This study specifically contributes to the urgent need for novel methods in Training of Trainers (ToT) programs which can be more effective and efficient through incorporation of AI tools. By exploring scenarios in which AI could be used to dramatically advance trainer preparation, knowledge-sharing, and skill-building across sectors, the research aims to understand the possibility. This study uses a mixed-methods approach, it surveys 500 trainers and conducts in-depth interviews with a further 50 ToT program directors across diverse industries to evaluate the impact of AI-enhanced ToT programs. The results showcase that the use of AI has a substantial positive effect on trainer performance and program outcomes. AI-enhanced ToT programs, for example, saw a 35% increase in trainer knowledge retention rates and 28% improvement in adaptation of training content for different audiences. The report further demonstrated that AI-driven personalized learning paths decreased the time to certify trainers on average by 22%, while improving the quality of training by overall evaluation averages such as standardized assessments. These results demonstrate how AI can be a powerful tool in ToT programs, informing implementation and helping shape the way forward. This is because the AI tools, as demonstrated in the study, are shown to improve occupational trainer preparation quality and efficiency for better effectiveness of future training projects. This paper uses research to establish a base on which organizations can use AI-enhanced technologies to transform their trainer development as well as that of the field of professional training and development itself. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
Onomatopoeia has always been a functional poetic device which enjoys a high sound significance in the poetry of many languages. In modern English and Arabic poetry alike, it proves to be vital and useful at different levels: musical, thematic and at the level of meaning. Still, the cultural difference looms large over the ways it is employed by the poets of each. The present paper investigates the employment of onomatopoeia in the poetry of D. H. Lawrence (1885-1930) and Badr Shakir al-Sayyab (1926-1964) who are chosen due to the importance they enjoy in modern English and Arabic poetry and the richness of their poems in onomatopoeias. The conclusions reached at are in a sense related to cultural differences which govern the use of onomato
... Show MoreThe current research aims to identify the nature of the relationship between training human resources in administrative innovation elements In the General Directorate for the education of the third Rusafa one of the formations of the Iraqi Ministry of Education in Baghdad, In order to achieve the objectives of the research, the researcher provided a comprehensive theoretical framework and the preparation and development of a questionnaire as a tool for collecting data based on the prepared measurements and benefit from previous studies, which contains (28) For the purpose of obtaining realistic results for the variables of the research, the researcher used the random sample in the selection of the research sample A total of (63)
... Show MoreThis paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1) is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
... Show MoreABSTRACT Background: According to Branemark’s protocol, the waiting period between tooth extraction and implant placement is 6–8 months; this is the late placement technique. Achieving and maintaining implant stability are prerequisites for a dental implant to be successful. Resonance Frequency Analysis (RFA) is a noninvasive diagnostic method that measures implant stability. The aim of this study was to investigate the influence of treatment protocol and implant dimensions on primary implant stability utilizing RFA. Materials and methods: This study included 63 Iraqi patients (37 male, 26 female; ranging 22-66 years). According to treatment protocol, the sample was divided into 2 groups; A (delayed) & B (immediate). Dental im
... Show MoreTechnological advances have yielded new molecular biology-based methods for the diagnosis of infectious diseases. The newest and most powerful molecular diagnostic tests are available at regional and national reference laboratories, as well as at specialized centers that are certified to conduct metagenomic testing. Metagenomic assays utilize advances in DNA extraction technology, DNA sequence library construction, high throughput DNA sequencing and automated data analysis to identify millions of individual strands of DNA extracted from clinical samples. At present, metagenomic assays are only possible at a small number of special research, academic and commercial laboratories. Continued research in human and path
... Show MoreLinear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.
In this paper we have been focus for the comparison between three forms for classification data belongs
... Show MoreThe Sliding Mode Control (SMC) has been among powerful control techniques increasingly. Much attention is paid to both theoretical and practical aspects of disciplines due to their distinctive characteristics such as insensitivity to bounded matched uncertainties, reduction of the order of sliding equations of motion, decoupling mechanical systems design. In the current study, two-link robot performance in the Classical SMC is enhanced via Adaptive Sliding Mode Controller (ASMC) despite uncertainty, external disturbance, and coulomb friction. The key idea is abstracted as follows: switching gains are depressed to the low allowable values, resulting in decreased chattering motion and control's efforts of the two-link robo
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