Search

found 23 results

Images for machines; more images...

Images, UC QuakeStudies

A digitally manipulated image of a high-reach excavator demolishing a building. The photographer comments, "After the earthquakes in Christchurch, New Zealand the demolition of most of the City Centre began. After two years the government thought that the progress was far too slow, so began the start of the automatic demolition. Luckily when the solar powered demolition machines started to cause indiscriminate death and destruction they were isolated to the South Island and unable to cross the seas".

Research Papers, Lincoln University

After 160 years of colonial settlement, Christchurch has recently experienced a sequence of devastating earthquakes and seen the need for a widespread de- and re-construction of the central city, as well as, many of the surrounding neighbourhoods and peri-urban satellite settlements. This paper will offer a view of the opportunities and restrictions to the post-earthquake re-development of Christchurch as informed by ‘growth machine’ theory. A case study investigating an illegal dump in central Christchurch will be used to assess the applicability of growth machine theory to the current disaster response.

Images, Canterbury Museum

One red and black fabric quilt comprised of pieced and appliquéd block work with both hand and machine stitching; machine quilted with embellishments and a one piece bordered back; an image of the ChristChurch Cathedral is in the centre and features pen work. Designed and quilted by the Coast Quilters of Whangaroa from fabric sent in by listener...

Research papers, University of Canterbury Library

Unreinforced masonry (URM) structures comprise a majority of the global built heritage. The masonry heritage of New Zealand is comparatively younger to its European counterparts. In a country facing frequent earthquakes, the URM buildings are prone to extensive damage and collapse. The Canterbury earthquake sequence proved the same, causing damage to over _% buildings. The ability to assess the severity of building damage is essential for emergency response and recovery. Following the Canterbury earthquakes, the damaged buildings were categorized into various damage states using the EMS-98 scale. This article investigates machine learning techniques such as k-nearest neighbors, decision trees, and random forests, to rapidly assess earthquake-induced building damage. The damage data from the Canterbury earthquake sequence is used to obtain the forecast model, and the performance of each machine learning technique is evaluated using the remaining (test) data. On getting a high accuracy the model is then run for building database collected for Dunedin to predict expected damage during the rupture of the Akatore fault.

Research papers, University of Canterbury Library

After a high-intensity seismic event, inspections of structural damages need to be carried out as soon as possible in order to optimize the emergency management, as well as improving the recovery time. In the current practice, damage inspections are performed by an experienced engineer, who physically inspect the structures. This way of doing not only requires a significant amount of time and high skilled human resources, but also raises the concern about the inspector’s safety. A promising alternative is represented using new technologies, such as drones and artificial intelligence, which can perform part of the damage classification task. In fact, drones can safely access high hazard components of the structures: for instance, bridge piers or abutments, and perform the reconnaissance by using highresolution cameras. Furthermore, images can be automatically processed by machine learning algorithms, and damages detected. In this paper, the possibility of applying such technologies for inspecting New Zealand bridges is explored. Firstly, a machine-learning model for damage detection by performing image analysis is presented. Specifically, the algorithm was trained to recognize cracks in concrete members. A sensitivity analysis was carried out to evaluate the algorithm accuracy by using database images. Depending on the confidence level desired,i.e. by allowing a manual classification where the alghortim confidence is below a specific tolerance, the accuracy was found reaching up to 84.7%. In the second part, the model is applied to detect the damage observed on the Anzac Bridge (GPS coordinates -43.500865, 172.701138) in Christchurch by performing a drone reconnaissance. Reults show that the accuracy of the damage detection was equal to 88% and 63% for cracking and spalling, respectively.

Research papers, University of Canterbury Library

The Canterbury Earthquake Sequence (CES), induced extensive damage in residential buildings and led to over NZ$40 billion in total economic losses. Due to the unique insurance setting in New Zealand, up to 80% of the financial losses were insured. Over the CES, the Earthquake Commission (EQC) received more than 412,000 insurance claims for residential buildings. The 4 September 2010 earthquake is the event for which most of the claims have been lodged with more than 138,000 residential claims for this event only. This research project uses EQC claim database to develop a seismic loss prediction model for residential buildings in Christchurch. It uses machine learning to create a procedure capable of highlighting critical features that affected the most buildings loss. A future study of those features enables the generation of insights that can be used by various stakeholders, for example, to better understand the influence of a structural system on the building loss or to select appropriate risk mitigation measures. Previous to the training of the machine learning model, the claim dataset was supplemented with additional data sourced from private and open access databases giving complementary information related to the building characteristics, seismic demand, liquefaction occurrence and soil conditions. This poster presents results of a machine learning model trained on a merged dataset using residential claims from the 4 September 2010.

