically at three sinusoidal velocities, were presented at a viewing distance of 0.8 m, corresponding to a stereodisparity well beyond Panum's fusional area. We compared the percentage of correct responses and the reaction time between binocular and monocular vision. When the 'snowflakes' were stationary, binocular vision yielded more correct responses than monocular vision (52.2 ± 1.8% vs 39.7 ± 1.7%). When the 'snowflakes' were moving, the task was much easier and the binocular advantage less pronounced (95.8 ± 1.4% vs 85.3 ± 5.2%). The reaction time with stationary noise was 1.25 s for binocular and 1.31 s for monocular vision. With moving noise, averaged over all three velocities, the reaction time was 1.23 s for binocular and 1.36 s for monocular vision. Parallactic movement of partly obstructing particles reduces the advantage of binocular over monocular vision to practically irrelevant values.

An Intelligent Approach to Assess Tacit Knowledge Fitness in Networked Enterprises

Many organizations attempt to form strategic networked enterprises, yet such strategies are difficult to implement because they are as likely to fail as to succeed. This failure is due to intangible differences and mismatches between partners in tacit knowledge (TK). Despite the various proposed partnership assessment models/tools in the literature, an immediate need exists for a new approach to measure the mismatch in TK across different organizations. This is due to the complex, vague, and uncertain nature of TK attributes. Hence, an instrument for measuring vagueness (imprecise), such as fuzzy linguistic variables, is needed. In this study, the author applies a neuro-fuzzy approach to assess TK fitness in networked enterprises. The results show how differences in TK between partners affect the networked enterprise’s performance. Furthermore, the assessment approach reveals the most significant values to adopt and the irrelevant values that must be abandoned to smooth the partnership formation. The proposed model can prevent unexpected conflicts between partners if managed properly.

Consommation des antibiotiques rapportée via les bilans standardisés de lutte contre les infections nosocomiales et relation avec l’ICATB

Objective The study's objective was to describe the evolution of antibiotic consumption between 2006 and 2008 in French health care facilities (HCF) its relations with the national policy of good antibiotics use using the ICATB score. Method Data from standardized reports on infection control activities collected from 2006 to 2008 by the Ministry of Health (antibiotic consumptions and elements of antibiotic stewardship of every HCF) were analyzed with linear regression models to multilevel random intercept adjusted on HCF characteristics (public or private) and activity. Results The analysis was performed on 4062 (48,2%) observations after exclusion of HCF not concerned by the ICATB public reporting indicator (7.2% of observations), invalid or missing data (21,2% of observations) and irrelevant values (23.4%). The global antibiotic consumption was 343 defined daily doses (DDD) per 1000 patient-days (PD) and varied little between 2006 and 2008. However, the linear regression model showed an increase of 5.7 DDD per 1000 PDs per year ( P < 0.001). There was a positive association between antibiotic consumption and ICATB score, mainly concerning sub-scores ICATB-action and ICATB-organization. Conclusion The recent lack of decrease in antibiotic consumption in French HCF between 2006 and 2008 is coherent with other available national data, but exclusion of more than 50% of observations limits the impact of this analysis. The relationship between policy of good use and consumption of antibiotics remain difficult to specify, because of the short (three years) study length and because of the nature of ICATB, a composite indicator assessing only partly antibiotic policies.

Count me in! On the automaticity of numerosity processing.

Extraction of numerosity (i.e., enumeration) is an essential component of mathematical abilities. The current study asked how automatic is the processing of numerosity and whether automatic activation is task dependent. Participants were presented with displays containing a variable number of digits and were asked to pay attention to the number of digits or to their numerical value, in separate blocks. Effects of task were tested with a comparative judgment task and a parity judgment task. In the comparative judgment task, participants had to indicate whether the numerosity or the numerical value of the digits was smaller or larger than 5. In the parity judgment task, participants had to indicate whether this value was odd or even. Irrelevant numerical values modulated performance regardless of task. In contrast, irrelevant numerosities modulated performance only in the comparative judgment task. These results suggest that numerical value is activated automatically, whereas activation of numerosity is modulated by task. We suggest that the differences observed are related to different cognitive and neural mechanisms recruited by these tasks.

GeoCache

GML is a promising model for integrating geodata within data warehouses. The resulting databases are generally large and require spatial operators to be handled. Depending on the size of the target geographical data and the number and complexity of operators in a query, the processing time may quickly become prohibitive. To optimize spatial queries over GML encoded data, this chapter introduces a novel cache-based architecture. A new cache replacement policy is then proposed. It takes into account the containment properties of geographical data and predicates, and allows evicting the most irrelevant values from the cache. Experiences with the GeoCache prototype show the effectiveness of the proposed architecture with the associated replacement policy, compared to existing works.

