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A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amount of energy, especially during the training phase. The transmission of big data between service providers, users and data centres emits carbon dioxide as a result of high power consumption. This chapter proposes a theoretical framework for big data analytics using computational intelligent algorithms that has the potential to reduce energy consumption and enhance performance. We suggest that researchers should focus more attention on the issue of energy within big data analytics in relation to computational intelligent algorithms, before this becomes a widespread and urgent problem.

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Publication Date
Wed Jan 01 2020
Journal Name
Applied Energy
Solidification enhancement with multiple PCMs, cascaded metal foam and nanoparticles in the shell-and-tube energy storage system
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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

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Publication Date
Sun Mar 01 2020
Journal Name
Iraqi Journal Of Physics
Effect of Laser Energy and Repetition Rate on Holmium Plasma Emission
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The holmium plasma induced by a 1064-nmQ-switched Nd:YAG laser in air was investigated. This work was done theoretically and experimentally.  Cowan code was used to get the emission spectra for different transition of the holmium target. In the experimental work, the evolution of the plasma was studied by acquiring spectral images at different laser pulse energies (600,650,700, 750, and 800 mJ). The repetition rates of (1Hz and 10Hz) in the UV region (200-400 nm). The results indicate that, the emission line intensities increase with increasing of the laser pulse energy and repetition rate. The strongest emission spectra appeared when the laser pulse energy is 800mJ and 10 Hz repetition rate at λ= 345.64nm, with the maximum intensi

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Performance of Case-Based Reasoning Retrieval Using Classification Based on Associations versus Jcolibri and FreeCBR: A Further Validation Study
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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of International Oral Health
Endothelin-1 is a surrogate biomarker link severe periodontitis and endothelial dysfunction in hypertensive patients: The potential nexus
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Aim and Objectives: The objective of this study was to illustrate the link between periodontitis (PO) and endothelial dysfunction in hypertensive patients. Materials and Methods: This cross‑sectional study involved 53 hypertensive patients with or without PO compared with 28 healthy controls. On the basis of the study protocol, the participants were divided into three groups: Group (1): 24 patients with hypertension only, Group (2): 29 patients with hypertension and PO, and Group (3): 28 healthy controls. Lipid profile, endothelin‑1 (ET‑1), and high‑sensitivity C‑reactive protein (hs‑CRP) were measured. Blood pressure and body mass index (BMI) were evaluated. Diagnostic criteria of severe PO periodontal indices including plaque

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Biotech Research
Bacteriocin Production by Staphylococcus Epidermidis the Normal Flora of Outer Ear: A Potential Probiotic Against Outer Ear Infections
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Publication Date
Tue May 23 2023
Journal Name
Journal Of Sensors
On-Board Digital Twin Based on Impedance and Model Predictive Control for Aerial Robot Grasping
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Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
ESTIMATED NON-PARAMETRIC AND SEMI-PARAMETRIC MODEL FOR LONGITUDINAL DATA
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Publication Date
Tue Jan 01 2008
Journal Name
Lecture Notes In Computer Science
IRPS – An Efficient Test Data Generation Strategy for Pairwise Testing
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Publication Date
Mon Mar 30 2026
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Adaptive Security Model for Data Protection Using Behavioral User Authentication
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Credential compromise is one of the most widespread security threats, allowing adversaries to bypass traditional authentication measures and impersonate legitimate users. Traditional intrusion detection systems are often based on network-level or macro-behavioral indicators, which can be easily spoofed by an attacker, thus compromising the effectiveness of those mechanisms. This study presents an improved adaptive intrusion detection system to authenticate user behavior based on micro-digital behavioral profiling. It involves the use of timing of keystrokes, micro-mouse, navigation in the application, and interaction rhythm signatures. The proposed system uses a hybrid model consisting of Long Short-Term Memory (LSTM) sequence predi

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