AL-MANSOUR JOURNAL

Discriminatory intervention is an exceptional case aimed at correcting the contested judgment or decision, and ensuring the proper application of the law, which distinguishes it from other means of appeal, as it is an essential basis for protecting the interests and rights of individuals, as judgments and decisions issued by criminal courts have the specificity of being the most prejudice to personal freedoms at a time when the judiciary seeks to achieve justice and work to balance between the public and private interest. The importance of discriminatory intervention lies in the fact that it is a legal means to ensure the monitoring of draft judicial rulings and to ensure that there are no errors in the application of the law, especially in cases where the convicted party or the prosecution cannot appeal by traditional methods of appeal.

The juristic consensus is that there four ways and methods for drafting Constitutions according to the circumstances that the state is going through there are the non-democratic methods. Which are represented by the grant and the contract, which are very old methods that are no longer used in drafting constitution, and there are the democratic methods, namely the constitutional referendum, which are methods that are compatible with the principles of democracy. however, after the emergence of the importance of international treaties in establishing the constitution of some countries that are going through exceptional circumstances of war and occupation, as the case of federal union, here it became necessary for constitutional scholars to acknowledge the existence of a fifth method for establishing constitutions, which is the method of international treaties.

The semantic significance of Qur\'anic context is considered one of the most important interpretive tools employed by exegetes in elucidating the meanings of the Holy Qur’an and deriving its rulings. This study, therefore, gains its importance from its focus on examining the contextual significance and its impact on the extraction of Qur’anic meanings. The meaning of a Qur’anic verse or phrase cannot be accurately understood without considering the preceding and following context in which it appears. The meaning conveyed through context holds various dimensions and offers numerous benefits, as pointed out by prominent scholars and exegetes of both early and later generations.

Environmental crimes constitute a significant topic that impacts life on Earth, whether humans, animals, plants, air, or water. Their scope is not limited to the local or regional level, but extends beyond that to take on an international dimension. Therefore, the current study sheds light on environmental crimes, both in terms of terminology and definition, as well as the forms of these crimes. It delimits the bases for considering such crimes as cross boundary, in addition to specifying the extent of environmental damage. The study also addresses the determination of international criminal responsibility in the event of their occurrence, in addition to the foundations for the establishment of this crime. The study ends up with a set of conclusions and recommendations.

This research Addresses civil wars and liberation wars. Because many countries hglsjulvm, when the colonized peoples were exploited for their human and material resources, and made these countries weak; and back ward in all aspects. This is a result of the colonialism of western countries, especially British colonialism, and the subsequent woes on the colonized counties. one of the Civil wars, the American Civil war and the Spanish Civil war, but for the struggle of the peoples and national consciousness, this kind of struggle against foreign colonizers has become a sacred national duty. which stirred the conscience of these Countries to be exposed to injustice, tyranny and oppression. National liberation movements became the slogan of this resistance, and the best evidence of this is the Algerian people’s resistance to the French Occupation and their forced evacuation from Algeria and the achievement of it.

This study deals with the analysis of the digital content of pages and sites that support the Palestinian cause on social media platforms،Specifically Facebook (Meta) in the context of Operation Al-Aqsa Flood, the study aims to highlight how these pages use social media as an effective tool in spreading awareness and stimulating international solidarity, and organizing protest activities The study was based on the analysis of a sample of Palestinian, Arab and international pages that dealt with the events of Operation Al-Afsa Flood and its various roles in strengthening digital resistance and spreading humanitarian stories and political analysis
She also reviewed the challenges faced by these pages, such as censorship and restriction by Facebook\'s management.
The results of the study showed that these pages are used successfully in publishing visual and documentary content that highlights the suffering of Palestinians. It also enhances international and local interaction through organizing solidarity campaigns and the use of unified hashtags. The study confirmed that social media has become an important element in Palestinian digital resistance, as it contributes to overcoming traditional media barriers and communicating the Palestinian narrative to a wider global audience.

The importance of the international specifications ISO (ISO - 9001/2008) through the product in the safe factory for manufacturing laundry soap (De Luxe brand) through the application of the ISO version in an effective and precise application in order to promote this required product with the quality performance in production of this agreed upon product is (De Luxe laundry soap) to be a high-quality product to be presented to customers.
The quality of the product is due to the organization in consolidating itself in the market to achieve a high level of quality to satisfy customers and obtain new customers and a geographical area in the local market for the purpose of controlling some of the challenges that it may face in the future. The research population consists of all workers in the Al-Maamoun factory for manufacturing soap (De Luxe). The community sample is (100), and because the research is based on an exploratory study of the opinions of a group of workers, the random research sample was represented by workers in the Al-Maamoun factory for manufacturing laundry soap (De Luxe brand), and it was determined the sample size included in the questionnaire, according to Stephen Thompson’s equation, amounted to (50) workers. The research consisted of four sections, including the first section (the methodology of scientific research and some previous studies), the second section (theoretical variables, including the ISO 9001/2008 version) and the product), and the third section (the applied section and the results of statistical analysis). The fourth section was (conclusions and recommendations) in addition to the sources. Arabic and foreign.