Pruning Decision Trees using Rules3 Inductive Learning Algorithm

One important disadvantage of decision tree based inductive learning algorithms is that they use some irrelevant values to establish the decision tree. This causes the final rule set to be less general. To overcome with this problem the tree has to be pruned. In this article using the recently developed RULES inductive learning algorithm, pruning of a decision tree is explained. The decision tree is extracted for an example problem using the ID3 algorithm and then is pruned using RULES. The results obtained before and after pruning are compared. This shows that the pruned decision tree is more general.

Hamiltonian structure and statistically relevant conserved quantities for the truncated Burgers‐Hopf equation

AbstractIn dynamical systems with intrinsic chaos, many degrees of freedom, and many conserved quantities, a fundamental issue is the statistical relevance of suitable subsets of these conserved quantities in appropriate regimes. The Galerkin truncation of the Burgers‐Hopf equation has been introduced recently as a prototype model with solutions exhibiting intrinsic stochasticity and a wide range of correlation scaling behavior that can be predicted successfully by simple scaling arguments. Here it is established that the truncated Burgers‐Hopf model is a Hamiltonian system with Hamiltonian given by the integral of the third power. This additional conserved quantity, beyond the energy, has been ignored in previous statistical mechanics studies of this equation. Thus, the question arises of the statistical significance of the Hamiltonian beyond that of the energy. First, an appropriate statistical theory is developed that includes both the energy and Hamiltonian. Then a convergent Monte Carlo algorithm is developed for computing equilibrium statistical distributions. The probability distribution of the Hamiltonian on a microcanonical energy surface is studied through the Monte‐Carlo algorithm and leads to the concept of statistically relevant and irrelevant values for the Hamiltonian. Empirical numerical estimates and simple analysis are combined to demonstrate that the statistically relevant values of the Hamiltonian have vanishingly small measure as the number of degrees of freedom increases with fixed mean energy. The predictions of the theory for relevant and irrelevant values for the Hamiltonian are confirmed through systematic numerical simulations. For statistically relevant values of the Hamiltonian, these simulations show a surprising spectral tilt rather than equipartition of energy. This spectral tilt is predicted and confirmed independently by Monte Carlo simulations based on equilibrium statistical mechanics together with a heuristic formula for the tilt. On the other hand, the theoretically predicted correlation scaling law is satisfied both for statistically relevant and irrelevant values of the Hamiltonian with excellent accuracy. The results established here for the Burgers‐Hopf model are a prototype for similar issues with significant practical importance in much more complex geophysical applications. Several interesting mathematical problems suggested by this study are mentioned in the final section. © 2002 Wiley Periodicals, Inc.

Putting adjustment back in the anchoring and adjustment heuristic: differential processing of self-generated and experimenter-provided anchors.

People's estimates of uncertain quantities are commonly influenced by irrelevant values. These anchoring effects were originally explained as insufficient adjustment away from an initial anchor value. The existing literature provides little support for the postulated process of adjustment, however, and a consensus that none takes place seems to be emerging. We argue that this conclusion is premature, and we present evidence that insufficient adjustment produces anchoring effects when the anchors are self-generated. In Study 1, participants' verbal reports made reference to adjustment only, from self-generated anchors. In Studies 2 and 3, participants induced to accept values by nodding their heads gave answers that were closer to an anchor (i.e., they adjusted less) than participants induced to deny values by shaking their heads--again, only when the anchor was self-generated. These results suggest it is time to reintroduce anchoring and adjustment as an explanation for some judgments under uncertainty.

Great divides: Deceptive distinctions and rhetorical strategies in the VMI and citadel cases

Legitimation for the maintenance of privilege is often made by rhetorical strategies that appeal to often irrelevant but favored values of a group. The case for the continuance of the exclusion of women at two revered state-supported militarystyle colleges, The Virginia Military Institute (VMI) (in Virginia) and the Citadel (in South Carolina), was made by those institutions and their lawyers and expert witnesses by appeals to “rationality” which encompass unsupported stereotyped views and references to the value of historical precedent and the status quo. The view that males and females are basically different with respect to cognitive and emotional characteristics is employed in the rhetoric. Thus, in these institutions and in some others today (e.g., a new single sex public school) sex segregation is offered as a benefit not only to males but to females, who are regarded as unable to learn well in coeducational environments. The article notes that assumptions about basic cognitive and emotional differences are deceptive and are not supported by empirical evidence, and that the studies cited by advocates of sex segregation are either impaired methodologically or are irrelevant today. The article also explores the way in which such values as diversity and states' rights are employed in the rationales for segregation.