Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genotype-by-environment interactions. Permutation-based feature importance analysis further revealed that planting date had a more significant impact on trait variation than genotype. To identify optimal combinations of genotype and planting date for maximizing morphological traits, the RF model was integrated with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). According to the RF–NSGA-II optimization results, the optimal values, including 26 branches per plant, a growth period of 176 days, 116 bolls per plant, and 1517 seed numbers per plant, were achieved with the Qaleganj genotype planted on May 5. Collectively, these findings highlight the potential of integrating machine learning and evolutionary optimization algorithms as powerful computational tools for crop improvement and agronomic decision-making.
Study showed structure of pecten oculi in the Kestrel Falco tinnunculus L.was
Pleated type and consisted of 17 folds which were thick. While in the Collared Dove
Streptopelia decaocto F. was Vaned type and consisted of 13 folds and it described
thin. The illustrated histological study of pecten oculi folds in the Kestrel and the
Collared Dove was composed of large number of capillaries, large blood vessels and
pigment cells which were few in Kestrel compare with the Collared Dove. The bridge
in the Kestrel and the Collared Dove pecten oculi was consisted of connective tissue,
many pigment cells, and contains on little capillaries and it linked the membrane to
the internal limiting membrane of the retina in the Kes
With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t
... Show MoreIslam was keen to get every man and woman a share of those benefits and wanted to marry and urged him. In order to unite efforts and articulates the arrow and clarifies the goal and I have a share in building a sober Islamic society, for all this and other research title is ((modern or planting and its impact on marital happiness)).
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show MoreThe current study was conducted for studying the impact of cold plasma on the expression level of three genes that participate in the biosynthesis of the phenylpropanoid pathway in Ocimum basilicum. These studied genes were cinnamate 4-hydroxylase (c4h), 4-coumarate CoA ligase (4cl), and eugenol O-methyl transferase (eomt). Also, the cold plasma impact was studied on the essential oil components and their relation with the gene expression level. The results demonstrated that cold plasma seeds germination of the treated groups 2 (initially for 3 minutes and 3 minutes after 7 days) ,and group 3(initially for 5 minutes and 3 minutes after 7 days) were faster than the control group. Also, the height average of the mature plants of
... Show MoreShadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit
... Show MoreThe ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi
... Show MoreThe hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
... Show MoreWe aimed to examine the potential protective effects of Iraqi
Rats were assigned to four groups, six in each group. Group I: rats were administered a daily oral dose of 1 mL/kg/day of distilled water. Group II: rats were intraperitoneally injected with 70 mg/kg DEN once per week for 10 conse