To be good conversational partners, natural language processing (NLP) systems should be trained to produce contextually useful utterances. Prior work has investigated training NLP systems with communication-based objectives, where a neural listener s
tands in as a communication partner. However, these systems commonly suffer from semantic drift where the learned language diverges radically from natural language. We propose a method that uses a population of neural listeners to regularize speaker training. We first show that language drift originates from the poor uncertainty calibration of a neural listener, which makes high-certainty predictions on novel sentences. We explore ensemble- and dropout-based populations of listeners and find that the former results in better uncertainty quantification. We evaluate both population-based objectives on reference games, and show that the ensemble method with better calibration enables the speaker to generate pragmatic utterances while scaling to a large vocabulary and generalizing to new games and listeners.
Framing has significant but subtle effects on public opinion and policy. We propose an NLP framework to measure entity-centric frames. We use it to understand media coverage on police violence in the United States in a new Police Violence Frames Corp
us of 82k news articles spanning 7k police killings. Our work uncovers more than a dozen framing devices and reveals significant differences in the way liberal and conservative news sources frame both the issue of police violence and the entities involved. Conservative sources emphasize when the victim is armed or attacking an officer and are more likely to mention the victim's criminal record. Liberal sources focus more on the underlying systemic injustice, highlighting the victim's race and that they were unarmed. We discover temporary spikes in these injustice frames near high-profile shooting events, and finally, we show protest volume correlates with and precedes media framing decisions.
The purpose of this report is to determine the effectiveness of using shear walls with Moment-resisting frames by modeling two bare frame structures. The first model is a combination of bare frames and shear walls, and the second model is without she
ar walls, and analyzing them statically (LATERAL FORCE METHOD) and dynamically (RESPONSE SPECTRUM METHOD) using ETABS 2016 software, and comparing the results of base shear forces, displacements and vibration modes, in order to form a comprehensive understanding of the proper use of shear walls.
The report raises critical questions regarding the key factors of resisting seismic forces on similar structures, where rigidity or ductility can play opposing roles in the overall structure resistance.
Plastic and rubber products considered of being a great importance to humans, but
their residues and wastes are a real environmental disaster. They are dumped in fields,
streams and forests or buried in large landfills that pose a serious hazard th
at needs to work
on solve it in the best possible way.
On the other hand, the economic problems caused by the erosion of concrete cement
have made it the major problem of infrastructure in the industrialized countries. Over the
past three decades, this problem has reached alarming proportions, which led to high repair
costs, whether in concrete or in reinforcing steel, Especially acidic media due to concrete
permeability of acid rainwater, where these costs exceeded initial construction amounts in
some cases.
This paper deals with the recycling of used tires and some types of plastic waste to
be used in the preparation of insulating materials for water and heat at a low cost compared
to the insulation materials currently used in the construction process, in addition to the
preparation of floor tiles for internal and external use.
