There is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardn
This research aims to the possibility of evaluating the strategic performance of the State Board for Antiquities and Heritage (SBAH) using a balanced scorecard of four criteria (Financial, Customers, Internal Processes, and Learning and Growth). The main challenge was that the State Board use traditional evaluation in measuring employee performance, activities, and projects. Case study and field interviews methodology has been adopted in this research with a sample consisting of the Chairman of the State Board, 6 General Managers, and 7 Department Managers who are involved in evaluating the strategic performance and deciding the suitable answers on the checklists to analyze it ac
... Show MoreSewer system plays an essential task in urban cities by protecting public health and the environment. The operation, maintenance, and rehabilitation of this network have to be sustainable and scientifically. For this purpose, it is crucial to support operators, decision makers and municipalities with performance evaluation procedure that is based on operational factors. In this paper, serviceability and performance indicator (PI) principles are employed to propose methodology comprising two enhanced PI curves that can be used to evaluate the individual sewers depending on operational factors such as flowing velocity and wastewater level in the sewers. To test this methodology; a case study of al-Rusafa in Baghdad city is
... Show MoreAdvancing the multi-scale performance of asphalt pavements requires innovative binder modifications that address limitations in rutting resistance, fatigue resistance, and durability across the binder, mixture, and structural levels. This study evaluates the performance of asphalt cement, mixtures, and pavement systems modified with a combination of polyethylene (PE) and carbon nanotubes (CNTs). The binder was modified using 4% PE and varying CNT contents (0.5%, 1%, 1.5%, and 2% by weight of the modified binder). Binder performance was assessed through conventional and rheological tests, including penetration, softening point, viscosity, performance grade (PG) evaluation, and master curve analysis. Mixture-level performance was eval
... Show MoreSolar photovoltaic (PV) has many environmental benefits and it is considered to be a practical alternative to traditional energy generation. The electrical conversion efficiency of such systems is inherently limited due to the relatively high thermal resistance of the PV components. An approach for intensifying electrical and thermal production of air-type photovoltaic thermal (PVT) systems via applying a combination of fins and surface zigzags was proposed in this paper. This research study aims to apply three performance enhancers: case B, including internal fins; case C, back surface zigzags; and case D, combinations of fins and surface zigzags; whereas the baseline smooth duct rep
Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
... Show MoreHard-grade asphalt binders, such as AC 20–30, offer excellent resistance to permanent deformation but are inherently brittle, making them highly susceptible to fatigue and low-temperature cracking. While polymer modification addresses these issues, virgin polymers remain expensive. Despite the growing interest in recycled plastics, the rheological impact of complex waste streams, specifically polyvinyl chloride (PVC) derived from flex banners containing plasticizers, on excessively stiff binders within the complete Superpave Performance Grading (PG) framework remains critically underexplored. This study introduces a novel valorization approach by utilizing solvent-extracted flex banner waste (WPVC) as a dual-action modifier. It leverages
... Show MoreSummary: This study aims to examine the names of four-legged animals found in Turkish translations of the Qur’an written between the 11th and 15th centuries from linguistic, etymological, and semantic perspectives. These translations, belonging to the Old Anatolian Turkish period, serve not only as religious texts but also as valuable documents reflecting the social structure, cultural values, and linguistic features of the time. Within the scope of this research, six major tafsir (exegesis) texts were systematically analyzed, and the data obtained were evaluated within historical and cultural contexts. The theoretical framework of the study is based on Lakoff and Johnson’s Conceptual Metaphor Theory and Wierzbicka’s approach to lingu
... Show MoreOlfactory impairment and abnormal frontal EEG oscillations are recognized as early markers of Alzheimer’s disease (AD). Using a publicly available olfactory EEG dataset of 35 subjects spanning normal cognition, amnestic mild cognitive impairment (aMCI), and AD, each with MMSE scores and demographics, stimulus-locked epochs from four electrodes (Fp1, Fz, Cz, Pz) were processed with wavelet-based time–frequency analysis. Band-limited power ratios (delta, theta, alpha, beta) were computed as log-transformed post-odor/baseline values and aggregated to subject-level features. Statistical analyses revealed graded attenuation of odor-evoked frontal (Fp1) band-power ratios across groups, with significant differences in several band–od
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
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