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PDF Comparison based on Various FSO Channel Models under Different Atmospheric Turbulence
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Recently, wireless communication environments with high speeds and low complexity have become increasingly essential. Free-space optics (FSO) has emerged as a promising solution for providing direct connections between devices in such high-spectrum wireless setups. However, FSO communications are susceptible to weather-induced signal fluctuations, leading to fading and signal weakness at the receiver. To mitigate the effects of these challenges, several mathematical models have been proposed to describe the transition from weak to strong atmospheric turbulence, including Rayleigh, lognormal, Málaga, Nakagami-m, K-distribution, Weibull, Negative-Exponential, Inverse-Gaussian, G-G, and Fisher-Snedecor F distributions. This paper extensively studies and analyses different probability density functions (PDFs) that govern the FSO channel, considering various channel models. This paper aims to comprehensively understand how FSO channels can be effectively modeled using different PDFs. Accurate modeling is crucial for designing FSO systems that can operate optimally under potential environmental conditions. Selecting the appropriate PDF model plays a crucial role in determining the FSO channel's performance during system design. With a multitude of PDF models available, this study aims to identify the most effective PDF model to be employed in FSO channel modeling.

 

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Publication Date
Sat May 24 2025
Journal Name
Iraqi Journal For Computer Science And Mathematics
Intrusion Detection System for IoT Based on Modified Random Forest Algorithm
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An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

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Publication Date
Sat Apr 01 2023
Journal Name
The Ocular Surface
Detecting dry eye from ocular surface videos based on deep learning
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Publication Date
Fri Feb 28 2025
Journal Name
Journal Européen Des Systèmes Automatisés
Decision-Making Model for Aircraft Landing Based on Fuzzy Logic Approach
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An aircraft's landing stage involves inherent hazards and problems associated with many factors, such as weather, runway conditions, pilot experiences, etc. The pilot is responsible for selecting the proper landing procedure based on information provided by the landing console operator (LCO). Given the likelihood of human decisions due to errors and biases, creating an intelligent system becomes important to predict accurate decisions. This paper proposes the fuzzy logic method, which intends to handle the uncertainty and ambiguity inherent in the landing phase, providing intelligent decision support to the pilot while reducing the workload of the LCO. The fuzzy system, built using the Mamdani approach in MATLAB software, considers critical

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Publication Date
Wed Apr 10 2024
Journal Name
Euphrates Journal Of Agriculture Science
Effect of irrigation levels and organic matter on quality chracteristics of chilli pepper under organic farming system
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Publication Date
Sat Feb 01 2020
Journal Name
Structures
Experimental and numerical study on wrapping concrete cylinders post heating and cooling under preload using CFRP fabrics
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This paper reports test results and describes a numerical investigation of the effectiveness of using carbon fibre reinforced polymer (CFRP) fabrics for strengthening concrete cylinders that have been undamaged and damaged due to heating under preload. The purpose of this research was to investigate whether there is any difference in the performance of CFRP-wrapped cylinders if the wrapping is done under preload, and those for which neither heating, cooling nor wrapping was done under preload. The cylinders were exposed to 30% of maximum load at ambient temperature during heating and cooling before being wrapped under preload. Of 18 Ø 100 × 200 mm identical cylinders, 6 were left as control samples without heating, 12 were exposed t

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Assessing the Influence of Moisture Damage under Repeated Load on Multilayer Interface Bond Strength of Asphalt Concrete
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The performance and durability of the asphalt pavement structure mainly depend on the strength of the bonding between the layers. Such a bond is achieved through the use of an adhesive material (tack coat) to bond the asphalt layers. The main objective of this study is to evaluate the effect of moisture in conjunction with repeated traffic loads on the strength of the bonding between asphalt layers using two types of tack coats with different application rates. Using the nominal maximum size of aggregate (NMAS), the layers were graded (25/19) and (19/9.5) mm. The slabs of multilayer asphalt concrete were prepared using a roller compactor using two types of tack coats to bond between layers, namely rapid curing cut back a

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Toxicity of Nanomulsion of Castor Oil on the Fourth larval stage of Culex quinquefsciatus under Laboratory Conditions
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Mosquitoes like Culex quinquefasciatus are the primary vector that transmits many causes of diseases such as filariasis, Japanese encephalitis, and West Nile virus, in many countries around the world. The development in the scientific fields, such as nanotechnology, leads to use this technique in control programs of insects including mosquitoes through the use of green synthesis of nanoemulsions based on plant products such as castor oil.  Castor oil nanoemulsion was formulated in various ratios comprising of castor oil, ethanol, tween 80, and deionized water by ultrasonication. Thermodynamic assay improved that the formula of (10 ml) of castor oil, ethanol (5ml), tween 80 (14 ml) and deionized water (71ml)   was mor

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Publication Date
Sat Apr 30 2022
Journal Name
Kufa Journal Of Engineering
Numerical Analysis for the Response of Skirt Circular Shallow Footing Resting on Sandy Soil under vertical loads
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Publication Date
Sat Dec 31 2022
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EFFECT OF ADDING DIFFERENT LEVELS OF DILL SEEDS TO THE DIET ON PHYSIOLOGICAL TRAITS OF BROILERS : EFFECT OF ADDING DIFFERENT LEVELS OF DILL SEEDS TO THE DIET ON PHYSIOLOGICAL TRAITS OF BROILERS
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ABSTRACT

This study was conducted in the poultry field of the department of animal production, college of agricultural engineering sciences, university of Baghdad for the period from 10/15/2021 to 11/25/2021 with the aim of showing the effect of adding different levels of dill seeds to the diet on productive and carcass traits For broiler meat. In this study, 200 unsexed broiler chicks of breed (Ross 308) were used, one day age, with a starting weight of 41.46 g. The chicks were randomly distributed to 5 treatments, and each treatment included 4 replicates, 10 birds for each replicate. The birds were fed three diets: the starter diet, the growth diet and the final diet. The experiment treatments were T1,

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Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Numeral Recognition Using Statistical Methods Comparison Study
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The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

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