Images, Canterbury Museum

One black wristband with the words ‘Band 4 Hope’ machine inscribed. These wristbands were designed as a fundraiser following the 22 February 2011 earthquake. This wristband was left as a tribute at the Canterbury Television (CTV) building which collapsed during the 22 February 2011 earthquake killing 115 people. It is one of three identical bla...

Images, Canterbury Museum

One black wristband with the words ‘Band 4 Hope’ machine inscribed. These wristbands were designed as a fundraiser following the 22 February 2011 earthquake. This wristband was left as a tribute at the Canterbury Television (CTV) building which collapsed during the 22 February 2011 earthquake killing 115 people. It is one of three identical bla...

Images, Canterbury Museum

One black wristband with the words ‘Band 4 Hope’ machine inscribed. These wristbands were designed as a fundraiser following the 22 February 2011 earthquake. This wristband was left as a tribute at the Canterbury Television (CTV) building which collapsed during the 22 February 2011 earthquake killing 115 people. It is one of three identical bla...

Images, Canterbury Museum

One red wristband with the words ‘Band 4 Hope’ machine inscribed. These wristbands were designed as a fundraiser following the 22 February 2011 earthquake. This wristband was left as a tribute at the Canterbury Television (CTV) building which collapsed during the 22 February 2011 earthquake killing 115 people. It is the only red wristband left ...

Images, UC QuakeStudies

A digitally manipulated image of furniture and machinery. The photographer comments, "This furniture restoration company got caught in the middle of the Christchurch earthquake and lost a whole wall. After constant exposure to the elements everything now needs a bit of restoration. They are now working in a different part of Christchurch, but their past can still be seen".

Images, UC QuakeStudies

Two workers inspect fuses placed in an embankment during reinforcement work. The photographer comments, "This is the reinforcing of an embankment in the port of Lyttelton, which partly collapsed in the Christchurch earthquakes. They are using the same equipment as used for blowing up rock faces to mend them".

Videos, UC QuakeStudies

A video of an interview with John Turner, owner of Ambience Tiling, about the restoration of the tiles in New Regent Street. Turner talks about working with SCE Stone & Design, who sent the sample tiles to China where they were machine replicated. The tiles took six to eight weeks to arrive, with about 10,500 new tiles produced. The video also includes an interview with Iain Taylor, a tiler at Ambience Tiling, about the retiling process.

Images, Alexander Turnbull Library

The title is 'Gambling on the rise in Christchurch'. Several vignettes show two men running in the 'Porta-loo stakes (runs)'; people betting on the 'size of the next shake'; people betting on 'who will have the last chimney standing'; a man sitting over a pot on a little gas ring wondering 'How long will it take to boil a 3 minute egg... when it's minus 10 in the kitchen'; someone in a car wondering 'Whose street can wipe out the most engine sumps'; and someone wondering 'Which power company will be first to put people before profits'. Context: The way of things following the earthquakes of September 4 2010, 22 February 2011 and 13 June 2011. The Problem Gambling Foundation says it is concerned more Christchurch people are turning to gambling to combat stress from earthquakes. It says spending on pokie machines in Christchurch has risen by almost $4 million, going against a downward national trend. The foundation says the data released by the Department of Internal Affairs shows spending on gaming machines rose by more than $3,800,000 in Christchurch city to almost $23 million. (Radio NZ News 26 July 2011) Colour and black and white versions available Quantity: 2 digital cartoon(s).

Audio, Radio New Zealand

A review of the week's news including... the former wife of a highly regarded Maori community leader who died in 2016 says she has passed on to Police the names of people she believes may have been involved in, or have knowledge of, what she's calling a paedophile sex ring involving her former husband, Peters on Trump, Wellington's new bus fleet hits the streets, more details of plans to cut jobs at the national museum, anti-gambling groups want poker machines included in a crackdown on money laundering, the worst winter for moteliers since the Canterbury earthquakes and who's to blame?, a statue on Bastion Point that could be as big as the Statue of Liberty and what happens when RNZ meets thrash metal?

Images, Alexander Turnbull Library

Shows Minister for Christchurch Earthquake Recovery Gerry Brownlee delighted with his plan to rebuild Christchurch and to have it paid for buy the PM's casino. Context: Refers to the Christchurch Central Development Unit that Minister for Christchurch Earthquake Recovery Gerry Brownlee has put in place. Refers also to the very controversial deal that Prime Minister John Key has made with Auckland's SkyCity to the effect that SkyCity will pay the full construction cost of a new convention centre - estimated at $350 million, in return for being allowed to add more gaming tables and machines, and extending its licence beyond 2021. Colour and black and white versions of this cartoon are available Quantity: 2 digital cartoon(s).

