JOURNAL OF ADMINISTRATION AND ECONOMICS

Brain cancers include primary brain tumours, and a brain tumour indicates an abnormal growth of cells in the brain that may be either benign or malignant. Benign tumours lack cancer cells, and once removed, they seldom reappear. However, benign brain tumours can lead to significant health complications and may eventually become malignant. Malignant brain tumours are cancerous, grow aggressively, invade nearby tissue, and are often life-threatening. In recent years, the treatment of many cancers, particularly brain cancer, has advanced significantly.
A mixed cure survival model is a type of survival analysis used when a portion of the individuals in a study are "immune" or "cured," meaning they will never experience the event being studied (such as death or recurrence of the disease). At the same time, the rest are exposed to that event.
Consequently, the number of patients who fail to achieve favourable outcomes, including passing, decreased. The quantitative assessment of this form of disease involves recovery models applied in place of traditional survival models. This study analysed 315 cases of brain cancer from Rzgari Hospital in Erbil city between 2020 and 2024. Among these cases, 99 patients (31.4%) were classified as cured. The data was modelled using the mixture cure approach with several statistical distributions, incorporating the cured fraction in this population and the significance of the Maller-Zhou test. Based on the research outcomes and a comparison of the Akaike Information Criterion and Bayesian Information Criterion, the cure framework employing the Weibull distribution for survival time was deemed the most suitable.

The research aims to determine the response of stock returns in the financial markets as a result of the nature of the investor’s impulsiveness and orientations following behavioural theory, away from rationality in decision-making, and how market liquidity can play a role in enhancing this effect. The Iraqi Stock Exchange was chosen as a research community, and the sample represents market data for the extended period. [1/2009 - 12/2023] on a monthly level, which produced a time series that included [180] observations for each variable. The investor sentiment variable was measured by the trading volume index, market liquidity by the natural logarithm of the market size according to the market value, and the volatility of stock returns by calculating the market rate of return. According to the market index, a simple and multiple regression model was adopted to test the mediation hypothesis, and the results showed that there is a positive, significant effect of investor morale on stock returns, which reflects a state of pessimism or optimism in price trends. It also showed that increasing investor options and market depth directly enhances the effect of investor morale on the Volatility of returns.

This research assesses the utility of Restricted Mean Survival Time (RMST) as a viable alternative to conventional survival analysis techniques, including the Kaplan-Meier test and Cox Proportional Hazards model, especially when the proportional hazards assumption is not met. RMST offers an alternative approach to using hazard ratios in such situations. This study aimed to evaluate the impact of predictive factors on breast cancer survival. The Restricted Mean Survival Time (RMST) offers a clinically interpretable measure of average survival time within a defined period, providing a more detailed understanding of treatment effects and patient outcomes. Additionally, the study utilised the Cumulative Incidence Function (CIF) model and probability estimates for each time point to further analyse survival data.
Using data from 4,420 breast cancer patients at Rizgary Hospital, this research quantifies the impact of various prognostic factors on survival outcomes. The study demonstrates that RMST effectively captures differences in survival probabilities across treatment groups, with patients undergoing surgery or receiving radiotherapy showing significantly higher survival rates than those who did not. Additionally, the analysis reveals that factors such as family history and tumour grade significantly influence survival outcomes, highlighting the heterogeneity of breast cancer. Statistical comparisons using RMST, alongside traditional tests like the Log-rank and Gehan-Wilcoxon tests, confirm significant differences in survival curves, particularly in early-stage survival, emphasising the importance of timely interventions.

The current research aims to highlight the role of financial technologies in reducing the costs of banking services among a sample of professors from five Iraqi universities in 2024. The study utilised a questionnaire to analyse opinions, distributing 110 forms via social media platforms, of which 83 were retrieved and all deemed valid for use. The researcher employed the statistical software SPSS V.27 to analyse and interpret the study's results. The study finds that there is a significant relationship between financial technology and decreased banking costs in the current sample, so when financial technology improves in banks, it leads to a decrease in banking costs.

