Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as the multi-objective first time as unsupervised Feature Selection (WDOFS) and the second time as a Clustering algorithm (WDOC). For example, the WDOC outperformed Harmony Search and Particle Swarm in terms of F-measurement by 93.3%; in contrast, text clustering's performance improves 0.9% because of using suggested clustering on the proposed feature selection. With WDOFS more than 50 percent of features have been removed from the other examination of features. The best result got the multi-objectives with F-measurement 98.3%.
This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to
... Show MoreBackground: Removing dental plaque is important to maintain a good oral hygiene and prevent periodontal disease; this could not be accomplished by the use of toothbrush alone, it needs the help of interdental aids or intra-oral irrigator devices. The aim of this study was to compare the effect of using Waterpik flosser as adjunct to tooth brushing than using the dental floss with the brushing. Materials and methods: A single blind, six weeks study included 45 subjects divided into three groups of 15 subjects at each group. Group B (brushing) was instructed to use the toothbrush only, group BF (brushing & flossing) was instructed to use dental floss and tooth brushing while group BW (brushing and Waterpik flosser) was instructed to use Water
... Show MoreIraq faces persistent challenges in achieving sustainable development due to decades of conflict, political instability, and infrastructural degradation. These challenges are particularly evident in critical sectors such as energy, water, healthcare, education, and governance, which significantly influence human well-being, social equity, and quality of life. This study proposes an AI-driven, ethically guided, and human-centric sustainability framework to support resilient urban transformation in Iraq.
The paper examines key aspects of the use of phraseologi-cal units related to colors in Russian culture and speech. It explores their role in shaping cultural identity, reflecting national characteristics and men-tality. The study analyzes the frequency and contexts of the use of color-related phraseological units in contemporary speech, as well as the influ-ence of media and literature on their popularization. The author highlights the significance of phraseological units in preserving cultural heritage and fostering a deeper understanding of language and culture.
The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m
... Show MoreAmong a variety of approaches introduced in the literature to establish duality theory, Fenchel duality was of great importance in convex analysis and optimization. In this paper we establish some conditions to obtain classical strong Fenchel duality for evenly convex optimization problems defined in infinite dimensional spaces. The objective function of the primal problem is a family of (possible) infinite even convex functions. The strong duality conditions we present are based on the consideration of the epigraphs of the c-conjugate of the dual objective functions and the ε-c-subdifferential of the primal objective functions.
This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t
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