scholarly journals Identification, Evaluation, and Classification of Building Failures

2021 ◽  
Author(s):  
◽  
William Alexander Porteous
Keyword(s):  
New Zealand ◽  
Professional Practice ◽  
Human Error ◽  
Legal Liability ◽  
New Work ◽  
Identification Evaluation

<p>The origin of this thesis was a long-standing interest in the performance of buildings in the years after completion, when the designers and builders have all moved onto the next new work. That interest grew as a result of conducting building surveys in the course of professional practice. The surveys often revealed incipient or actual building failures which required careful diagnosis to discover the cause, so that the failure could be prevented in future. For the knowledge gained from investigation and diagnosis to benefit the wider community, rather than merely the individuals concerned with one building, it became obvious that some system of objective and anonymous recording of the circumstances of each building failure was necessary. This thesis proposes a basis for identifying and evaluating building failures. Building failure is defined from the viewpoint of both the producer of the building and the user to ensure that it is the expectations of both that are considered when a building failure is being identified and evaluated. Identifying and evaluating building failures is a precursor to diagnosing the cause or causes of that failure. it is argued here that any evaluation of the causes of building failures must acknowledge the part played by natural causes as well as the part sometimes played by human error. It is also argued that placing emphasis on blame, and hence on legal liability, encourages universal denial of fault and works against the search for the truth. A system for classification of building failures by their causes is proposed as a means by which the knowledge gained from diagnosis of individual building failure events can be aggregated to reveal the pattern of failures in a sample of buildings. The results from applying the system of identifying, evaluating, and classifying building failures in a sample of New Zealand dwellings are presented. The main conclusion drawn from the work is that because natural causes are so difficult an influence to regulate, the best prospect for reducing the incidence of building failures is the avoidance of human error. Because human error can never be entirely discounted insurance against the risk of error is only wise. A second conclusion reached is that the proposed system of identifying, evaluating, and classifying building failures has been shown to produce useful results, even when the system has had only a written record from which to work.</p>

scholarly journals Identification, Evaluation, and Classification of Building Failures

2021 ◽  
Author(s):  
◽  
William Alexander Porteous
Keyword(s):  
New Zealand ◽  
Professional Practice ◽  
Human Error ◽  
Legal Liability ◽  
New Work ◽  
Identification Evaluation

<p>The origin of this thesis was a long-standing interest in the performance of buildings in the years after completion, when the designers and builders have all moved onto the next new work. That interest grew as a result of conducting building surveys in the course of professional practice. The surveys often revealed incipient or actual building failures which required careful diagnosis to discover the cause, so that the failure could be prevented in future. For the knowledge gained from investigation and diagnosis to benefit the wider community, rather than merely the individuals concerned with one building, it became obvious that some system of objective and anonymous recording of the circumstances of each building failure was necessary. This thesis proposes a basis for identifying and evaluating building failures. Building failure is defined from the viewpoint of both the producer of the building and the user to ensure that it is the expectations of both that are considered when a building failure is being identified and evaluated. Identifying and evaluating building failures is a precursor to diagnosing the cause or causes of that failure. it is argued here that any evaluation of the causes of building failures must acknowledge the part played by natural causes as well as the part sometimes played by human error. It is also argued that placing emphasis on blame, and hence on legal liability, encourages universal denial of fault and works against the search for the truth. A system for classification of building failures by their causes is proposed as a means by which the knowledge gained from diagnosis of individual building failure events can be aggregated to reveal the pattern of failures in a sample of buildings. The results from applying the system of identifying, evaluating, and classifying building failures in a sample of New Zealand dwellings are presented. The main conclusion drawn from the work is that because natural causes are so difficult an influence to regulate, the best prospect for reducing the incidence of building failures is the avoidance of human error. Because human error can never be entirely discounted insurance against the risk of error is only wise. A second conclusion reached is that the proposed system of identifying, evaluating, and classifying building failures has been shown to produce useful results, even when the system has had only a written record from which to work.</p>

A Comparison of Rule-Based and Machine Learning Models for Classification of Human Factors Aviation Safety Event Reports

2020 ◽  
Vol 64 (1) ◽  
pp. 129-133
Author(s):  
Katherine Darveau ◽  
Daniel Hannon ◽  
Chad Foster
Keyword(s):  
Machine Learning ◽  
Human Factors ◽  
Human Error ◽  
Data Science ◽  
Aircraft Engine ◽  
Rule Based ◽  
Root Cause ◽  
Textual Data ◽  
Safety Event

There is growing interest in the study and practice of applying data science (DS) and machine learning (ML) to automate decision making in safety-critical industries. As an alternative or augmentation to human review, there are opportunities to explore these methods for classifying aviation operational events by root cause. This study seeks to apply a thoughtful approach to design, compare, and combine rule-based and ML techniques to classify events caused by human error in aircraft/engine assembly, maintenance or operation. Event reports contain a combination of continuous parameters, unstructured text entries, and categorical selections. A Human Factors approach to classifier development prioritizes the evaluation of distinct data features and entry methods to improve modeling. Findings, including the performance of tested models, led to recommendations for the design of textual data collection systems and classification approaches.