This research aims to determine the level of implementation of the Total Productive Maintenance system at the first gas power station in South Baghdad, and the impact of this system on achieving green productivity among a sample of employees at the researched station, represented by 60 employees in senior and middle management. The research problem was formulated regarding the relationship between the research variables (Total Productive Maintenance and Green Productivity) and three sub-dimensions for each primary variable through a questionnaire model. Several statistical methods were used, including arithmetic means, standard deviations, confirmatory factor analysis, impact testing, and other statistical methods. One of the most important conclusions reached in the research through inference of the practical statistical results is that there is a relationship and impact between Total Productive Maintenance and Green Productivity, in other words, the necessity of implementing the Total Productive Maintenance system to achieve Green Productivity and contribute to saving the environment surrounding the station from environmental pollution catastrophe in the country.

The instability of regression models is one of the most prominent issues facing researchers when estimating the model. On the other hand, regularisation techniques (Lasso and Rlasso ) are some of the most notable techniques applied in the estimation of multiple regression models because of their ability to reach an explanatory regression model through which accurate predictions can be made. In this research, the simulation method was applied to conduct a comparison between a set of regression models estimated using the two regularisation techniques (Lasso & Ro), where the Chow Test and CUSUM Test were used to test the stability of the estimated models and the presence of multicollinearity. The results showed that both techniques performed excellently in building a stable regression model. The results showed the superiority of the Rlasso technique, especially in the presence of multicollinearity.

The current research aims to explain how the interim financial statements are prepared in the industrial sector in the Iraqi Stock Exchange, their conformity with the International Accounting Standard (34), and the extent to which the quality of gains is available in these statements. It focuses on the type of users of the financial statements, indicating that there may be manipulation in the interim lists. For the companies in the research sample, the management’s ability to use various accounting methods and procedures may make profits not truly reflect the company’s performance. The researcher adopted the model (Kothari et al. 2005) to measure the non-discretionary receivables of the companies in the research sample for the period (2019-2021). He also used the regression equation to estimate Model parameters to indicate the quality of earnings. The research concluded that the application of International Accounting Standard (34) was not accurate in the industrial companies of the research sample during the period, and the quality of earnings decreased in the interim financial statements of the companies of the research sample in general, and the researcher recommends publishing complete interim financial statements. Attached are adequate disclosures, containing all the information items needed by stakeholders associated with the company, and educating users of the interim financial statements on the importance of the quality of earnings

The study aimed to investigate the role of digital readiness among administrative leaders in adopting the requirements of artificial intelligence (AI). The significance of this research stems from the growing importance of AI adoption in business activities, particularly within private universities. The study sought to assess the level of digital readiness among administrative leadership in private universities in the Kurdistan Region and analyse how its dimensions impact the adoption of AI requirements. A descriptive-analytical approach was employed to examine the study variables. The research population included deans, heads of departments and administrative unit managers in colleges affiliated with private universities in the region. The primary data collection tool was a questionnaire, of which 175 copies were distributed. A total of 144 valid responses were retrieved and used for analysis, representing the study sample. The researchers utilised various statistical tools, including descriptive statistics, correlation coefficients, and regression analysis.
The study reached several conclusions, most notably that AI adoption in private universities is closely linked to the digital readiness of their administrative leadership. This suggests that the likelihood of adopting AI increases when digital readiness is present. Additionally, digital readiness was found to play a critical role in supporting AI adoption. Among the dimensions of digital readiness, shared beliefs ranked highest in influencing AI adoption, followed by organisational capabilities. The study recommends focusing on methods that enhance digital readiness among administrative leaders to facilitate the adoption of AI requirements. It also calls for future research to explore the impact of other variables on AI adoption.

