Conciliar Infallibility and Error in the Thomistic Ecclesiology of St. Robert Bellarmine, S.J.

2021 ◽  
Vol 8 (2) ◽  
pp. 251-273
Author(s):  
Christian D. Washburn
Keyword(s):  
Sixteenth Century ◽  
General Council ◽  
Different Types ◽  
Historical Examination ◽  
Do So

Abstract In the sixteenth century, St. Robert Bellarmine (1542–1621) in his Disputationes de controversiis Christianae fidei adversus huius temporis haereticos defended the authority of the conciliar magisterium. Bellarmine, like other sixteenth-century Thomists, held that there were conditions under which God necessarily protects a general council from teaching error, but he did not deny that councils can and have erred. This article explains Bellarmine’s classification of the different types of councils. It also examines the conditions under which he believes that God necessarily protects a council from teaching error. It then discusses Bellarmine’s teaching on what kinds of councils can err and under what conditions a council can do so. Finally, the article will discuss his historical examination of various alleged conciliar errors.

On the different types of collective attacks in abstract argumentation: equivalence results for SETAFs

2020 ◽  
Vol 30 (5) ◽  
pp. 1063-1107
Author(s):  
Wolfgang Dvořák ◽  
Anna Rapberger ◽  
Stefan Woltran
Keyword(s):  
Abstract Argumentation ◽  
Actual Behaviour ◽  
Different Types ◽  
Do So

Abstract Argumentation frameworks with collective attacks are a prominent extension of Dung’s abstract argumentation frameworks, where an attack can be drawn from a set of arguments to another argument. These frameworks are often abbreviated as SETAFs. Although SETAFs have received increasing interest recently, a thorough study on the actual behaviour of collective attacks has not been carried out yet. In particular, the richer attack structure SETAFs provide can lead to different forms of redundant attacks, i.e. attacks that are subsumed by attacks involving less arguments. Also the notion of strong equivalence, which is fundamental in nonmonotonic formalisms to characterize equivalent replacements, has not been investigated for SETAFs so far. In this paper, we first provide a classification of different types of collective attacks and analyse for which semantics they can be proven redundant. We do so for eleven well-established abstract argumentation semantics. We then study how strong equivalence between SETAFs can be decided with respect to the considered semantics and also consider variants of strong equivalence. Our results show that removing redundant attacks in a suitable way provides direct means to characterize strong equivalence by syntactical equivalence of so-called kernels, thus generalizing well-known results on strong equivalence between Dung AFs.

Dual stain kit for the microscopic gram classification of ocular infection bacteria

1993 ◽  
Vol 51 ◽  
pp. 248-249
Author(s):  
Jacob S. Hanker ◽  
Dale N. Holdren ◽  
Kenneth L. Cohen ◽  
Beverly L. Giammara
Keyword(s):  
Contact Lenses ◽  
Ocular Infection ◽  
Gram Negative Bacteria ◽  
Gram Negative ◽  
Gram Staining ◽  
Ocular Infections ◽  
Different Types ◽  
Culture Positive ◽  
Increased Susceptibility

Keratitis and conjunctivitis (infections of the cornea or conjunctiva) are ocular infections caused by various bacteria, fungi, viruses or parasites; bacteria, however, are usually prominent. Systemic conditions such as alcoholism, diabetes, debilitating disease, AIDS and immunosuppressive therapy can lead to increased susceptibility but trauma and contact lens use are very important factors. Gram-negative bacteria are most frequently cultured in these situations and Pseudomonas aeruginosa is most usually isolated from culture-positive ulcers of patients using contact lenses. Smears for staining can be obtained with a special swab or spatula and Gram staining frequently guides choice of a therapeutic rinse prior to the report of the culture results upon which specific antibiotic therapy is based. In some cases staining of the direct smear may be diagnostic in situations where the culture will not grow. In these cases different types of stains occasionally assist in guiding therapy.

Explanatory Power for Medical Expert Systems: Studies in the Representation of Causal Relationships for Clinical Consultations

1982 ◽  
Vol 21 (03) ◽  
pp. 127-136 ◽  
Author(s):  
J. W. Wallis ◽  
E. H. Shortliffe
Keyword(s):  
Explanatory Power ◽  
Prototype System ◽  
Inference Rules ◽  
Medical Expert ◽  
Comprehensive Knowledge ◽  
Different Types ◽  
Medical Expert Systems ◽  
Explanation System ◽  
Systems Studies

This paper reports on experiments designed to identify and implement mechanisms for enhancing the explanation capabilities of reasoning programs for medical consultation. The goals of an explanation system are discussed, as is the additional knowledge needed to meet these goals in a medical domain. We have focussed on the generation of explanations that are appropriate for different types of system users. This task requires a knowledge of what is complex and what is important; it is further strengthened by a classification of the associations or causal mechanisms inherent in the inference rules. A causal representation can also be used to aid in refining a comprehensive knowledge base so that the reasoning and explanations are more adequate. We describe a prototype system which reasons from causal inference rules and generates explanations that are appropriate for the user.

