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A method of multi-dimensional variable selection for additive partial linear models.
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In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection criteria, as- sessing the correct detection of zero coefficients and the false omission of nonzero coef- ficients. A practical application involving financial data from the Baghdad Soft Drinks Company demonstrates their utility in identifying key predictors of stock market value. The results indicate that MAVE-SCAD performs well in high-dimensional and complex scenarios, whereas MAVE-ALASSO is better suited to small samples, producing more parsimonious models. These results highlight the effectiveness of these two methods in addressing key challenges in semiparametric modeling

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
A Signal Amplification-based Transceiver for Visible Light Communication
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Visible light communication (VLC) is an upcoming wireless technology for next-generation communication for high-speed data transmission. It has the potential for capacity enhancement due to its characteristic large bandwidth. Concerning signal processing and suitable transceiver design for the VLC application, an amplification-based optical transceiver is proposed in this article. The transmitter consists of a driver and laser diode as the light source, while the receiver contains a photodiode and signal amplifying circuit. The design model is proposed for its simplicity in replacing the trans-impedance and transconductance circuits of the conventional modules by a simple amplification circuit and interface converter. Th

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Computers, Communications, Control And Systems Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

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Publication Date
Tue Apr 02 2024
Journal Name
Advances In Systems Science And Applications
A New Face Swap Detection Technique for Digital Images
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Publication Date
Thu Mar 09 2017
Journal Name
Sensors
A Multimodality Hybrid Gamma-Optical Camera for Intraoperative Imaging
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The development of low profile gamma-ray detectors has encouraged the production of small field of view (SFOV) hand-held imaging devices for use at the patient bedside and in operating theatres. Early development of these SFOV cameras was focussed on a single modality—gamma ray imaging. Recently, a hybrid system—gamma plus optical imaging—has been developed. This combination of optical and gamma cameras enables high spatial resolution multi-modal imaging, giving a superimposed scintigraphic and optical image. Hybrid imaging offers new possibilities for assisting clinicians and surgeons in localising the site of uptake in procedures such as sentinel node detection. The hybrid camera concept can be extended to a multimodal detec

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Publication Date
Wed Jun 10 2009
Journal Name
Iraqi Journal Of Laser
A new achromatic glass for near infrared laser instruments
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This research investigates new glasses which are best suitable for design of optical systems
working in the infrared region between 1.01 to 2.3μm. This work is extended to Oliva & Gennari
(1995,1998) research in which they found that the best known achromatic pairs are (BAF2-IRG2; SRF2-
IRG3; BAF2-IRG7; CAF2-IRGN6; BAF2-SF56A and BAF2-SF6). Schott will most probably stop the
production of these very little used and commercially uninteresting IRG glasses. In this work equally
good performances can be obtained by coupling BAF2, SRF2&CAF2 with standard glasses from Schott
or Ohara Company. The best new achromatic pairs found are (SRF2-S-TIH10; CAF2-S-LAL9; CAF2-SLAL13
and CAF2-S-BAH27). These new achromatic pai

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Publication Date
Fri Mar 31 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
A Cryptosystem for Database Security Based on RC4 Algorithm
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Because of vulnerable threats and attacks against database during transmission from sender to receiver, which is one of the most global security concerns of network users, a lightweight cryptosystem using Rivest Cipher 4 (RC4) algorithm is proposed. This cryptosystem maintains data privacy by performing encryption of data in cipher form and transfers it over the network and again performing decryption to original data. Hens, ciphers represent encapsulating system for database tables

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Publication Date
Tue Mar 28 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Guggulusome - A Novel Vesicular Carriers for Enhanced Transdermal Delivery
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The present work describes guggul as a novel carrier for some anti-inflammatory drugs. Guggulusomes containing different concentration of guggul with aceclofenac were prepared by sonication method and characterized for vesicle shape, size, size-distribution, pH, viscosity, spread ability, homogeneity, and accelerated stability in-vitro drug permeation through mouse skin. The vesicles exhibited an entrapment efficiency of 93.2 ± 12%, vesicle size of 0.769 ± 3μm and a zeta potential of - 6.21mV. In vitro drug release was analyzed using Franz’s diffusion cells. The cumulative release of the guggulusomes gel (G2) was 75.8% in 18 hrs, which is greater than that all the gel formulation. The stability profile of prepare

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Publication Date
Sat Aug 06 2022
Journal Name
Ijci. International Journal Of Computers And Information
Techniques for DDoS Attack in SDN: A Comparative Study
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Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

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Publication Date
Tue Jun 08 2021
Journal Name
Biomolecules
A Pan-Inhibitor for Protein Arginine Methyltransferase Family Enzymes
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Protein arginine methyltransferases (PRMTs) play important roles in transcription, splicing, DNA damage repair, RNA biology, and cellular metabolism. Thus, PRMTs have been attractive targets for various diseases. In this study, we reported the design and synthesis of a potent pan-inhibitor for PRMTs that tethers a thioadenosine and various substituted guanidino groups through a propyl linker. Compound II757 exhibits a half-maximal inhibition concentration (IC50) value of 5 to 555 nM for eight tested PRMTs, with the highest inhibition for PRMT4 (IC50 = 5 nM). The kinetic study demonstrated that II757 competitively binds at the SAM binding site of PRMT1. Notably, II757 is selective for PRMTs over a panel of other methyltransferases, w

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