AL-MANSOUR JOURNAL

The Two words that inform the title of this paper, namely ‘treason’ and ‘compassion’ are quite suggestive in the elegant sense that they actually define the stunning realities in Flaubert’s novel. They impinge on our minds the negative as well as the positive realities and magnificently isolate for us a writer who is in full control of his creation.
Emma starts by marrying a man who disastrously fails to satisfy her and soon she feels wretched. As a way out of her miserable state, she first befriends Randolph as a lover. Then she leaves him and befriends Léon only to go back to Randolph to help her financially. But he let her down. She, then, feels so wretched that she ends her life by poisoning herself.
A grief-stricken Charles, Emma’s husband, has been unaware of Emma’s financial troubles and her miserable state. He remains devoted to his deceased wife as he struggles to pay her debts. After discovering love letters from Randolph and Léon, Emma’s lovers, he becomes increasingly sad, blaming Emma’s sad end on fate. Shortly afterwards he dies. Then left alone, Berthe, his daughter, ends by working at a cotton factory.
The message of Flaubert’s novel is quite enlightening: “In writing Madam Bovary, Flaubert criticises the values of the bourgeois class through events leading to Emma’s downfall.” (1)

Deep image steganography has emerged as a promising approach for concealing secret information with in digital images, leveraging the power of deep learning techniques to enhance security. The study explores the integration of deep neural networks to enhance the security and robustness of steganographic methods. Conventional image steganography approaches may have vulnerabilities because of their fixed algorithms, which makes them less flexible in handling different types of image material and more prone to being detected by advanced steganalysis methods. The proposed method aims to advance covert communication systems by utilizing deep learning to achieve imperceptibility and robustness against common structural analysis methods.
This study presents a generic Convolutional Neural Network (CNN) with encoder-decoder architecture for deep image steganography method. It facilitates the seamless concealment and extraction of information. In order to assess the efficacy of the proposed approach, peak signal-to-noise ratio and structural similarity index measurements were used. Experimental results based on an ImageNet dataset show that our approach outperforms the selected related methods in terms of security, robustness and visually imperceptibility. PSNR: 72.79 SSIM: 0.9753 The test results, thus gleaning that the approach we proposed is superior to previous methods.

With the fast deployment of Internet of Things (IoT) in healthcare environment, it is critically important to secure reliable mechanisms for securing constantly streamed real-time data. This paper suggests a blockchain-based architectural model to preserve C-I-A (Confidentiality, Integrity and Availability) of health data while transferring from IoT-Devices. The model creates a simulated blockchain network on the MATLAB on which it incorporates Delegated Proof-of-Stake (DPoS) consensus protocol, PoW and PoV mechanisms to strengthen transactional trust and eliminate unauthorized data fabrication. In the simulation, different testing parameters (node density, amount of data traffic, and network change rate) are set up to test the system performance. We analyze the efficiency of the framework to enable continuous data transfers and balance real-time computational offloading in healthcare IoT environments. The results indicate that the architecture can support continuous secure and trustworthy information flows that are available, making critical healthcare data authentic and resilient.

: Due to the increasing growth of data sent and received between parties, and how to protect it and keep it safe from tampering and theft, this led to the necessity of using and innovating techniques and algorithms that enhance the security of this data, especially sensitive data. Blockchain technology provides a reliable option for transferring data, especially sensitive data, securely due to its decentralized properties. However, there is still a challenge in how to maintain it in the face of continuous digital development. Non-fungible tokens (NFTs), one of the growing uses of blockchain technology, have evolved as digital ownership certificates that safely store a variety of data on a distributed ledger, This study offered a strategy for protecting a valuable, sensitive image and prove that a certain person is the rightful owner of it, The image encrypted, and then uploaded to the interplanetary file system (IPFS), hidden within a carrier image for added security, and then stored on the blockchain. This strategy would mitigate the issue of counterfeit photographs and nefarious individuals attempting to mimic the rightful owners of images or sensitive data. The results regarding encryption and embedding, which were as follows: PNG images retained higher quality after encoding than JPEG images. (PSNR: inf dB, MSE:0.0).

Water shortage has been a significant issue in arid and semi-arid areas owing to the uneven rainfall distribution, population explosion, and mounting pressure on the traditional water resources. Centralized rainwater harvesting (RWH) systems represent a technically feasible and sustainable approach for augmenting water resources; however, their effectiveness largely depends on the careful selection of suitable locations. Accordingly, this study proposes a GIS-driven decision-support model that integrates DEM-derived hydrological indices with an objective multi-criteria decision-making (MCDM) framework to identify suitable sites for the implementation of centralized RWH systems in Karbala Province, Iraq. Based on Shuttle Radar Topography Mission (SRTM) data, and spatial analysis, six physically meaningful criteria were obtained, namely mean slope, mean elevation, mean curvature, mean log-transformed flow accumulation, mean distance to streams, and site area. To reduce subjectivity, the Entropy Weight Method (EWM) was used to find the relative significance of each criterion objectively. Technique of Order of Preference by Similarity to an Ideal Solution (TOPSIS) was used to rank 23 candidate sites according to their proximity to the ideal solution. The findings indicate that site area and flow accumulation account for the largest share of influence on site suitability, whereas elevation and curvature contribute a comparatively smaller proportion to the overall assessment.