THE SEC PREEMPTS THE ACCOUNTING PRINCIPLES BOARD IN 1965: THE CLASSIFICATION OF THE DEFERRED TAX CREDIT RELATING TO INSTALLMENT SALES

2007 ◽  
Vol 34 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Stephen A. Zeff
Keyword(s):  
Securities And Exchange Commission ◽  
Accounting Practice ◽  
Slow Pace ◽  
Accounting Principles ◽  
Private And Public ◽  
Deferred Tax ◽  
Accounting Procedure ◽  
The U.S ◽  
Do So

In 1959, the Accounting Principles Board (APB) replaced the Committee on Accounting Procedure because the latter was unable to deal forthrightly with a series of important issues. But during the APB's first half-dozen years, its record of achievement was no more impressive than its predecessor's. The chairman of the Securities and Exchange Commission (SEC), Manuel F. Cohen, criticized the APB's slow pace and unwillingness to tackle difficult issues. This article discusses the circumstances attending the SEC's issuance of an Accounting Series Release in late 1965 to demonstrate forcefully to the APB that, when it is unable to carry out its responsibility to “narrow the areas of difference” in accounting practice, the SEC is prepared to step in and do so itself. In this sense, the article deals with the tensions between the private and public sectors in the establishment of accounting principles in the U.S. during the mid-1960s. The article makes extensive use of primary resource materials in the author's personal archive, which have not been used previously in published work.

scholarly journals Deep Learning Methods for Classification of Certain Abnormalities in Echocardiography

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 495
Author(s):  
Imayanmosha Wahlang ◽  
Arnab Kumar Maji ◽  
Goutam Saha ◽  
Prasun Chakrabarti ◽  
Michal Jasinski ◽  
...  
Keyword(s):  
Deep Learning ◽  
Short Term Memory ◽  
Support Vector ◽  
Variational Autoencoder ◽  
Different Types ◽  
Static Images ◽  
Long Short Term Memory ◽  
2D And 3D ◽  
Better Than

This article experiments with deep learning methodologies in echocardiogram (echo), a promising and vigorously researched technique in the preponderance field. This paper involves two different kinds of classification in the echo. Firstly, classification into normal (absence of abnormalities) or abnormal (presence of abnormalities) has been done, using 2D echo images, 3D Doppler images, and videographic images. Secondly, based on different types of regurgitation, namely, Mitral Regurgitation (MR), Aortic Regurgitation (AR), Tricuspid Regurgitation (TR), and a combination of the three types of regurgitation are classified using videographic echo images. Two deep-learning methodologies are used for these purposes, a Recurrent Neural Network (RNN) based methodology (Long Short Term Memory (LSTM)) and an Autoencoder based methodology (Variational AutoEncoder (VAE)). The use of videographic images distinguished this work from the existing work using SVM (Support Vector Machine) and also application of deep-learning methodologies is the first of many in this particular field. It was found that deep-learning methodologies perform better than SVM methodology in normal or abnormal classification. Overall, VAE performs better in 2D and 3D Doppler images (static images) while LSTM performs better in the case of videographic images.

scholarly journals Preventing corneal blindness caused by keratitis using artificial intelligence

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhongwen Li ◽  
Jiewei Jiang ◽  
Kuan Chen ◽  
Qianqian Chen ◽  
Qinxiang Zheng ◽  
...  
Keyword(s):  
Early Diagnosis ◽  
Vision Loss ◽  
Learning System ◽  
Automated Classification ◽  
Slit Lamp ◽  
Resource Limited ◽  
The World ◽  
Different Types ◽  
Corneal Blindness

AbstractKeratitis is the main cause of corneal blindness worldwide. Most vision loss caused by keratitis can be avoidable via early detection and treatment. The diagnosis of keratitis often requires skilled ophthalmologists. However, the world is short of ophthalmologists, especially in resource-limited settings, making the early diagnosis of keratitis challenging. Here, we develop a deep learning system for the automated classification of keratitis, other cornea abnormalities, and normal cornea based on 6,567 slit-lamp images. Our system exhibits remarkable performance in cornea images captured by the different types of digital slit lamp cameras and a smartphone with the super macro mode (all AUCs>0.96). The comparable sensitivity and specificity in keratitis detection are observed between the system and experienced cornea specialists. Our system has the potential to be applied to both digital slit lamp cameras and smartphones to promote the early diagnosis and treatment of keratitis, preventing the corneal blindness caused by keratitis.

