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Much research has been done to examine the relation between investors' human capital and their financial asset allocation. While some showed that the value of human capital should be taken into consideration to make financial asset allocation decisions on the composition of investing portfolios, most argued not. In this paper, we selected the monthly return of 9 industrial ETFs from June of 2007 to July 2011, used the present value of total future income as estimate of human capital, and relied on the Mean-Variance Optimal Asset Allocation framework to reexamine if human capital will impact investors optimal financial portfolios. Based on our tests, we found significant connection between human capital and risky asset allocation, which resulted in significant change to weights allocated to the risk assets to create a Mean-Variance optimal portfolio.

We investigate the power of voting among diverse, randomized software agents. With teams of computer Go agents in mind, we develop a novel theoretical model of two-stage noisy voting that builds on recent work in machine learning. This model allows us to reason about a collection of agents with different biases (determined by the first-stage noise models), which, furthermore, apply randomized algorithms to evaluate alternatives and produce votes (captured by the second-stage noise models). We analytically demonstrate that a uniform team, consisting of multiple instances of any single agent, must make a significant number of mistakes, whereas a diverse team converges to perfection as the number of agents grows. Our experiments, which pit teams of computer Go agents against strong agents, provide evidence for the effectiveness of voting when agents are diverse.

https://viurrspace.ca/bitstream/handle/10613/17324/Nov16-1898.pdf?sequence=2

Enunciados de examen de junio del curso 97/98. Parte de teoría (2ª semana).

Notaris saat ini diperbolehkan melakukan sertifikasi dokumen elektronik. Kewenangan ini termaktub dalam Pasal 15 ayat (3) Undang-Undang Nomor 2 Tahun 2014 Tentang Jabatan Notaris. Selain mengesahkan akta, notaris juga dapat menyimpan berkas dalam bentuk file. Namun, tidak sedikit notaris yang masih enggan menggunakan teknologi untuk membuat dan mengesahkan sebuah akta dikarenakan adanya pertentangan antar pasal baik dalam Undang-Undang Jabatan Notaris sendiri maupun dengan pasal dalam Undang-Undang lainnya. Penelitian ini bertujuan untuk mengetahui apakah akta yang menggunakan teknologi informatika memiliki kekuatan pembuktian layaknya akta autentik dan apakah sertifikasi elektronik yang dilakukan oleh notaris sejalan dengan tugas dan jabatan notaris. Metode penelitian yang digunakan yaitu jenis penelitian hukum normatif yang dilakukan dengan cara penelaahan bahan pustaka atau data sekunder dengan menggunakan pendekatan undang-undang dan pendekatan konseptual. Penelitian ini berfokus pada akta hasil Rapat Umum Pemegang Saham Luar Biasa PT. Lippo Karawaci. Tbk yang dilakukan melalui video konferensi pada tanggal 13 Oktober 2021. Adanya ketidaksepakatan dari beberapa pemegang saham atas sertifikasi yang dilakukan secara elektronik karena dinilai dapat membuat akta tersebut menjadi akta di bawah tangan. Selain adanya pertentangan antara pasal, hal ini juga disebabkan tidak adanya peraturan pelaksana terkait pembuatan akta melalui teknologi informasi (Cyber Notary) oleh notaris sehingga perlunya pengkajian ulang terhadap Undang-Undang terkait dan pembuatan peraturan pelaksana khusus cyber notary.

https://viurrspace.ca/bitstream/handle/10613/17327/Nov19-1898.pdf?sequence=2

The mid-Pliocene is a valuable time interval for investigating equilibrium climate at current atmospheric CO2 concentrations because atmospheric CO2 concentrations are thought to have been comparable to the current day and yet the climate and distribution of ecosystems were quite different. One intriguing, but not fully understood, feature of the early to mid-Pliocene climate is the amplified Arctic temperature response and its impact on Arctic ecosystems. Only the most recent models appear to correctly estimate the degree of warming in the Pliocene Arctic and validation of the currently proposed feedbacks is limited by scarce terrestrial records of climate and environment. Here we reconstruct the summer temperature and fire regime from a subfossil fen-peat deposit on west–central Ellesmere Island, Canada, that has been chronologically constrained using cosmogenic nuclide burial dating to 3.9+1.5/-0.5 Ma. The estimate for average mean summer temperature is 15.4±0.8 ∘C using specific bacterial membrane lipids, i.e., branched glycerol dialkyl glycerol tetraethers. This is above the proposed threshold that predicts a substantial increase in wildfire in the modern high latitudes. Macro-charcoal was present in all samples from this Pliocene section with notably higher charcoal concentration in the upper part of the sequence. This change in charcoal was synchronous with a change in vegetation that included an increase in abundance of fire-promoting Pinus and Picea. Paleo-vegetation reconstructions are consistent with warm summer temperatures, relatively low summer precipitation and an incidence of fire comparable to fire-adapted boreal forests of North America and central Siberia. To our knowledge, this site provides the northernmost evidence of fire during the Pliocene. It suggests that ecosystem productivity was greater than in the present day, providing fuel for wildfires, and that the climate was conducive to the ignition of fire during this period. The results reveal that interactions between paleo-vegetation and paleoclimate were mediated by fire in the High Arctic during the Pliocene, even though CO2 concentrations were similar to modern values.

https://viurrspace.ca/bitstream/handle/10613/16962/Mar24-1900.pdf?sequence=2

Juvenile Idiopathic Arthritis (JIA) is the most common rheumatic disease of childhood. Our objective is to predict the results of remission so that those children who are likely to experience poor remission outcomes could benefit from early aggressive treatment. Many classification techniques could provide either a binary prediction or an estimated probability of remission. However, parents would like to know more specifically about the remission outcomes of children similar to their own. In this project, we propose a supervised clustering method that provides this information. Inspired by the basic idea of supervised principal component analysis, we perform supervision by selecting and/or weighting explanatory variables differently depending on their associations with the class response. Our supervised clustering method is applied to JIA data and to data simulated with known properties. Our method is shown to be competitive with an existing supervised clustering method, classification trees and random forests in terms of out-of-sample misclassification rates.