This research introduces and tests a blockchain-based approach for building citizens trust in e-government services. Using the mixed-methods research design in a two-stage approach, we first conducted the expert focus groups (n=12) to generate a conceptual model of the relationship between perceived security (PS), transparency (TR), data integrity (DI), and procedural fairness (PF) with trust in service (TS), intention to adopt (AI), with governance quality (GQ) as a contextual moderator. Then we did a survey of 412 active users of public digital services and analyzed this data using PLS-SEM. The reliability and validity of the measurement model was good (alpha=.82-.91; AVE=.59-.76). The structural model accounted for 68% of TS and 61% of AI (SRMR=.056; NFI=.90). All antecedents were positively associated with TS (betaPS=.27; betaTR=.23; betaDI=.18; betaPF=.22; all p values <.05), and TS was strongly associated with AI (beta=.63, p <.001). TS mediated all the effects of PS/TR/DI/PF on AI to a full extent, and GQ significantly reinforced the connection between PS and TS (beta=.14, p<.05). We also present a four-layer framework (infrastructure, service, governance, user) to achieve a combination of auditability on-chain and the off-chain PII along with zk-compatible roadmap. The results imply that blockchain can be used to build positive influences on trust embedded in transparent, accountable, and privacy preserving governance.

The most difficult task for a robotics researcher is to control the robot manipulator with adequate overall efficiency. This work presents accurate and fast techniques for optimizing the parameters of a 3-DOF robot manipulator, this kind of robot is intended for academic and educational work and it is also used in the medical field. The links of the 3- DOF are all rotary or revolute joints with serial connections.
The optimization technique focuses on the Intelligent Swarm algorithms that are used for optimizing and tuning the gain of the proposed controller, which is the conventional Proportional Integral Derivative (PID) is used.
The Intelligent Particle Swarm Optimization (PSO) and Social Spider Optimization (SSO) have been used for obtaining the best values for the parameters of the controller, to achieve consistency, stability, and robustness. MATLAB/Simulink is used to speed up the computing of FK, IK, and DM of the 3-DOF robot manipulator. The results show that modified PID /SSO gives the best results in terms of stable phase response, minimum Root Means Square Error with the best objective function, stable control signal and reasonable steady-state with perfect trajectory tracking for circular path.

With the ever-growing demand for ultra-low-latency communication in Vehicle-to-Everything (V2X), traditional software-based approaches to encryption have become an increasingly challenging subject. We propose the current adaptive encryption architecture in FPGA to enhance the real-time functionality of vehicular networks in 5G and beyond. Through the parallelism and reconfigurability properties of FPGAs, the proposed model dynamically alters cipher algorithms and key scheduling based on message priority and network situation. A modular encryption core, real-time key scheduler, and stream/block controller are developed on a Xilinx Zynq-7000 System-on-Chip (SoC)for fast and flexible cryptographic processing. Experimental performance in a simulated V2X traffic demonstrates a 42% decrease in latency and 36% increase in throughput with respect to standard microcontroller solutions, in full conformance to European Telecommunications Standards Institute Intelligent Transport Systems - G5 (ETSI ITS-G5) and 3GPP V2X. It also takes advantage of runtime cipher reconfiguration and is resistant to timing side-channel and replay attacks. These findings emphasize the feasibility of the proposed approach for secure deployment in the emerging intelligent transportation systems.

This research aims to study the relationship between organizational Creation and academic entrepreneurship by surveying a sample of 50 faculty members at the College of Tourism Sciences, Al-Mustansiriya University. The research employs a descriptive analytical approach to analyze the impact of organizational Creation on fostering a culture of academic entrepreneurship within the university environment. The study concluded that organizational Creation positively influences academic entrepreneurship, revealing that flexible organizational structures, university leadership support, and the availability of financial and technological resources are key factors in promoting entrepreneurial thinking among faculty members. The results also highlighted several challenges hindering the adoption of academic entrepreneurship, most notably administrative bureaucracy, limited funding, and the lack of effective partnerships between universities and the tourism sector. The research recommends strengthening organizational Creation within universities by providing a supportive organizational environment, developing incentive policies to encourage faculty members to transform their research into entrepreneurial projects, and establishing university business incubators to facilitate the transfer of knowledge to the market.