NEURAL CLASSIFICATION OF MASS ABNORMALITIES WITH DIFFERENT TYPES OF FEATURES IN DIGITAL MAMMOGRAPHY

2006 ◽  
Vol 06 (01) ◽  
pp. 61-75 ◽  
Author(s):  
R. PANCHAL ◽  
B. VERMA
Keyword(s):  
Breast Cancer ◽  
Research Work ◽  
Breast Cancer Diagnosis ◽  
Classification Rate ◽  
Test Dataset ◽  
Benchmark Database ◽  
Different Types ◽  
Breast Tissues ◽  
Mass Type

Early detection of breast abnormalities remains the primary prevention against breast cancer despite the advances in breast cancer diagnosis and treatment. Presence of mass in breast tissues is highly indicative of breast cancer. The research work presented in this paper investigates the significance of different types of features using proposed neural network based classification technique to classify mass type of breast abnormalities in digital mammograms into malignant and benign. 14 gray level based features, four BI-RADS features, patient age feature and subtlety value feature have been explored using the proposed research methodology to attain maximum classification on test dataset. The proposed research technique attained a 91% testing classification rate with a 100% training classification rate on digital mammograms taken from the DDSM benchmark database.

Regulating for Content on the Internet: Meeting Cultural and Social Objectives for Broadband

2001 ◽  
Vol 101 (1) ◽  
pp. 19-31 ◽  
Author(s):  
Gerard Goggin ◽  
Catherine Griff
Keyword(s):  
The Internet ◽  
Final Report ◽  
Media Convergence ◽  
Different Types ◽  
The Future ◽  
Broadcasting Regulation ◽  
Productivity Commission ◽  
Specific Regulation ◽  
Film And Video ◽  
Do So

Much of the present debate about content on the internet revolves around how to control the distribution of different sorts of harmful or undesirable material. Yet there are considerable issues about whether sufficient sorts of desired cultural content will be available, such as ‘national’, ‘Australian’ content. In traditional broadcasting, regulation has been devised to encourage or mandate different types of content, where it is believed that the market will not do so by itself. At present, such regulatory arrangements are under threat in television, as the Productivity Commission Broadcasting Inquiry final report has noted. But what of the future for certain types of content on the internet? Do we need specific regulation and policy to promote the availability of content on the internet? Or is such a project simply irrelevant in the context of gradual but inexorable media convergence? Is regulating for content just as quixotic and fraught with peril as regulating of content from a censorship perspective often appears to be? In this article, we consider the case of Australian content for broadband technologies, especially in relation to film and video, and make some preliminary observations on the promotion and regulation of internet content.

scholarly journals Space Precession Target Classification Based on Radar High-Resolution Range Profiles

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Yizhe Wang ◽  
Cunqian Feng ◽  
Yongshun Zhang ◽  
Sisan He
Keyword(s):  
Parameter Extraction ◽  
Classification Performance ◽  
Support Vector ◽  
Electromagnetic Data ◽  
Feature Extractor ◽  
Different Types ◽  
Radar Echo ◽  
High Level ◽  
Cone Target

Precession is a common micromotion form of space targets, introducing additional micro-Doppler (m-D) modulation into the radar echo. Effective classification of space targets is of great significance for further micromotion parameter extraction and identification. Feature extraction is a key step during the classification process, largely influencing the final classification performance. This paper presents two methods for classifying different types of space precession targets from the HRRPs. We first establish the precession model of space targets and analyze the scattering characteristics and then compute electromagnetic data of the cone target, cone-cylinder target, and cone-cylinder-flare target. Experimental results demonstrate that the support vector machine (SVM) using histograms of oriented gradient (HOG) features achieves a good result, whereas the deep convolutional neural network (DCNN) obtains a higher classification accuracy. DCNN combines the feature extractor and the classifier itself to automatically mine the high-level signatures of HRRPs through a training process. Besides, the efficiency of the two classification processes are compared using the same dataset.

Lexicographer’s Lacunas or How to Deal with Missing Representative Dictionary Forms on the Example of Czech

2019 ◽  
Author(s):  
Dominika Kováříková ◽  
Michal Škrabal ◽  
Václav Cvrček ◽  
Lucie Lukešová ◽  
Jiří Milička
Keyword(s):  
Grammatical Category ◽  
Manual Analysis ◽  
Different Types ◽  
Word Forms ◽  
Frequency Threshold

Abstract When compiling a list of headwords, every lexicographer comes across words with an unattested representative dictionary form in the data. This study focuses on how to distinguish between the cases when this form is missing due to a lack of data and when there are some systemic or linguistic reasons. We have formulated lexicographic recommendations for different types of such ‘lacunas’ based on our research carried out on Czech written corpora. As a prerequisite, we calculated a frequency threshold to find words that should have the representative form attested in the data. Based on a manual analysis of 2,700 nouns, adjectives and verbs that do not, we drew up a classification of lacunas. The reasons for a missing dictionary form are often associated with limited collocability and non-preference for the representative grammatical category. Findings on unattested word forms also have significant implications for language potentiality.

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