Geospatial data of the building stock is essential in many domains pertaining to the built
environment. These datasets are often provided by governments, but crowdsourcing them …

The advance of Machine Learning (ML) has led to a strong interest in this technology to
support decision making. While complex ML models provide predictions that are often more …

Acquiring spatial data of fine and dynamic urban features such as buildings remains
challenging. This paper brings attention to real estate advertisements and property sales …

As our world becomes increasingly urbanized, smart cities are leading the way in using
technology to create more efficient, connected, and sustainable environments. However …

Numerous countries have adopted electricity market liberalization for residential consumers.
Although the benefits of the free market are notorious, when this opening refers to the …

Background In recent years the generation of antibodies by recombinant methods, such as
phage display technology, has increased the speed by which antibodies can be obtained …

Characteristics of ambient data and classical business data; the goal of this work is to
investigate how machine learning can be used to harness ambient data in business …

Forecasting electricity demand plays a critical role in ensuring reliable and cost-efficient
operation of the electricity supply. With the global transition to distributed renewable energy …

The government's role in providing social assistance to reduce poverty has been going very
well. However, in practice, there are obstacles to collecting and verifying data on prospective …

In an attempt to channel sales activities, companies often focus on 'high value targets' that
offer attractive prospective returns. In liberalized electricity markets, commercial customers …