The study aims to present the most significant threats facing the Iraqi hotel sector in order to achieve cybersecurity, which plays a pivotal role in addressing future challenges, given its use as a technology for managing hotel organizations' networks. The objective is to develop mechanisms to mitigate these threats and take all necessary precautionary measures to prevent any potential destabilization of hotel organizations. While technology has contributed significantly to the development of the hotel sector and facilitated access to and utilization of its services, it has also had negative consequences — namely, the threat of cyberattacks, data breaches, and unauthorized access to the organizations' information systems. This poses a serious risk not only to hotel organizations themselves but also to the privacy and safety of their customers' information. Therefore, this study seeks to explore the concept of cybersecurity and identify the main threats that may face the Iraqi hotel sector. The study concludes that there is a negative impact on hotel performance and reputation: any breach, data leak, or cyberattack can result in financial losses, loss of customer trust, and legal consequences — all of which weaken competitiveness and harm business operations, especially in a sector that relies heavily on customer service and trust. The study recommends the establishment of clear and consistent security policies: adopting an information security policy that ensures data confidentiality, customer privacy, security updates, and controlled user access.

Organizational culture plays a significant role in developing human capital in organizations. It can be argued that organizational culture is the foundation upon which an organization's success is built. Organizational culture is one of the most important factors that directly and indirectly influence organizational performance, particularly with regard to human capital development. The values and beliefs that prevail within an organization form the framework that guides individual behavior, influences their motivation and incentives, and supports the development of their skills and capabilities. This research aims to explore how organizational culture contributes to enhancing human capital, both in terms of knowledge and skills, as well as organizational loyalty, innovation, and continuous learning. Literature indicates that organizations with a flexible and stimulating organizational culture provide greater opportunities for organizational learning and encourage responsibility and initiative, which enhances the development of human capital as one of the organization's most important strategic assets).
Organizational culture also plays a key role in fostering employee loyalty and motivating employees to achieve excellence, which in turn positively impacts their individual and collective performance. Several studies have indicated that a supportive organizational culture fosters a climate of trust and cooperation and provides a safe environment for learning and experimentation, which contributes to building human capital capable of innovation and adapting to change. Furthermore, the various dimensions of organizational culture, such as performance culture, empowerment, and participation culture, play a pivotal role in attracting, developing, and retaining human talent within the organization. It becomes clear that the relationship between organizational culture and human capital is not a one-way street, but rather a reciprocal one, whereby human capital, in turn, contributes to shaping organizational culture by embodying shared values and implementing positive practices. The researcher recommends integrating organizational culture strategies into human resource development plans to ensure sustainable institutional performance and enhance organizations' competitiveness in the contemporary work environment.

This study aims to construct a proposed structural model to identify the most influential factors on the success of Machine Learning (ML) applications in the Iraqi hotel sector, focusing on four- and five-star hotels in Baghdad to address the research gap in unique local environments. The study adopted the descriptive-analytical approach based on primary data collected through a field survey of a sample of (83) individuals from hotel management and staff, reflecting the challenges of sample sizes available in unique local settings. The measurement instrument (questionnaire) was designed to evaluate three main complex constructs: Human factors, Organizational factors, and Technological factors. The Smart PLS V.4 software was utilized for Partial Least Squares Structural Equation Modeling (PLS-SEM), which included validity and reliability analyses and structural path testing. The results demonstrated that the proposed model possesses high statistical robustness, and that Technological and Human factors hold the largest and most significant impact on explaining ML success. This outcome confirms that data quality and technical competencies are the cornerstones for technological projects in this context.

This study examines the role of artificial intelligence in the development of radio content through a case study of the virtual presenter Aimee at Radio Mustang Jakarta in Indonesia. The research employed a descriptive-analytical approach and a case-study design, applying content-analysis methods to a systematic random sample of 30 radio episodes broadcast between December 2023 and July 2024.
The findings reveal a strong, positive, and statistically significant correlation (r = 0.72, p = 0.003) between increased use of artificial intelligence and the perceived overall quality of content, thereby supporting the study’s principal hypothesis. The main conclusion is that a hybrid model—combining AI’s efficiency in routine tasks (which accounted for 32.9% of airtime) with human creativity in producing complex content—represents the optimal approach for advancing the radio industry. Accordingly, the study recommends that Arab broadcasting institutions adopt this hybrid model while establishing ethical and regulatory frameworks to ensure transparency in AI use and to preserve media credibility. The research underscores that artificial intelligence is not a substitute for humans but a powerful tool for reshaping and developing radio broadcasting in the digital age.

This study aims to compare the effect of ephedrine and phenylephrine on the Apgar score of newborns after cesarean section under spinal anesthesia. A comparative pilot study was conducted on 40 pregnant women selected for elective cesarean section. They were randomly assigned to two groups: one group received ephedrine
Another received phenylephrine when hypotension occurred. Apgar scores were recorded at the first and fifth minutes after birth, and the data were analyzed using the Kolmogorov-Smirnov test to check the normality of the distribution, followed by the Wilcoxon Signed-Rank test to measure statistical differences.
The results showed statistically significant differences between the Apgar scores at the first and fifth minutes for both drugs (p<0.05), with ephedrine having a relative advantage in the number of cases that recorded positive improvements in scores. The results indicate that the use of ephedrine contributes more clearly to improving the immediate assessment of the newborn's condition than phenylephrine. Further studies with larger samples are recommended to monitor the long-term effects on the newborn's health.