This study explores the determinants of electronic banking service usage among Arab Bank customers in Palestine who do not currently use these services. Adopting a descriptive research approach, a questionnaire was designed to collect data. The study targeted all Arab Bank customers in Palestine who are non-users of electronic banking services. Using a purposive sampling method, 380 questionnaires were distributed, and 337 were retrieved for analysis.
The findings revealed that the overall level of determinants affecting the use of electronic banking services was high, with an arithmetic mean of 3.46. The perceived benefits of using e-banking services were rated at an average level, with a mean of 3. Statistical analysis showed no significant differences (α ≤ 0.05) in respondents' perceptions of determinants based on gender, except for the variables of "lack of human communication" and "lack of banking secrecy." Similarly, educational qualifications showed no significant differences except for "lack of trust" and "resistance to change." Monthly income levels did not yield substantial differences across most fields, except for "resistance to change" and "banking secrecy." Additionally, the number of banks a customer deals with did not show significant differences, apart from the "bank secrecy" variable.
These results highlight key areas influencing the adoption of electronic banking services in Palestine and provide valuable insights for banks to address customer concerns and enhance service delivery.

Artificial intelligence has already been utilised in medical treatments for a while, but its progress over the past ten years is impressive. In medicine, both machine learning and deep learning approaches are becoming more popular since there is more health-related data available, these techniques are better at handling massive datasets, and computers are getting more powerful.
The purpose of this paper is to investigate how to use supervised learning, more specifically, classification machine learning and deep learning algorithms, to discover the best way to classify brain tumour therapy using K-Nearest Neighbour and recurrent neural network algorithms. Employed algorithms for machine learning, K-nearest neighbour, and the recurrent neural network to see how risk factors changed the way drugs were classified for patients. Both algorithms worked well. The results suggest that forecasting methods can group drugs and are useful for making decisions. This development is a step toward using machines and deep learning in medical treatment.

This section should include a succinct, self-contained and powerful statement that describes the main objective of the study. The abstract of one paragraph length should not contain formulas and references, it should occupy the first page and includes the following items: Brief background on the research topic, problem statement (if exists), research objective, methods and tools used in the research and significant results, an abstract summarizing the content of the paper of no more than 250 words. A good abstract is precise and honest, can stand alone, uses no technical jargon and is specific. (Size line 11, Time Now Roman and Italic).

Organisational wisdom is considered one of the strategic pillars that educational institutions—especially international schools—strive to enhance to achieve competitiveness. This requires these schools to create an internal environment that enables them to gain a competitive advantage. Among the organisational elements that influence many aspects of organisational performance is the administrative leadership style, which can play a key role in fostering organisational wisdom.
The research problem lies in diagnosing the extent to which the transcendent leadership style contributes to organisational wisdom in international schools in Duhok Governorate. The main aim of the study is to examine the role of transcendent leadership—through its dimensions of (values and attitudes, transcendent behaviour, and moral elevation)—in shaping the dependent variable, which is organisational wisdom, in these schools.
The study adopted the descriptive-analytical method, and the primary tool for data collection was a questionnaire. A total of 120 questionnaires were distributed, of which 102 were retrieved and deemed valid for analysis, forming the study sample. Using SPSS software, the research yielded several findings, foremost among them being that transcendent leadership has a significant impact on organisational wisdom. In particular, the dimensions of transcendent behaviour and moral elevation were found to contribute significantly to enhancing organisational wisdom among teaching staff in international schools in Duhok.
The study recommends the adoption of transcendent behaviors and moral elevation among future administrative leaders to strengthen organizational wisdom in these schools. It also calls for future studies to explore other leadership styles that may contribute to enhancing organizational wisdom among educators in educational institutions.

The purpose of this study is to assess the impact of various adjacency matrices (Rook and Queen) on the accuracy of the spatial autoregressive-moving averages model (SAR-MA) and to examine the effects of spatial dependency on the estimates of the model using the maximum likelihood approach (MLE). The study's foundation was actual diabetes data. Concerning Iraqi children in 2024, when data was gathered from different governorates, including variables like age, gender, cumulative blood sugar level, and other factors that impact the disease's spread, the presence of spatial dependence was tested using Moran's Z test. The maximum likelihood method (MLE) was then used to estimate the model parameters. To guarantee precise estimates and expand the range of potential future uses of spatial models in urban planning and economics, the study recommended utilising the SAR-MA model in conjunction with the Rook adjacency matrix in spatial analysis. Additionally, some variables (S4, S5, S8) showed a clear geographical dependence in the results, whereas others did not.