Images, Alexander Turnbull Library

The cartoon shows a monstrous machine with an enormous crushing ball attached to a giant crane. It moves past a signpost that points towards Christchurch. A man watches and tells his friend 'Gerry Brownlee borrowed it from Auckland! Context - Brownlee has caused a stir by suggesting that if he had his way some of Christchurch's older buildings would be "down tomorrow". He also said the price of saving some historic buildings badly damaged in the February 22 earthquake was too high. People had died in the quake because of attempts to save historic buildings badly damaged in the September 4 quake. Brownlee said he had no regrets despite the stir his comments caused - but he was annoyed by suggestions the Cathedral and Riccarton House were among buildings he thought should be bowled. He believed those buildings should be saved, and they would be. "I'm not a philistine; I was chairman of the trust that actually saved Riccarton House from the bulldozers in 1990. "I understand conservation architecture very well and I do have an appreciation of heritage buildings." Colour and black and white versions available Quantity: 2 digital cartoon(s).

Research papers, University of Canterbury Library

High-quality ground motion records are required for engineering applications including response history analysis, seismic hazard development, and validation of physics-based ground motion simulations. However, the determination of whether a ground motion record is high-quality is poorly handled by automation with mathematical functions and can become prohibitive if done manually. Machine learning applications are well-suited to this problem, and a previous feed-forward neural network was developed (Bellagamba et al. 2019) to determine high-quality records from small crustal events in the Canterbury and Wellington regions for simulation validation. This prior work was however limited by the omission of moderate-to-large magnitude events and those from other tectonic environments, as well as a lack of explicit determination of the minimum usable frequency of the ground motion. To address these shortcomings, an updated neural network was developed to predict the quality of ground motion records for all magnitudes and all tectonic sources—active shallow crustal, subduction intraslab, and subduction interface—in New Zealand. The predictive performance of the previous feed-forward neural network was matched by the neural network in the domain of small crustal records, and this level of predictive performance is now extended to all source magnitudes and types in New Zealand making the neural network applicable to global ground motion databases. Furthermore, the neural network provides quality and minimum usable frequency predictions for each of the three orthogonal components of a record which may then be mapped into a binary quality decision or otherwise applied as desired. This framework provides flexibility for the end user to predict high-quality records with various acceptability thresholds allowing for this neural network to be used in a range of applications.

Audio, Radio New Zealand

DAVID SHEARER to the Prime Minister: Does he stand by all his statements? PAUL GOLDSMITH to the Minister of Finance: What reports has he received on the performance of the public service? Dr RUSSEL NORMAN to the Prime Minister: Does he stand by his statement about asset sales that it was the Governments intention that “every New Zealander who wants shares gets them”? SIMON O'CONNOR to the Minister for Tertiary Education, Skills and Employment: What progress has been made in expanding the Youth Guarantee Scheme to provide more 16 and 17 year-olds with fees-free tertiary training this year? Hon DAVID CUNLIFFE to the Minister for Economic Development: Does he stand by his statement that “the global financial crisis and the Canterbury earthquakes were not projected in any of those forecasts”? Rt Hon WINSTON PETERS to the Minister of Local Government: Has he been in communication with the Auckland Council over financial management issues, and if so, on what occasions this year? MIKE SABIN to the Minister for Social Development: How will the Government’s recently announced changes target young people not in education, employment or training? DENISE ROCHE to the Prime Minister: Does he stand by his comment that the Government has a “sinking lid policy” for pokie machines? Hon CLAYTON COSGROVE to the Minister of Finance: Does he stand by the statement made on his behalf in answer to Oral Question No 1 on 1 March 2012, that “I do know what is in the coalition agreement” and, if so, does he agree that the United Future-National confidence and supply agreement does not require United Future to vote for the Government’s asset sales legislation? TODD McCLAY to the Associate Minister of Conservation: What benefits will the Game Animal Council Bill bring for recreational hunters? Hon ANNETTE KING to the Minister of Housing: What response has he received to the “Smarter. Faster. Fairer” tenancy service which provides an 0800 phone customer service centre response to people with housing needs? JAMI-LEE ROSS to the Minister for ACC: What initiatives are underway to help raise awareness about falls in the home?