The benchmark performance of cross-database semantic parsing has climbed steadily in recent years, catalyzed by the wide adoption of pre-trained language models. Yet existing work have shown that state-of-the-art cross-database semantic parsers strug
gle to generalize to novel user utterances, databases and query structures. To obtain transparent details on the strengths and limitation of these models, we propose a diagnostic testing approach based on controlled synthesis of canonical natural language and SQL pairs. Inspired by the CheckList, we characterize a set of essential capabilities for cross-database semantic parsing models, and detailed the method for synthesizing the corresponding test data. We evaluated a variety of high performing models using the proposed approach, and identified several non-obvious weaknesses across models (e.g. unable to correctly select many columns). Our dataset and code are released as a test suite at http://github.com/hclent/BehaviorCheckingSemPar.
The huge growth in the data storing and the wide use of social networks and applications that depend mainly on complicated and interrelated relations between entities which need specific models of databases to store and retriev quickly and effectivel
y, the relational databases are no longer adequate in distributed systems and websites that deal with big data which have to be accessible and operable.
This paper explains briefly the challenges of relational databases and the reasons that led to emergence the non-relational databases (NoSQL), in addition to CAP theorem and some of NoSQL types, specially GraphQL
The aim of this study is to assess the spatial distribution of health centers in rural Lattakia
governorate and to develop a scientific methodology to guide the growth of the health
sector by identifying the needs and adequacy of the primary health
care centers according
to the spatial distribution of the population within these rural areas using spatial statistical
techniques in GIS.
In order to achieve this objective, a spatial database was created, including the population
centers, the primary health care centers (health centers) with the population served by
them, as well as a group of fields on the specifications of these centers in terms of
ownership, floor space and human cadres.
A number of quantitative and spatial tests were conducted in order to measure the fairness
of the distribution of health centers according to the population distribution and determine
the need, while attempting to find an initial guidance on the locations of the supporting
centers according to quantitative and spatial analysis And then measure the degree of
improvement according to the study indicators.
The result of this research was to describe the current status of the distribution of health
centers in the northern Latakia countryside, identify areas of weakness and inadequacy,
propose supporting centers and develop an effective guideline for assessing and improving
the placement of primary health care activities in rural areas.
The importance of research lies in the need to keep pace with the technological development of computer systems and technologies
Modern methods, especially geographic information systems, in collecting, storing, analyzing and exiting
Spatial inform
ation and linking it to metadata, modeling and scenarios
Planners and decision-makers to assist them in planning and finding appropriate solutions for various problems.
In this research, some of audio signal properties have been studied according to the
speaker's vocal tract shape. A database of audio files has been recorded. These files belong
to 57 men whose age between 35 and 45. All speakers came from the same
academic and
social culture. Furthermore, they don't suffer from any problems in hearings and utterance.
The vowel database was created in perfect recording conditions. The spent time
needed for recording process was about five minutes for each speaker who said the Arabic
word " سألتمُونِيهَا " three times. That word is very rich of vowel letters. It composes of the
whole Arabic long vowel.
Based on the analysis study of the recorded audio signals, the relationship between
the formant frequencies and the length of speaker's vocal tract has been studied. The results
show an inverse proportion for the first three frequencies F1, f2, F3 and no clear
relationship for the two other frequencies F4, F5.
New sciences have greatly contributed in improving analysis processes and
subsequently lead to better understanding of the future. The more knowledge and
information are available, the better planning process will be. Furthermore, better data
lead
s to better decision-making. This is the basis of Geographic Information System (GIS).
Due to its great ability in processing and analyzing extensive and various amount of spatial
data, GIS has solved many obstacles in the research field since it was first launched.
GIS plays an important role in the field of tourism planning as it contributes in
developing new applications that serve modern touristic.
In this research paper, GIS will be used to build an effective system that will improve
touristic planning in Lattakia governorate. A spatial database will be created, that includes
the most prominent touristic places in the city, such as restaurants, hotels, religious and
historical sites.etc.
Each of the touristic attractions will be evaluated, and then a tool , created in GIS
environment, will be used for weighting roads network, in order to determine the touristic
weight for each path in roads network.
The volume of data being generated nowadays is increasing at
phenomenal rate. Extracting useful knowledge from such data
collections is an important and challenging issue. A promising
technique is the rough set approach, a new mathematical method
to data analysis based on classification of objects into similarity
classes, which are indiscernible with respect to some features. This
paper focuses on discovering maximal generalized decision rules
in databases based on a simple or multiple regression, generalized
theory, and decision matrix.
In our research we offer detailed study of one of the data
mining functions within the text data using the object properties in
databases. It studies the possibility of applying this function on the
Arabic texts. We use procedural query language P
L / SQL that
deals with the object of Oracle databases.
Data mining model Has been built. It works on classification
of Arabic texts documents using SVM algorithm for indexing of
texts and texts preparation, Naïve Bayes algorithm to classify data
after transformation it into nested tables. So we made an evaluation
of the obtained results and conclusions.
This Research suggests a new mechanism that aims to increase the effectiveness of
surveillance systems by extracting the moving objects coming from surveillance camera in
order to identify them and propose a new mechanism for indexing and storing i
n database
and classified them according to the basic characteristics and strong indicators and retrieval
when needed in less possible time.
The basic idea lies in the combination of the basic characteristics of the goal (color,
edges and texture) which ensures the best performance in extracting the basic target
features and depend on it as indexes, then nonlinear transfers has been done on the edges
of the target in order to get a picture bearing the minutest details, then conducted adverse
transfers on the edges of the target during the process retrieved from the database. Finally,
we propose a new mechanism for indexing all images tabase to Retrieval them in best
accuracy and less time, and a program had been achieved to realize this idea.
In this research, a new comparison criterion was proposed to study properties of the
audio signal for each of the varieties of smokers and non-smoking persons. For this
purpose, a database for smokers has been created. The smoker database contains
12 Syrian
native speakers, six of them were smokers and the others were non-smokers. The smokers
had been smoking for more than 10 years. All speakers were men and their ages ranging
between 35 and 42 years old. They live in rural towns and speak the same dialect.
Syrian vowels can be classified into long vowels and short ones. The long vowels are
/AA/, /UU/, /II/ pronounced as ([ ي, و, ا ]) and the short vowels are /A/, /U/, /I/ pronounced
as ([ كسرة, ضمة, فتحة ]). In this study, the Speakers have to pronounce the following sentence
/I love Syria/ pronounced as ([ أَنَاْ أَحَبُّ سُوْرِيْة ]), and it was spoken during three hours. This
sentence is rich with vowels.
For each speaker, a long vowel triangle in ten planes and a short vowel triangle in ten
planes as well were generated and analyzed. A new criterion was suggested to determine
the most suitable vowel triangle for smoker distinction. This criterion depends on
calculating the different distances among all centers of vowel triangles in each plane and
determining the minimal distance called d. For each plane, the most suitable vowel triangle
had been set as AIU35 short vowel triangle and AAIIUU45 long vowel triangle.
