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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
Fri Mar 20 2020
Journal Name
Remote Sensing
Lossy and Lossless Video Frame Compression: A Novel Approach for High-Temporal Video Data Analytics
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The smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterogenous data from various resources, including unmanned aerial vehicles, surveillance cameras, and low-earth-orbit satellites. One of the core challenges in exploitation of such high temporal data streams, specifically videos, is the trade-off between the quality of video streaming and limited transmission bandwidth. An optimal compromise is needed between video quality and subsequently, rec

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Statistical Sciences
Use The Coiflets and Daubechies Wavelet Transform To Reduce Data Noise For a Simple Experiment
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In this research, a simple experiment in the field of agriculture was studied, in terms of the effect of out-of-control noise as a result of several reasons, including the effect of environmental conditions on the observations of agricultural experiments, through the use of Discrete Wavelet transformation, specifically (The Coiflets transform of wavelength 1 to 2 and the Daubechies transform of wavelength 2 To 3) based on two levels of transform (J-4) and (J-5), and applying the hard threshold rules, soft and non-negative, and comparing the wavelet transformation methods using real data for an experiment with a size of 26 observations. The application was carried out through a program in the language of MATLAB. The researcher concluded that

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Publication Date
Mon Jun 15 2020
Journal Name
Al-academy
Biophysics and its scientific data in industrial product design: جاسم خزعل العقيلي -علاء نجم عبود
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  The current research discussed biophysics data as a theoretical and applied knowledge base linking industrial design with the natural sciences at the level of applied strategies through which we can enrich the knowledge base of industrial design. The research focused on two main aspects of the scientific references for biophysics, namely: electromagnetism, and biomechanics. According to the performance and functional applications in designing the functions of industrial products at the electromagnetic level, it was found that remote sensing applications: such as fire sensors that were adopted from the insect (Black Beetle) and that their metaphors enable them to hear fire, and collision sensors, which were adopted from the insect

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
The effect of the activation functions on the classification accuracy of satellite image by artificial neural network
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Publication Date
Fri Oct 07 2016
Journal Name
Fourth International Conference On Wireless And Optical Communications, 2016, Beijing, China
ESAM: Endocrine inspired Sensor Activation Mechanism for multi-target tracking in WSNs
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Target tracking is a significant application of wireless sensor networks (WSNs) in which deployment of self-organizing and energy efficient algorithms is required. The tracking accuracy increases as more sensor nodes are activated around the target but more energy is consumed. Thus, in this study, we focus on limiting the number of sensors by forming an ad-hoc network that operates autonomously. This will reduce the energy consumption and prolong the sensor network lifetime. In this paper, we propose a fully distributed algorithm, an Endocrine inspired Sensor Activation Mechanism for multi target-tracking (ESAM) which reflecting the properties of real life sensor activation system based on the information circulating principle in the endocr

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Advanced GIS-based Multi-Function Support System for Identifying the Best Route
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Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste

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Publication Date
Wed Sep 01 2021
Journal Name
Iraqi Journal Of Physics
Surface Plasmon Plastic Optical Fiber Resonance with Multi-Layer as Chemical Sensor
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A chemical optical fiber sensor based on surface plasmon resonance (SPR) was developed and implemented using multimode plastic optical fiber. The sensor is used to detect and measure the refractive index and concentration of various chemical materials (Urea, Ammonia, Formaldehyde and Sulfuric acid) as well as to evaluate the performance parameters such as sensitivity, signal to noise ratio, resolution and figure of merit. It  was noticed that the value of the sensitivity of the optical fiber-based SPR sensor, with 60nm and 10 mm long, Aluminum(Al) and Gold (Au) metals film exposed sensing region, was 4.4 μm, while the SNR was 0.20, figure of merit was 20 and resolution 0.00045. In this work a multimode

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
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The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

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Publication Date
Sun Oct 18 2015
Journal Name
International Journal Of Pure And Applied Mathematics
A MODIFIED FUZZY MULTI-OBJECTIVE LINEAR PROGRAMMING TO SOLVE AGGREGATE PRODUCTION PLANNING
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This paper develops a fuzzy multi-objective model for solving aggregate production planning problems that contain multiple products and multiple periods in uncertain environments. We seek to minimize total production cost and total labor cost. We adopted a new method that utilizes a Zimmermans approach to determine the tolerance and aspiration levels. The actual performance of an industrial company was used to prove the feasibility of the proposed model. The proposed model shows that the method is useful, generalizable, and can be applied to APP problems with other parameters.

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Publication Date
Thu Oct 01 2020
Journal Name
Ieee Transactions On Artificial Intelligence
Recursive Multi-Signal Temporal Fusions With Attention Mechanism Improves EMG Feature Extraction
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