Background:-The Modified Alvarado Scoring
System (MASS) has been reported to be a cheap
and quick diagnostic tool in patients with acute
appendicitis. However, differences in diagnostic
accuracy have been observed if the scores were
applied to various populations and clinical settings.
Objectives:- The purpose of this study was to
evaluate the diagnostic value of Modified Alvarado
Scoring System in patients with acute appendicitis
in our setting.
Methods:-one hundre twenty eight patients, were
included in this study, admitted to Al-Kindy
teaching hospital from June 2009 to June 2010.
Patients’ age ranged from 8 to 56 years (21±10)
they were divided into three groups; paediatrics,
child bearing age females & adult males,. MASS
was calculated for each patient included as the
diagnosis & treatment were done on the bases of
surgeon's clinical decision,confirmation was done
by histopathological examination. Finally statistics
done included negative appendectomy rate,
sensitivity, specificity, positive predictive
value,negative predictive value & accuracy.
Results: - Our negative appendectomy rate was
19.5% (22.22% for paediatrics 40.9% for females
4.2% for males). MASS showed sensitivity of
61%(92.8% for paediatrics 38% for females & 58%
for males), specificity 80% (75% for paediatrics
88% for females & 50% for males), positive
predictive value 92%(92.8% for paediatrics 83%
for females 50% for males), negative predictive
value 33% (75%for paediatrics 50% for females
5% for males) & accuracy 65% (88.9% for
paediatrics 59% for females 58% for males).
Conclusion:- MASS was of limited help to junior
doctors in our setting,clinical assessment &
experience are still the gold standard for acute
appendicitis.
An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to
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Orthogonal Frequency Division Multiplexing (OFDM) is one of recent years multicarrier modulation used in order to combat the Inter Symbol Interference (ISI) introduced by frequency selective mobile radio channel. The circular extension of the data symbol, commonly referred to as cyclic prefix is one of the key elements in an OFDM transmission scheme. This paper study The influence of the cyclic prefix duration on the BER performance of an OFDM-VCPL (Orthogonal frequency division multiplexing - Variable Cyclic Prefix Length) system and the conventional OFDM system with frame 64-QAM modulation is evaluated by means of computer simulation in a multipath fading channel. The adaptation of CP is done with respect to the delay spread estimation
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That the essential contribution of this research is a description of how complex systems analysis service of the properties of the queue in Baghdad Teaching Hospital using a technique network is techniques method (Q - GERT) an acronym of the words:
Queuing theory _ Graphical Evaluation and Review Technique
Any method of assessment and review chart where you will be see the movement flow of patients within the system and after using this portal will be represented system in the form of planned network probabilistic analysis and knowledge of statistical distributions appropriate for times of arrival and departure were using the program ready (Win QSB) and simulatio
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This paper deals with a Twin Rotor Aerodynamic System (TRAS). It is a Multi-Input Multi-Output (MIMO) system with high crosscoupling between its two channels. It proposes a hybrid design procedure that combines frequency response and root locus approaches. The proposed controller is designated as PID-Lead Compensator (PIDLC); the PID controller was designed in previous work using frequency response design specifications, while the lead compensator is proposed in this paper and is designed using the root locus method. A general explicit formula for angle computations in any of the four quadrants is also given. The lead compensator is designed by shifting the dominant closed-loop poles slightly to the left in the s-plane. This has the effect
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A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton
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