Priority of road maintenance can be viewed as a process influenced by decision-makers with varying decision-making power. Each decision-maker may have their view and judgment depending on their function and responsibilities. Therefore, determining the priority of road maintenance can be thought of as a process of MCDM. Regarding the priority of road maintenance, this is a difficult MCDM problem involving uncertainty, qualitative criteria, and possible causal relationships between choice criteria. This paper aims to examine the applicability of multiple MCDM techniques, which are used for assessing the priority of road maintenance, by adapting them to this sector. Priority of road maintenance problems subject to internal uncertainty caused by imprecise human judgments will be reviewed and investigated, as well as the most popular theories and methods in group MCDM for presenting uncertain information, creating weights for decision criteria, examining causal relationships, and ranking alternatives. The study concluded that through the strengths and weaknesses reached, fuzzy set theory is the most appropriate and best used in modeling uncertain information. In addition, the methods that are employed the most common in the literature that has been done to explore the correlations between decision criteria have been examined, and it is concluded that the fuzzy best-worst method may be utilized in this research. The Fuzzy VIKOR approach is most likely the best method for ranking the decision alternatives.
Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi
... Show MoreThe major objective of this study is to establish a network of Ground Control Points-GCPs which can use it as a reference for any engineering project. Total Station (type: Nikon Nivo 5.C), Optical Level and Garmin Navigator GPS were used to perform traversing. Traversing measurement was achieved by using nine points covered the selected area irregularly. Near Civil Engineering Department at Baghdad University Al-jadiriya, an attempt has been made to assess the accuracy of GPS by comparing the data obtained from the Total Station. The average error of this method is 3.326 m with the highest coefficient of determination (R2) is 0.077 m observed in Northing. While in
In this study, dynamic encryption techniques are explored as an image cipher method to generate S-boxes similar to AES S-boxes with the help of a private key belonging to the user and enable images to be encrypted or decrypted using S-boxes. This study consists of two stages: the dynamic generation of the S-box method and the encryption-decryption method. S-boxes should have a non-linear structure, and for this reason, K/DSA (Knutt Durstenfeld Shuffle Algorithm), which is one of the pseudo-random techniques, is used to generate S-boxes dynamically. The biggest advantage of this approach is the production of the inverted S-box with the S-box. Compared to the methods in the literature, the need to store the S-box is eliminated. Also, the fabr
... Show MoreAttention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w
... Show MoreThe objective of present study was to compare of several methods for estimating the degree of heritability and calculating the number of genes using generation mean analysis of maize (
يعتقد البعض ان مفهوم العلم يعني الآلات والاجهزة العلمية (تقنيات التعليم) وهي لا تختلف عن مفهوم تكنولوجيا المعلومات , ويعد هذا الاعتقاد خاطئ , لان العلم هو بناء المعرفة العلمية المنظمة والتي يتم التوصل اليها عن طريق البحث العلمي , اما تكنولوجيا المعلومات فهي "التطبيقات العملية للمعرفة العلمية في مختلف المجالات ذات الفائدة المباشرة بحياة الانسان, او هي النواحي التطبيقية للعلم وما يرتبط بها من آلات واجهزة".
The atmospheric air cold plasma has been used to manufacture gold nanomaterials for treating parasitic leishmaniasis. This study experimentally assessed the treatment of Leishmania parasites (L. donovani and L. tropica) by gold nanoparticles. Specifically, atmospheric pressure nonthermal plasma was generated using different diameters (1.0, 2.8, 3.8 and 4.3 mm) of high voltage electrode. Aqueous gold tetrachloride salts (HAuCl4·4H2O) were used as precursor to produce gold nanoparticles. UV-vis spectroscopy and x-ray diffraction were conducted for characterization of the nanoparticles. The optimum condition (a diameter of 1 mm) was chosen to prepare gold nanoparticles, where the grain size was found to be 17 nm. Accordingly, the nanoparticle
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