AN EARLY CLASSIFICATION OF NEW ZEALAND COASTAL CLIMATES

1964 ◽  
Vol 16 (2) ◽  
pp. 6-10
Author(s):  
R. P. Hargreaves ◽  
W. J. Maunder
Keyword(s):  
New Zealand ◽  
Early Classification

scholarly journals Automated Negative Lightning Return Strokes Classification System

2021 ◽  
Vol 2107 (1) ◽  
pp. 012022
Author(s):  
F. Abdul Haris ◽  
M.Z.A. Ab Kadir ◽  
S. Sudin ◽  
D. Johari ◽  
J. Jasni ◽  
...  
Keyword(s):  
Classification System ◽  
Automatic System ◽  
Human Error ◽  
Processing Time ◽  
Visual Inspection ◽  
Automated System ◽  
Graphic User Interface ◽  
Data Comparison ◽  
Good Agreement

Abstract Over the years, many studies have been conducted to measure and classify the lightning-generated electric field waveform for a better understanding of the lightning physics phenomenon. Through measurement and classification, the features of the negative lightning return strokes can be accessed and analysed. In most studies, the classification of negative lightning return strokes was performed using a conventional approach based on manual visual inspection. Nevertheless, this traditional method could compromise the accuracy of data analysis due to human error, which also required a longer processing time. Hence, this study developed an automated negative lightning return strokes classification system using MATLAB software. In this study, a total of 115 return strokes was recorded and classified automatically by using the developed system. The data comparison with the Tenaga Nasional Berhad Research (TNBR) lightning report showed a good agreement between the lightning signal detected from this study with those signals recorded from the report. Apart from that, the developed automated system was successfully classified the negative lightning return strokes which this parameter was also illustrated on Graphic User Interface (GUI). Thus, the proposed automatic system could offer a practical and reliable approach by reducing human error and the processing time while classifying the negative lightning return strokes.

Royal Australian and New Zealand College of Psychiatrists professional practice guidelines for the administration of electroconvulsive therapy

2019 ◽  
Vol 53 (7) ◽  
pp. 609-623 ◽  
Author(s):  
Alan Weiss ◽  
Salam Hussain ◽  
Bradley Ng ◽  
Shanthi Sarma ◽  
John Tiller ◽  
...  
Keyword(s):  
Clinical Practice ◽  
New Zealand ◽  
Professional Practice ◽  
Electroconvulsive Therapy ◽  
Practice Guidelines ◽  
Best Practice ◽  
Scientific Evidence ◽  
Literature Information ◽  
Zealand College ◽  
Cognitive Side Effects

Objectives:To provide guidance for the optimal administration of electroconvulsive therapy, in particular maintaining the high efficacy of electroconvulsive therapy while minimising cognitive side-effects, based on scientific evidence and supplemented by expert clinical consensus.Methods:Articles and information were sourced from existing guidelines and the published literature. Information was revised and discussed by members of the working group of the Royal Australian and New Zealand College of Psychiatrists’ Section for Electroconvulsive Therapy and Neurostimulation, and findings were then formulated into consensus-based recommendations and guidance. The guidelines were subjected to rigorous successive consultation and external review within the Royal Australian and New Zealand College of Psychiatrists, involving the full Section for Electroconvulsive Therapy and Neurostimulation membership, and expert and clinical advisors and professional bodies with an interest in electroconvulsive therapy administration.Results:The Royal Australian and New Zealand College of Psychiatrists’ professional practice guidelines for the administration of electroconvulsive therapy provide up-to-date advice regarding the use of electroconvulsive therapy in clinical practice and are informed by evidence and clinical experience. The guidelines are intended for use by psychiatrists and also others with an interest in the administration of electroconvulsive therapy. The guidelines are not intended as a directive about clinical practice or instructions as to what must be done for a given patient, but provide guidance to facilitate best practice to help optimise outcomes for patients. The outcome is guidelines that strive to find the appropriate balance between promoting best evidence-based practice and acknowledging that electroconvulsive therapy is a continually evolving practice.Conclusion:The guidelines provide up-to-date advice for psychiatrists to promote optimal standards of electroconvulsive therapy practice.

scholarly journals O1A.6 The carcinogenicity of pesticides used in new zealand

2019 ◽  
Vol 76 (Suppl 1) ◽  
pp. A4.2-A4
Author(s):  
Andrea ‘t Mannetje
Keyword(s):  
New Zealand ◽  
Environmental Protection ◽  
Environmental Protection Agency ◽  
Agricultural Sector ◽  
Intervention Strategy ◽  
Epidemiological Studies ◽  
Regulatory Agencies ◽  
International Agency ◽  
Active Ingredients

IntroductionYearly over 3000 tonnes of pesticide active ingredients are applied in New Zealand agriculture. Since the 1980’s, epidemiological studies have reported increased risks of lymphopoietic cancers in agricultural sectors with high pesticide use. Here we aim to estimate the number and total volume of currently used pesticides in New Zealand that are known or suspected human carcinogens, in order to inform interventions.MethodsFor each of the pesticide active ingredients most commonly used in New Zealand, the carcinogenicity classification of three regulatory agencies (The New Zealand Environmental Protection Authority [NZ-EPA], the US Environmental Protection Agency [US-EPA], and the European Chemicals Agency [EU]) were extracted, as well as the classification of the International Agency for Research on Cancer (IARC) Monograph Programme. Total tonnes of active ingredients that are known or suspected human carcinogens was calculated for each classification.ResultsNone of the pesticides used in New Zealand are classified as known human carcinogens by any of the three regulatory agencies or IARC. Annually New Zealand uses 148–756 tonnes of active pesticide ingredients that are classified as suspected human carcinogens by the three regulatory agencies. If also including the pesticides classified by IARC as possible or probable human carcinogens, the upper estimate doubles to 1475 tonnes, representing half of the total volume of pesticide active ingredients used in New Zealand agriculture. The percentage and volume of active ingredients classified as suspected carcinogens by the three regulatory agencies was highest for the fungicides (8%–60%; 72–540 tonnes), followed by herbicides (3%–10%; 60–200 tonnes), and insecticides (8%, 16 tonnes).ConclusionsAlthough no known human carcinogens are used as pesticides, New Zealand’s high use of pesticides that are suspected carcinogens requires a greater awareness of the presence of potential carcinogens in the agricultural sector and the development of an intervention strategy to reduce cancer risk.

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