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Finite Time Disturbance Observer Based on Air Conditioning System Control Scheme
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A novel robust finite time disturbance observer (RFTDO) based on an independent output-finite time composite control (FTCC) scheme is proposed for an air conditioning-system temperature and humidity regulation. The variable air volume (VAV) of the system is represented by two first-order mathematical models for the temperature and humidity dynamics. In the temperature loop dynamics, a RFTDO temperature (RFTDO-T) and an FTCC temperature (FTCC-T) are designed to estimate and reject the lumped disturbances of the temperature subsystem. In the humidity loop, a robust output of the FTCC humidity (FTCC-H) and RFTDO humidity (RFTDO-H) are also designed to estimate and reject the lumped disturbances of the humidity subsystem. Based on Lyapunov theory, the stability proof of the two closed-loop controllers and observers is presented. Comparative simulations are carried out to confirm that the proposed controller outperforms conventional methods and offers greater accuracy of temperature, humidity, and carbon dioxide concentration, having superior regulation performance in terms of a rapid finite time convergence, an outstanding disturbance rejection property, and better energy consumption. In addition to presenting the comparative simulation results from the control applications on the VAV system, the quantitative values are provided to further confirm the superiority of the proposed controller. In particular, the proposed method exhibits the shortest settling time of, respectively, 15 and 40 min to reach the expected temperature and humidity, whereas other comparative controllers require a longer time to settle down.

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Publication Date
Mon Feb 28 2022
Journal Name
International Journal Of Interactive Mobile Technologies (ijim)
Flying Ad hoc Networks (FANET): Performance Evaluation of Topology Based Routing Protocols
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Flying Ad hoc Networks (FANETs) has developed as an innovative technology for access places without permanent infrastructure. This emerging form of networking is construct of flying nodes known as unmanned aerial vehicles (UAVs) that fly at a fast rate of speed, causing frequent changes in the network topology and connection failures. As a result, there is no dedicated FANET routing protocol that enables effective communication between these devices. The purpose of this paper is to evaluate the performance of the category of topology-based routing protocols in the FANET. In a surveillance system involving video traffic, four routing protocols with varying routing mechanisms were examined. Additionally, simulation experiments conduct

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Publication Date
Thu Feb 01 2018
Journal Name
Iet Signal Processing
Signal compression and enhancement using a new orthogonal‐polynomial‐based discrete transform
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Publication Date
Sun Oct 01 2023
Journal Name
Optical Fiber Technology
A taper-in-etch based hybrid fiber Mach-Zehnder interferometer hydrogen sensor
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Publication Date
Sun Jul 01 2012
Journal Name
Applied Soft Computing
A new evolutionary based routing protocol for clustered heterogeneous wireless sensor networks
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Synthesis, Anticancer and Antibacterial Activity of Mannose-based bis-1,2,3-Triazole Derivatives
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       In the current work, aromatic amines and alkyl halides have been converted to the corresponding azides 2a‒d and 4a-d by the reaction with sodium nitrite and sodium azide respectively for amines and sodium azide for halides. Then, dipropargyl ether derivative of D-mannose 8 has been synthesized from diacetone mannose that has been obtained by the treatment of D-mannose (5) with dry acetone in the presence of sulfuric acid. Then, aldol condensation has been used to prepare diol 7 from the mannose diacetonide 6. The reaction of compound 7 with propargyl bromide in alkaline media has been afforded dipropargyl

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Publication Date
Tue Mar 25 2014
Journal Name
Sensors
Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects
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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation
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Publication Date
Fri Nov 03 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Study the Variables Affecting Formulation of Ethylcellulose-based Microsponges Loaded with Clobetasol
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Clobetasol propionate (CP) is a super potent corticosteroid widely used to treat various skin disorders such as atopic dermatitis and psoriasis. However, its utility for topical application is hampered due to its common side effects, such as skin atrophy, steroidal acne, hypopigmentation, and allergic contact dermatitis. Microsponge is a unique three-dimensional microstructure particle with micro and nano-meters-wide cavities, which can encapsulate both hydrophilic and lipophilic drugs providing increased efficacy and safety. The aim of the current study is to prepare and optimize clobetasol-loaded microsponges. The emulsion solvent diffusion method is used for the preparation of ethylcellulose (EC)-based microsponges. The impact of

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Publication Date
Thu Mar 24 2022
Journal Name
Arab World English Journal
Collocation Networks of Selected Words in Academic Writing: A Corpus-Based Study
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This study aims at shedding light on the linguistic significance of collocation networks in the academic writing context. Following Firth’s principle “You shall know a word by the company it keeps.” The study intends to examine three selected nodes (i.e. research, study, and paper) shared collocations in an academic context. This is achieved by using the corpus linguistic tool; GraphColl in #LancsBox software version 5 which was announced in June 2020 in analyzing selected nodes. The study focuses on academic writing of two corpora which were designed and collected especially to serve the purpose of the study. The corpora consist of a collection of abstracts extracted from two different academic journals that publish for writ

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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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