Recent successes in deep generative modeling have led to significant advances in natural language generation (NLG). Incorporating entities into neural generation models has demonstrated great improvements by assisting to infer the summary topic and t
o generate coherent content. To enhance the role of entity in NLG, in this paper, we aim to model the entity type in the decoding phase to generate contextual words accurately. We develop a novel NLG model to produce a target sequence based on a given list of entities. Our model has a multi-step decoder that injects the entity types into the process of entity mention generation. Experiments on two public news datasets demonstrate type injection performs better than existing type embedding concatenation baselines.
Ever since neural models were adopted in data-to-text language generation, they have invariably been reliant on extrinsic components to improve their semantic accuracy, because the models normally do not exhibit the ability to generate text that reli
ably mentions all of the information provided in the input. In this paper, we propose a novel decoding method that extracts interpretable information from encoder-decoder models' cross-attention, and uses it to infer which attributes are mentioned in the generated text, which is subsequently used to rescore beam hypotheses. Using this decoding method with T5 and BART, we show on three datasets its ability to dramatically reduce semantic errors in the generated outputs, while maintaining their state-of-the-art quality.
Most existing methods for automatic fact-checking start with a precompiled list of claims to verify. We investigate the understudied problem of determining what statements in news articles are worthy to fact-check. We annotate the argument structure
of 95 news articles in the climate change domain that are fact-checked by climate scientists at climatefeedback.org. We release the first multi-layer annotated corpus for both argumentative discourse structure (argument types and relations) and for fact-checked statements in news articles. We discuss the connection between argument structure and check-worthy statements and develop several baseline models for detecting check-worthy statements in the climate change domain. Our preliminary results show that using information about argumentative discourse structure shows slight but statistically significant improvement over a baseline of local discourse structure.
Arabic grammar has origins and rules that grammarians have worked out
and adjusted. This research deals with an issue of Arabic grammar which is
the issue of 'Appreciation'.
This research seeks mainly to clarify the concept of appreciation and how
grammarians defined it.
In this research, we are studying the possibility of contribution in solving the Vehicle
Routing Problem with Time Windows(VRPTW),that is one of the optimization problems
of the NP-hard type.
Moreover, Hybrid algorithm (HA) provided that integrate
s between Tabu Search
Algorithm and Guided Local Search algorithm And existence 2- Opt Local Search, based
on the savings algorithm in terms of continued of a particular objective to provide a lot of
savings. As we will compare the presented approach with standard tests to demonstrate
the efficiency, and their impact on the quality of the solution in terms of speed of
convergence and the ability to find better solutions.
In this research, we are studying the possibility of contribution
in solving the multi-objective vehicle Routing problem with time
windows , that is one of the optimization problems of the NP-hard
type , This problem has attracted a lot of attenti
on now because of
its real life applications.
Moreover, We will also introduced an algorithm called hybrid
algorithm (HA) which depends on integrates between Multiple
objective ant colony optimisation (MOACO) and tabu search (TS)
algorithm based on the Pareto optimization , and compare the
presented approach is the developer with standard tests to
demonstrate the applicability and efficiency.
In this research, we are studying the possibility of
contribution in solving the Vehicle Routing Problem With Time
Windows(VRPWTW), that is one of the optimization problems of
the NP-hard type. This problem has attracted a lot of attention now
be
cause of its real life applications. However, there is still no
algorithm that provides us with the perfect solution to this problem
because of the complexity of polynomial time. This means that the
time of the solution to the VRPWTW is growing steadily with the
increase in the number of nodes .All the used algorithms have just
given solutions that are close to the optimal one.
A Vehicular Ad-hoc Network (VANET) is a collection of nodes forming a
wireless network, but the nodes of this network are vehicles with special equipment that
enable them to communicate with each other. VANET protocols have to face high
challenges
due to dynamically changing topologies, link breakage and low vehicular
density. A suitable and effective routing protocol helps to ensure that messages are reached
to their destinations and achieve the desired aim of the application.
In this research, we present an analysis of the performance of two major routing
protocols used in these networks, which are AODV (Ad hoc On-Demand Distance Vector)
and GPSR (Greedy Perimeter Stateless Routing). This analysis is based on various
parameters such as end-to-end delay and average dropped packets, in order to find the best
protocol which can be used in the network with low density at the junctions. To achieve
this purpose, we used a simulator OPNET_17.5. Depending on the simulation results, we
have obtained and the analysis and comparison of two protocols at different low density
contract. We found that GPSR protocol has better performance end-to-end delay and
average dropped packets are used as the performance metrics, and is better for VANET
under the low vehicular density simulation scenario at junctions.
Enjoy the sender in the right to guide the goods either by dragging them
from reaching the airport or from the airport to do or diverted to non-agreed
location or change the recipient's name, and this right is transmitted to the
addressee in certa
in circumstances, and to the enjoyment of both the sender
and the addressee of this right varied opinions about the legal basis governing
this right.
3D data, extracted from stereoscopic images, are considered as the main input for
digital modeling and GIS database construction. These data are usually collected by using
professional software. This kind of tools, is difficult to use by the non-sp
ecialists.
In this study, we propose to use the free academic photogrammetric softwares that
are available in the internet, to achieve interior and exterior orientations of images. But,
before this step, these softwares must be evaluated. In our research, we applied a software
developed by an academic photogrammetric society. The software was applied to calculate
the orientation parameters of a stereoscopic pair of aerial photos taken for an urban area.
After that, the results were evaluated by the help of a professional photogrammetric
software. Finally, a group of stereoscopic analysis was done by using the academic
software. Again, the results were evaluated by the help of a professional software.
