Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userدراسة حول تحسين أمن قواعد المعطيات - تطبيق على قواعد معطيات كلمات السر
551
0 6
0.0
(
0
)
Added by
Syrian Virtual University رسالة ماجستير
Publication date
2015
fields
Informatics Engineering
and research's language is
العربية
Created by
Shamra Editor
Ask ChatGPT about the research
أصبحت جميع المواقع الموجودة على الشبكة العنكبوتية والمخدمات تهتم بأمور السرية التامة في مواقعها بالإضافة إلى عمليات تطوير حماية البيانات الخاصة بها
No English abstract
References used
أنظمة قواعد المعطيات المحاضرة الأولى 2011 تعريف قواعد البيانات
rate research
Read More
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.
The mentioning relational database system term has become a synonymous to
database system, but the monopoly of big companies that work in database systems field
has become an obsession for persons who work in this field, because of the high costs o
f
this systems. For this reason the concerns turn towards the advanced technique : the native
XML database systems which are free or most of them are open source systems because of
the increasing dependency on XML files and particularly in transporting data between
different applications and the availability of collections of related files. This has
summoned towards a system to manage and organize them, for this reason the NXDs
appeared. The aim of this study is making a comparison between the capabilities of
RDBMS and NXDs in accordance to multiple standards , investing these two techniques
in practical application , make the relevant tests which reflect the use of these techniques
on the suggested application , display the results and give future suggestions.
There was within the last 50 years a lot of database applications in which time plays an
important role. These applications revealed a lack in time support within the current DBMSs as
the application should give the data the temporal semantics rela
ted to it, also to check the
temporal constraints. Therefore, researches were made in order to embed this temporal
semantics and constraints in the DBMS itself, also to provide a new query language that can be
tagged as “temporal”.
The purpose of this study is to offer help to patients through the employment of
databases applications of existing and available telecommunication systems in medical
services ,particularly treatment. So that it can be possible to avoided what can
be avoided
of health disasters that a human being encounter without warning. This study examines
how modern technologies can be employed in controlling and processing some vital signs
of human beings,particulary those who suffer some health problems affiliated with some
diseases ,and keeping these problems under control in order to maintain the stability of the
patients health statues.
The vital signs that the study is applied to are blood pressure, pulse and blood
glucose, since any of change in the value of any of these signs, positive or negative, may
cause the patient to have a sudden health problems.
شبكات الحساسات اللاسلكية
العلامات الحياتية
شبكات الحساسات اللاسلكية الحيوية
بروتوكول التوجيه بالزمن الحقيقي
استدعاء الطرق عن بعد
Vital signs
(WSN (wireless sensor networks
(WBSN (wireless body sensor networks
RTLD (Real-time with load distributed routing) Protocol
(RMI (Remote method invocation
المزيد..
relation extraction systems have made extensive use of features generated
by linguistic analysis modules. Errors in these features lead to errors of
relation detection and classification. In this work, we depart from these
traditional approaches w
ith complicated feature engineering by introducing
a convolutional neural network for relation extraction that automatically
learns features from sentences and minimizes the dependence on external
toolkits and resources. Our model takes advantages of multiple window
sizes for filters and pre-trained word embeddings as an initializer on a nonstatic
architecture to improve the performance.
suggested questions
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
