This paper presents a novel miniaturized triple-mode microstrip bandpass filter (BPF) designed using the space-mapping (SM) technique. The filter supports three center frequencies at 1.9 GHz, 2.14 GHz, and 2.45 GHz, corresponding to CDMA, WCDMA, and RFID applications, respectively. The proposed design utilizes an RT/Duroid 5880 substrate with a dielectric constant of 2.21 and a thickness of 20 mil, with the conductor layer on the top and a ground plane on the bottom. The proposed resonator exhibits high rejection levels in the stopband, low insertion loss within the passband, and an integrated compact structure. The overall size of the designed BPF is 4 mm × 36 mm, demonstrating a considerable reduction in physical dimensions. Experimental results show strong agreement with simulated performance. The compact structure, high Q-factor, and low insertion loss represent the key advantages of this filter compared with previously reported designs.
This study presents a hybrid decision-making approach for supplier selection, with the objective of identifying suppliers that impose the lowest level of risk in their relationship with the purchasing organization. Supplier selection involves numerous criteria, many of which are characterized by uncertainty or imprecision. To address this ambiguity, fuzzy theory is incorporated into the evaluation process. Initially, relevant supplier selection criteria were identified, and a fuzzy Analytic Hierarchy Process (fuzzy AHP) was employed to determine the relative weights of these criteria. Supplier performance for each criterion was expressed using linguistic terms, which were subsequently converted into mathematical form through triangular fuzzy numbers (TFNs). The α-cut method was then applied to transform the TFNs into interval numbers. Since different values of α can produce varying supplier rankings, the average ranking was calculated to obtain the final prioritization of suppliers. This approach enables a more robust and realistic assessment of supplier risk by accounting for uncertainty in the decision-making environment.
Studies in recent decades have demonstrated that artificial neural networks possess strong capabilities for modeling complex and nonlinear systems. This research investigates the applicability of radial basis function (RBF) and multilayer perceptron (MLP) neural networks for determining land suitability. Data from 300 soil profiles located in a northern agricultural plain were used. The evaluated parameters included soil texture, pH, EC, ESP, CaCO₃ content, gypsum content, soil depth, topography, groundwater depth, and segment depth. Land suitability classes were initially determined using the FAO classification method. These values were used as target outputs for training neural networks with various structural configurations. Of the total dataset, 69% was used for training and 31% for testing. Next, the trained neural networks were applied to predict land suitability classes using the unseen portion of the data (31%). A comparison of the two neural network models revealed that the MLP network produces more accurate predictions of land suitability classes than the RBF network. Additionally, the MLP model required less training time compared to the RBF model. These results indicate that MLP neural networks offer superior performance for land suitability estimation.
In this paper, an efficient and accurate Chebyshev wavelet collocation method is developed for the numerical solution of the time-fractional telegraph equation. The proposed approach achieves high accuracy with a relatively small number of grid points. A notable advantage of the method is its suitability for boundary value problems, as the boundary conditions are inherently satisfied within the formulation. The numerical results obtained are in close agreement with the exact solutions, thereby confirming the reliability of the method. Several examples are presented to illustrate the effectiveness, simplicity, and applicability of the Chebyshev wavelet-based numerical scheme.
The present study investigated the relationship between parental and personal factors that influence students’ academic achievement. Although the determinants of academic success and failure have long been central topics in educational research, a substantial number of students continue to experience academic difficulties each year despite extensive studies and considerable investment in educational development. A quantitative research approach and a correlational design were employed. The sample consisted of 382 male and female high school students selected through proportional stratified random sampling. Data were collected using standardized instruments, including Buri’s Parental Authority Questionnaire, Paulson’s Parental Academic Involvement Questionnaire, the Morgan–Jinks Academic Self-Efficacy Scale, the Schutte Emotional Intelligence Questionnaire, and the Academic Engagement Questionnaire developed by Short, Fleming, Guiling, and Roper. Pearson correlation analysis revealed significant relationships between academic achievement and several variables: authoritative and permissive parental styles, parental involvement in schooling, academic self-efficacy, academic engagement, and emotional intelligence. These findings highlight the intertwined roles of parental influence and personal attributes in shaping academic performance.
In recent years, climate change and recurring drought events in Algeria have caused increasing variability in rainfall patterns and heightened pressure on already-limited water resources. This imbalance between water availability and demand has resulted in reduced precipitation and adverse effects on both economic activity and community livelihoods. The province of Mostaganem, characterized by a semi-arid climate, suffers from particularly constrained water resources. Agriculture accounts for approximately 74% of total water consumption in the region, yet much of this water is used through outdated irrigation techniques that result in significant inefficiencies and waste. Irrigation water is predominantly drawn from small and medium hydraulic (PMH) systems and uncontrolled wells. As agricultural demand relies heavily on groundwater, overexploitation has led to a notable decline in aquifer levels, threatening the long-term viability of the province’s water supply. This study provides a diagnostic assessment of current irrigation practices, with the aim of identifying inadequacies and proposing measures to support water conservation and improve irrigation efficiency. The observed overexploitation of groundwater has already reached a critical level, posing a risk to future agricultural sustainability. However, with the implementation of targeted policies and interventions aimed at promoting rational water use, it is expected that local water management authorities will be better positioned to meet growing agricultural demands.
Innovation is commonly defined as the discovery of new ideas along with their commercial application. Creativity alone does not ensure innovativeness; the successful implementation of new ideas is fundamental to the innovation process. Central to achieving this is the presence of effective leadership capable of guiding and supporting innovative efforts. Prior theoretical studies indicate that explorative and exploitative forms of innovation are associated with different leadership behaviors, specifically transformational and transactional leadership, respectively. This research examines the influence of transformational and transactional leadership styles on explorative and exploitative innovation. Data were collected through questionnaires administered to selected innovative organizations. The results were analyzed and used to develop a conceptual model. Findings indicate that transformational leadership fosters exploratory innovation by facilitating the development of new knowledge and the creation of novel products. Conversely, transactional leadership supports exploitative innovation through the refinement and extension of existing knowledge. Keywords: Innovation; Explorative Innovation; Exploitative Innovation; Transformational Leadership; Transactional Leadership.
