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Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such as decision tree and nearest neighbor search. The proposed method can handle streaming data efficiently and, for entropy discretization, provide su the optimal split value.

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Publication Date
Wed Oct 25 2023
Journal Name
2023 Ieee 8th International Conference On Engineering Technologies And Applied Sciences (icetas)
Vibration Characteristics of Perforated Plate using Experimental and Numerical Approaches
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Vibration analysis plays a vital role in understanding and analyzing the behavior of the structure. Where, it can be utilized from this analysis in the design process of the structures in different engineering applications, check the quality and safety of the structure under different working conditions. This work presents experimental measurements and numerical solutions to an out of plane vibration of a rectangular plate with a circular hole. Free edges rectangular plates with different circular holes diameters were studied. The effects of hole location on the plate natural frequencies were also investigated. A finite element modeling (using ANSYS Software) has been used to analyze the vibration characteristics of the plates. A good agree

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Publication Date
Tue Mar 07 2017
Journal Name
The First International Conference For Engineering Research
Colony Counting Using iPad and iPhone Applications
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Publication Date
Sun Jun 07 2015
Journal Name
Baghdad Science Journal
Steganography in Audio Using Wavelet and DES
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In this paper, method of steganography in Audio is introduced for hiding secret data in audio media file (WAV). Hiding in audio becomes a challenging discipline, since the Human Auditory System is extremely sensitive. The proposed method is to embed the secret text message in frequency domain of audio file. The proposed method contained two stages: the first embedding phase and the second extraction phase. In embedding phase the audio file transformed from time domain to frequency domain using 1-level linear wavelet decomposition technique and only high frequency is used for hiding secreted message. The text message encrypted using Data Encryption Standard (DES) algorithm. Finally; the Least Significant bit (LSB) algorithm used to hide secr

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Voice Identification Using MFCC and Vector Quantization
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The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi

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Publication Date
Tue Dec 07 2021
Journal Name
2021 14th International Conference On Developments In Esystems Engineering (dese)
Object Detection and Distance Measurement Using AI
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Publication Date
Thu Apr 01 2021
Journal Name
Complexity
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

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Publication Date
Fri May 02 2014
Journal Name
International Journal Of Scientific & Technology Research
Synthesis, Structure And Characterization Of Zns Qds And Using It In Photocatalytic Reaction
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ZnS nanoparticles were prepared by a simple microwave irradiation method under mild condition. The starting materials for the synthesis of ZnS quantum dots were zinc acetate (R & M Chemical) as zinc source, thioacetamide as a sulfur source and ethylene glycol as a solvent. All chemicals were analytical grade products and used without further purification. The quantum dots of ZnS with cubic structure were characterized by X-ray powder diffraction (XRD), the morphology of the film is seen by scanning electron microscopy (SEM). The particle size is determined by field effect scanning electron microscopy (FESEM), UV-Visible absorption spectroscopy and XRD. UV-Visible absorption spectroscopy analysis shows that the absorption peak of the as-prep

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Publication Date
Thu Jul 05 2018
Journal Name
Eurasip Journal On Wireless Communications And Networking
Positioning and guiding educational robots by using fingerprints of WiFi and RFID array
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Publication Date
Thu Feb 29 2024
Journal Name
Iraqi Journal Of Science
Tigecycline is the Most Effective against Multi-Drug Resistant Klebsiella pneumoniae Recovered from Burn Wound Infections in Two Hospitals in Al-Kut City, Iraq
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     Klebsiella pneumoniae is among the most frequent microorganisms isolated from infections of burn wounds. This cross-sectional study aimed to investigate the distribution of multi-drug resistant (MDR) K. pneumoniae in two burn hospitals and the antibiotic resistance profile in different burn regions of the same patient. It was performed in two hospitals (Al-Zahraa and Al-Karama) in Al-Kut, Iraq, between January and May 2022. Totally, 100 burn swabs were collected from 40 patients of both genders suffering from burn wound infections, with ages ranging between 3 and 50 years. Klebsiella pneumoniae were isolated and identified using conventional methods followed by VITEK®2 system and confirmed via polymerase chain reaction targeting t

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Publication Date
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Indoor Positioning and Monitoring System Using Smartphone and WLAN (IPMS)
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Buildings such as malls, offices, airports and hospitals nowadays have become very complicated which increases the need for a solution that helps people to find their locations in these buildings. GPS or cell signals are commonly used for positioning in an outdoor environment and are not accurate in indoor environment. Smartphones are becoming a common presence in our daily life, also the existing infrastructure, the Wi-Fi access points, which is commonly available in most buildings, has motivated this work to build hybrid mechanism that combines the APs fingerprint together with smartphone barometer sensor readings, to accurately determine the user position inside building floor relative to well-known lan

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