Artificial intelligence (AI) aims to develop systems that achieve a level of intelligence similar to or surpassing human intelligence. AI applications are designed to mimic human cognitive behaviors, with the goal of embedding human knowledge into computers through what is known as knowledge bases. Computers can then use software tools to search these bases, perform comparisons, and conduct analyses to derive and infer the best solutions to various problems. This process resembles how humans solve new problems in their daily lives by relying on past experiences, predicting potential outcomes, and using reasoning skills to evaluate the best available solutions. This study investigates the current use of AI applications in education by faculty members in scientific and humanities colleges at the University of Baghdad, as well as the challenges they face. It also aims to identify differences in the use of AI and the associated challenges based on variables such as academic degree (Master’s, PhD), gender (male, female), academic specialization (scientific, humanities), and years of service (1–10 years, 11 years or more). The research sample included 279 faculty members from the College of Physical Education and Sports Sciences for Women and the College of Education for Women at the University of Baghdad for the academic year 2020 2021. The study utilized a scale developed by Sabah Eid Al-Subhi (2020) to measure the reality of faculty members' use of AI applications. The scale consisted of 23 items divided into two axes: the reality of AI use in education (11 items) and the challenges faced by faculty members (12 items). Responses ranged from "very high degree" to "very low degree." The scale's validity was confirmed by a panel of experts, and its reliability, calculated using Cronbach's alpha, was 0.88. The results revealed that the use of AI applications by faculty members in scientific and humanities colleges at the University of Baghdad was very low, while the challenges they faced were very high. Based on these findings, the researchers recommended providing intensive lectures to raise awareness among faculty and students about the importance of using AI in education to save time, effort, and costs. They also suggested organizing discussion sessions and workshops on AI and its applications.
The growing use of tele
This paper presents a new secret diffusion scheme called Round Key Permutation (RKP) based on the nonlinear, dynamic and pseudorandom permutation for encrypting images by block, since images are considered particular data because of their size and their information, which are two-dimensional nature and characterized by high redundancy and strong correlation. Firstly, the permutation table is calculated according to the master key and sub-keys. Secondly, scrambling pixels for each block to be encrypted will be done according the permutation table. Thereafter the AES encryption algorithm is used in the proposed cryptosystem by replacing the linear permutation of ShiftRows step with the nonlinear and secret pe
... Show MoreLuminescent sensor membranes and sensor microplates are presented for continuous or high-throughput wide-range measurement of pH based on a europium probe.
This research concerns study the crack growth in the wall of pipes made of low carbon steel under the impact load and using the effect of hygrothermal (rate of moisture 50% and 50℃ temperature). The environmental conditions were controlled using high accuracy digital control with sensors. The pipe have a crack already. The test was performed and on two type of specimens, one have length of 100cm and other have length 50cm. The results were, when the humidity was applied to the pipe, the crack would enhance to growth (i.e. the number of cycles needed to growth the crack will reduce). In addition, when the temperature was increase the number of cycles needed to growth the crack are reduced because the effect of heat on the mechanical pro
... Show MoreMany industrial systems involve multiple criteria and objectives, and they are very complex problems in computational science, such as task scheduling. We propose bi-criteria and bi-objective scheduling problems, which are solved by two nature-inspired evolutionary algorithms, such as Simulated Annealing (SA) and Bee Algorithm (BA). This problem is characterized by scheduling a batch of tasks on multiple machines, and it is fundamental because the solution should focus on the simultaneous optimization of two conflicting objectives: the makespan minimization and the total tardiness minimization. This problem is NP-Hard, and therefore, two evolutionary methods were used to search for solutions intelligently in this huge, very complex
... Show MoreCladophora and Spirulina algae biomass have been used for the removal of Tetracycline (TC) antibiotic from aqueous solution. Different operation conditions were varied in batch process, such as initial antibiotic concentration, different biomass dosage and type, contact time, agitation speed, and initial pH. The result showed that the maximum removal efficiencies by using 1.25 g/100 ml Cladophora and 0.5 g/100 ml Spirulina algae biomass were 95% and 94% respectively. At the optimum experimental condition of temperature 25°C, initial TC concentration 50 mg/l, contact time 2.5hr, agitation speed 200 rpm and pH 6.5. The characterization of Cladophora and Spirulina biomass by Fourier transform infrared (FTIR) indicates that the presenc
... Show MoreText categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th
... Show More<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In
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