title: The validity of exemption clauses in contract law: Cases, rules, legislation intervention and implications

authors: Liao, Zhixiong (Leo)

subjects: Contract

abstract: Exclusion or limitation of liability clauses are commonly seen nowadays in online contracts. This paper analyses the validity of exemption clauses in a variety of circumstances comparing the cases and legislation in different jurisdictions. It submits that in determining whether such exemption clauses are valid and enforceable, the law and the Courts have to balance the competing public policies between upholding freedom of contracts on the one hand and fairness and protection of consumers on the other.

text: The validity of exemption clauses in contract law: Cases, rules, legislation intervention and implications Exclusion or limitation of liability clauses are commonly seen nowadays in online contracts. This paper analyses the validity of exemption clauses in a variety of circumstances comparing the cases and legislation in different jurisdictions. It submits that in determining whether such exemption clauses are valid and enforceable, the law and the Courts have to balance the competing public policies between upholding freedom of contracts on the one hand and fairness and protection of consumers on the other.

year: 2021

title: Accurate photometric redshift probability density estimation - method comparison and application

authors: Rau, Michael M.

subjects: galaxies

abstract: We introduce an ordinal classification algorithm for photometric redshift estimation, which significantly improves the reconstruction of photometric redshift probability density functions (PDFs) for individual galaxies and galaxy samples. As a use case we apply our method to CFHTLS galaxies. The ordinal classification algorithm treats distinct redshift bins as ordered values, which improves the quality of photometric redshift PDFs, compared with non-ordinal classification architectures. We also propose a new single value point estimate of the galaxy redshift, that can be used to estimate the full redshift PDF of a galaxy sample. This method is competitive in terms of accuracy with contemporary algorithms, which stack the full redshift PDFs of all galaxies in the sample, but requires orders of magnitudes less storage space. 
The methods described in this paper greatly improve the log-likelihood of individual object redshift PDFs, when compared with a popular Neural Network code (ANNz). In our use case, this improvement reaches 50% for high redshift objects (z ≥ 0.75). 
We show that using these more accurate photometric redshift PDFs will lead to a reduction in the systematic biases by up to a factor of four, when compared with less accurate PDFs obtained from commonly used methods. The cosmological analyses we examine and find improvement upon are the following: gravitational lensing cluster mass estimates, modelling of angular correlation functions, and modelling of cosmic shear correlation functions.

text: Accurate photometric redshift probability density estimation - method comparison and application We introduce an ordinal classification algorithm for photometric redshift estimation, which significantly improves the reconstruction of photometric redshift probability density functions (PDFs) for individual galaxies and galaxy samples. As a use case we apply our method to CFHTLS galaxies. The ordinal classification algorithm treats distinct redshift bins as ordered values, which improves the quality of photometric redshift PDFs, compared with non-ordinal classification architectures. We also propose a new single value point estimate of the galaxy redshift, that can be used to estimate the full redshift PDF of a galaxy sample. This method is competitive in terms of accuracy with contemporary algorithms, which stack the full redshift PDFs of all galaxies in the sample, but requires orders of magnitudes less storage space. 
The methods described in this paper greatly improve the log-likelihood of individual object redshift PDFs, when compared with a popular Neural Network code (ANNz). In our use case, this improvement reaches 50% for high redshift objects (z ≥ 0.75). 
We show that using these more accurate photometric redshift PDFs will lead to a reduction in the systematic biases by up to a factor of four, when compared with less accurate PDFs obtained from commonly used methods. The cosmological analyses we examine and find improvement upon are the following: gravitational lensing cluster mass estimates, modelling of angular correlation functions, and modelling of cosmic shear correlation functions.

year: 2015

title: Te Tikanga me nga Kawa

authors: Temara, Pou

subjects: Tikanga

abstract: Ko te tikanga te kaitohu i te huarahi tika e pai ai te whakahaere a te Māori i a ia anō. Ki te kore he tikanga e kore e pai tāna noho, ka mate tōna mauri, te mutunga atu ko tōna toiora ka mate. Ki te kore he tikanga, ka  tūtakarerewa te kāhui. He pērā anō te kawa. Ki te kore he kawa, ko taua āhua anō o te pāihiihi o te whakaaro, ko te noho i roto o te kōpā, te mutunga atu ko te pakanga. Engari he nui ngā pōhēhētanga mō te tikanga me te kawa. Ko ētahi tohunga e kī ana he tapu kē atu te kawa i te tikanga, ko ētahi anō e tohe ana mō te tapu o te tikanga. He tohunga anō e kōkiri ana i te haumanutanga o te tikanga me te tāharaharatanga o te kawa. Kai tēnei tuhinga e takoto ai ngā whakamārama mō te tikanga me te kawa me te rerekētanga o tētahi i tētahi.

text: Te Tikanga me nga Kawa Ko te tikanga te kaitohu i te huarahi tika e pai ai te whakahaere a te Māori i a ia anō. Ki te kore he tikanga e kore e pai tāna noho, ka mate tōna mauri, te mutunga atu ko tōna toiora ka mate. Ki te kore he tikanga, ka  tūtakarerewa te kāhui. He pērā anō te kawa. Ki te kore he kawa, ko taua āhua anō o te pāihiihi o te whakaaro, ko te noho i roto o te kōpā, te mutunga atu ko te pakanga. Engari he nui ngā pōhēhētanga mō te tikanga me te kawa. Ko ētahi tohunga e kī ana he tapu kē atu te kawa i te tikanga, ko ētahi anō e tohe ana mō te tapu o te tikanga. He tohunga anō e kōkiri ana i te haumanutanga o te tikanga me te tāharaharatanga o te kawa. Kai tēnei tuhinga e takoto ai ngā whakamārama mō te tikanga me te kawa me te rerekētanga o tētahi i tētahi.

year: 2011