In today’s competitive environment, organizational efficiency and sustained growth are crucial for survival. The performance of an organization is intricately connected to strategic planning, prompting firms to gather and leverage competitive information for a competitive advantage. Senior managers, recognizing this, initiate actions accordingly. This study aims to investigate the relationship between foresight, vision, strategic partnerships, motivation, system thinking, and organizational performance. Data, gathered through a self-administered questionnaire from various textile units, were analysed using structural equation modelling (SEM). The findings indicate that sub-constructs of strategic intelligence positively impact organizatio

This paper aims to study the role of a prey refuge that depends on both prey and predator species on the dynamics of a food web model. It is assumed that the food transfer among the web levels occurs according to Lotka-Volterra functional response. The solution properties, such as existence, uniqueness, and uniform boundedness, are discussed. The local, as well as the global, stabilities of the solution of the system are investigated. The persistence of the system is studied with the assistance of average Lyapunov function. The local bifurcation conditions that may occur near the equilibrium points are established. Finally, numerical simulation is used to confirm our obtained results. It is observed that the system has only one type of a

     By taking into account various food components in the ecosystem, the research intends to develop a set of difference equations to simulate a plant-herbivore interaction of Holling Type II. We determine the local stability of the equilibrium points for the scenarios of extinction, semi-extinction (extinction for one species), and coexistence using the Linearized Stability Theorem. For a suitable Lyapunov function, we investigate theoretical findings to determine the global stability of the coexisting equilibrium point. It is clear that the system exhibits both Flip and Neimark-Sacker bifurcation under particular circumstances using the central manifold theorem and the bifurcation theory. Numerical simulations are

A newly developed analytical method characterized by its speed and sensitivity for
the determination of cadmium (II) in aqueous solution in three randomly chosen
samples from river water at different locations via turbidimetric measurement by
Ayah 6SX1-T-2D Solar - CFI analyser. The method is based on the formation of
yellowish white precipitate for the complex Cd3[Fe(CN)6]2 by direct reaction of the
cadmium (II) with potassium hexacyano ferrate (III) in aqueous medium. Turbidity
was measured via the reflection of incident light that collides on the surfaces
precipitated particles at 0-180o. Chemical and physical parameters were investigated.
Linear dynamic of cadmium (II) is ranged from 0.05-12 mmol.L-1, with cor

There are different types of corruptions such as administrative, political, economic and financial corruption. The corruption forms also varied such as bribery, nepotism and extortion. All types and forms of corruption play significant role in the all economic variables generally and on investments in particular, and the corruption used to be an intermediate means in reducing the rate of economic growth.  The corruption contributes in reducing the domestic investments via pay bribery by investors to officials’ persons for supplemental contracts and tenders which finally leads to reduction in the investment efficiency. The corruption also contributes in rise of operational costs for the investment projects.  In additio

The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

This study aimed at recognizing the impact of empowerment of human resources strategy on enhancing the financial performance in working banks in Jordan, the axes of the strategy were: informative sharing, free and independence, working teams, and organizational power. To achieve the objective of the study, a questionnaire is designed and distributed on the sample of the study, which represented 60 employees of Banks. After analyzing the data by using SPSS, the study resulted that there is positive impact of empowerment of human resources strategy on enhancing the financial performance in working banks in Jordan. It suggested that the working banks in Jordan should establish database, and to create working teams.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class