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DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

“…It was found that (by the Group Method of Data Handling algorithm), length of the pipe, wellhead pressure, and angle of inclination have a pronounced effect on the pressure drop estimation under these conditions. …”
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Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study by Ayoub, Mohammed Abdalla, Demiral, B.M.R

“…The data covered a wide range of variables such as oil rate (up to 25000 STB/D), water cut (up to 60%), angles of inclination (from -80 to 210), pipe length up to 26.0 km and pressure drop (from 10 to 250 psi). the model has been generated using the Back-propagation technique with Bayesian Regularization training algorithm for predicting pressure drop in pipelines under various angles of inclination. …”
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Network instrusion prevention system ( NIPS) based on network intrusion detection system (NIDS) and ID3 algorithm decision tree classifier by Syurahbil, A

“…Network security has gained significant attention in research and industrial communities.Due to the increasing threat of the network intrusion,firewalls have become important elements of the security policy.Firewall performance highly depends toward number of rules,because the large more rules the consequence makes downhill performance progressively.Firewall can be allow or deny access network packets incoming and outgoing into Local Area Network(LAN),but firewall can not detect intrusion.To distinguishing an intrusion network packet or normal is very difficult and takes a lot of time.An analyst must review all the network traffics previously.In this study,a new way to make the rules that can determine network packet is intrusion or normal automatically.These rules implemented into firewall as prevention,which if there is a network packet that match these rules then network packet will be dropped.This is called Network Intrusion Prevention System(NIPS).These rules are generated based on Network Intrusion Detection System(NIDS)and Iterative Dichotomiser 3 (ID3)Algorithm Decision Tree Classifier,which as data training is intrusion network packet and normal network packets from previous network traffics.The experiment is successful,which can generate the rules then implemented into a firewall and drop the intrusion network packet automatically.Moreover,this way can minimize number of rules in firewall.…”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

Performance monitoring algorithm for optimizing electrical power generated by using photovoltaic system by Pradeep, M.V.K., Balbir, S.M.S., Norani, M.M.

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

“…The Differential Services Code Point within the Differentiated Service (DiffServ) field is primarily used inside the Layer 3 encapsulated network IP packets. Since the user generated data is growing rapidly with variety in data such as, streaming, VoIP, online gaming etc. …”
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Efficient radio resource management algorithms for downlink long term evolution networks by Mamman, Maharazu

“…Secondly, the proposed call admission control algorithm improved the resource utilization algorithm thus reducing the call block, call dropped, call degradation. …”
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CHID : conditional hybrid intrusion detection system for reducing false positives and resource consumption on malicous datasets by Alaidaros, Hashem Mohammed

“…However, flow-based detection still suffers from the generation of the false positive alerts due to incomplete data input. …”
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Discovering rules for nursery students using apriori algorithm by Marufuzzaman M., Gomes D.J., Rupai A.A.A., Sidek L.M.

“…The study was conducted using association rule mining where several mining rules were generated using the Apriori algorithm. The rules obtained had the confidence of 0.95 and support of 0.04. …”

Image Reconstruction Algorithm for Electrical Charge Tomography System by Rahmat, Mohd Fua'ad, Isa, Md Daud, Jusoff, Kamaruzaman, Hussin, T.A., Md Rozali, Sahazati

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Delay-based and QoS-aware packet scheduling for RT and NRT multimedia services in LTE downlink systems by Madi, Nadim K. M., Mohd Hanapi, Zurina, Othman, Mohamed, K. Subramaniam, Shamala

“…Guaranteeing Quality of Service (QoS) for heterogeneous traffic is a major challenge in the Fourth Generation (4G) mobile networks. Therein, the absence of sophisticated resources allocation process at the base station jeopardizes QoS in terms of latency data transfer. …”
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Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks by Mujahid Tabassum

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Image reconstruction algorithm for electrical charge tomography system by Rahmat, Mohd Fua'ad, Isa, Mohd Daud, Jusoff, Kamaruzaman, Raja Hussin, Tengku Ahmad Badrul Shah, Md Rozali, Sahazati

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Automatic mapping of concrete strength in structural element by Hamid, Roszilah, Mohamed, Ramizi, Mohd. Nayan, Khairul Anuar, Osman, Siti Aminah, Mohd. Yusof, Kamarudin

“…The mapping process is done automatically in computer-generated program. Signal-processing techniques were used to compute the data; Fourier Transform to translate a time-series signal into frequency domain, concrete strength calculation, interpolation technique and a Graphic User Interface (GUI) to complete the mapping algorithms.…”
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Instrumentation Monitoring For Heavy Metal Detection In Batik Industry by Kodi, Saravanan Thunsh

“…This project introduced mathematical algorithm to represent the existing metal concentration in the solution based on statistical analysis from the data collection using laboratory control sample. …”
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Improving robotic grasping system using deep learning approach by Mohannad K. H., Farag

“…By proposing a four-step data augmentation technique, the achieved grasping accuracy was 98.2 % exceeding the best-reported results by almost 0.5 % where 625 new instances were generated per original image with different grasp labels. …”
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Tunable Sub-Nanosecond Ultra Wideband Narrow Pulse Generator For Microwave Imaging by Zalzala, Ali Mahdi Jaafar

“…The aforementioned pulse data has been simulated in a locally developed image reconstruction algorithm (EDAS) to detect hypothetical objects and the resultant images show significant quality enhancement in comparison to a Gaussian pulse (or its derivative) with an equivalent duration. …”
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A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines by Tahan, M., Muhammad, M., Abdul Karim, Z.A.

“…Two back-propagation training algorithms, namely the Levenberg–Marquardt and Bayesian regularization algorithms, and the k-fold cross-validation technique, were employed to train the optimal networks using a training data set. …”
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