We deal with the navigation problem where the agent follows natural language instructions while observing the environment. Focusing on language understanding, we show the importance of spatial semantics in grounding navigation instructions into visua
l perceptions. We propose a neural agent that uses the elements of spatial configurations and investigate their influence on the navigation agent's reasoning ability. Moreover, we model the sequential execution order and align visual objects with spatial configurations in the instruction. Our neural agent improves strong baselines on the seen environments and shows competitive performance on the unseen environments. Additionally, the experimental results demonstrate that explicit modeling of spatial semantic elements in the instructions can improve the grounding and spatial reasoning of the model.
In this study the urban system of the governorate of Lattakia has been examined
through the applicability of measurements of the equality of spatial distribution patterns of
cities (Demangeon Index and Lorenz curve), and those of Primacy and cities
size
distribution patterns (the Law of Primate city of Mark Jefferson, 1939, the Index of
Primacy of Stewart, and the hierarchical order of city through the Rank-size Rule - George,
K. Zipf, 1949). It has been identified on the size of the imbalance equilibrium in the system
urban cities through Urban Isostastic Index. The results of the study showed a clustered
patterns of the spatial distribution of urban centers according to the value of Demangeon
Index (0.42) and unequal distribution of urban population to the cities (75% of urban
population are distributed on 15% of cities). It showed also a great domination of the
primate city of Latakia on the urban system where the population volume was (6.1) time
bigger than the volume of the next cities according to Primacy Index; a great decrease of
the real value of the next cities comparing with the theoretical value of Law of Primate
City (16.4%) against (67%), and disability to applying the Rank-size Rule.
This paper introduces a system to recognize labels of time plans, where labels are
extracted from time plan. This labels are images, so spatial segmentation is used to extract
images of labels only. Size of images of labels are made same using medi
an's algorithm for
two purposes. The first one is to create database training for used neural networks. The
second is to recognizing's processing. Two methods of recognizing are dependent on using
neural networks technic: classification using perceptron network and recognizing using
back propagation network. Perceptron network is built to take image as input and to give
classification index as output for label. Then label is recognize dependent on stored table
of ASCII for label. Back propagation network is designed to recognize images for all
letters of English alphabet that are used in time plan. Results of research appear efficiency
of designed system to recognize labels of time plan from their images for both methods
after system had been applied on three time plans.
The appearance of revolutionary containerization utilized by maritime transport
sector has led to congested seaports. A transfer of a portion of the activities performed
inside was suggested. A complement to the sea port became desired, which creat
ed the idea
of a dryport. We studied the effect of the dryport’s site, planned to be constructed in Hassia
industrial city, on the Syrian transport network. We used geographic information systems
(GIS) to get the results due potential assistance. Study shows that a dryport increases the
efficiency of the transport system, thus reducing the cost and time of transport.
Furthermore, Hassia industrial city is especially qualified to establish a dryport, and the
eastern region would be the optimal region for such an establishment.
GIS software provide manual import tools to maps produced on CAD software to be transformed to geo-database. This operation consumes time and effort. The "transformation" however will not be
adequate unless we analyze the relation between CAD and GI
S software in preparing maps. The question raised here if this relation competitive or integrative? This research tries to answer this matter
by studying it from different angles: modeling, spatial feature, scale, spatial analysis and data management. Analyses reveal that this relation isn't competitive at all, but rather integrative, as CAD
software produce technical\design plans, whereas GIS software are dedicated for the production of general and thematic maps. Thus, CAD based spatial data (topographic, cadastral, master plans) could
be "up-graded" to be efficient in GIS environment. However available tools to make this are basically manual, and for that, an automated approach was developed to execute this upgrade from CAD to GIS.
This new approach was applied and evaluated and the output results were satisfactory accurate, time\effort saving, and indeed didn't miss any of CAD layers. This all could be achieved if being conditioned with the approach constrains.