The research aims to study the impact of artificial intelligence on predicting future government expenditures in Iraq. The study covered 11 directorates in Ninawa province, and the research strategy was a case study of archive data for previous years of Ninawa province departments. The study used the artificial intelligence algorithm represented by the Perceptron network to predict the values of expenditures for future years. The research concluded that the use of artificial intelligence leads to rationalizing and improving spending in government units in Iraq. The researcher recommended encouraging government units to allocate financial resources to implement artificial intelligence technologies, including updating systems, programs, and devices used.

The rapid development of the Internet of Things (IoT) and wireless communication networks has made improving data routing between nodes increasingly important. These networks face several challenges. Moreover, advanced optimization is used, most notably the Genetic Algorithm (GA), due to its ability to explore multiple solutions and improve them over successive generations by working with routing and evaluation. This work aims to develop and establish a model based on the GA to improve path routing in single-object wireless networks, taking into account four main criteria: latency, throughput, reliability, and energy consumption by using an algorithm. The results of this work show that the proposed model will provide significant improvement and balance in all criteria compared to the traditional methods.

Tissue immune homeostasis is essential for the prevention of pathological inflammation and the preservation of organ integrity. However, when immune regulation at the tissue level is disrupted, it can trigger or aggravate a wide array of diseases, including cancer and systemic inflammatory disorders. This review looks into the pathophysiology of autoimmune and chronic systemic disorders, as well as the emerging understanding of how tissue-specific immune dysregulation contributes to oncogenesis, tumor progression, and metastasis. Dysfunctional interactions between tissue-resident immune cells, stromal components, cytokine networks, and the local microenvironment are at the core of this dysregulation. The failure of immune tolerance, chronic low-grade inflammation, and aberrant activation of immune checkpoints are identified as critical mechanisms. Additionally, the role of tissue-specific immune niches in shaping disease outcomes emphasizes the need for localized therapeutic approaches. Understanding the molecular and cellular basis of tissue immune dysregulation opens new insights into targeted immunotherapies and precision medicine for both malignant and non-malignant diseases.

Currently, information security is a difficult issue due to growing information capacity and transmission procedures. One encryption method that can provide security above and beyond the brute-force limit is honey encryption (HE). Ultimately, HE becomes a part of everyday systems. Most researchers use improved encryption and decryption for HE schemes to improve information security domains since traditional HE has several drawbacks. An overview of current developments in the Honey Encryption scheme will be provided in this article. HE\'s drawbacks and difficulties are outlined and examined. Specific of the solutions suggested have been introduced.

This paper intends to explore mother’s extravagant love which negatively shapes the son’s emotional responses and, consequently, diverts his emotional development from its fulfilling normal course. In exposing this governing idea of possessive love which deplorably informs the human predicament in Sons and Lovers and, which organises the narrative text, Lawrence recognises that which eventually encourage human emancipation. It is true that Lawrence has not yet discovered his technique in Sons and Lovers in the way Schorer argues for - he frequently falls on colourful depiction of setting, on natural phenomena to reveal psychic states, on earnest qualifications that verge on preaching … etc. - but it is equally true that he has been thematically and creatively aware of that which distorts human life and makes man impotent. The rejection of negative states such as dependence, possessiveness, rationalism etc, Lawrence argues, will realise that rhythm of life which makes man wholesome.

Stroke is one of the most serious medical conditions that requires rapid and accurate diagnosis to avoid its fatal complications. The use of Deep Learning (DL) techniques contributes to enhancing the accuracy of detecting strokes in their early stages, enabling faster medical intervention and reducing long-term damage. In addition to early stroke detection, maintaining the confidentiality of patient information is vital to ensuring trust and protecting sensitive data. DL techniques also help detect unauthorized access or manipulation of patient data, enhancing digital security and ensuring compliance with healthcare privacy standards. In this paper, a precise and safe DL-based medical system for the detection of strokes is proposed. The design includes two stages. First, propose a high-accuracy DL learning algorithm to detect Stroke, which is achieved through a hybrid CNN-LSTM algorithm. The second stage is represented by maintaining the security of the proposed medical system by suggesting an efficient DL algorithm, which is attained using a lightweight Shallow Deep Neural Network (SDNN) algorithm. The performance evaluation of the two former stages, accuracy, security, and memory footprint, has been achieved. The simulation results demonstrate that the proposed hybrid CNN-LSTM algorithm achieves superior performance in stroke detection, reaching an accuracy of up to 99.6 percent when evaluated on the AHA stroke dataset. This performance surpasses that of standalone CNN and LSTM models. In terms of cybersecurity, the SzDNN algorithm also proves effective, maintaining a high detection rate of up to 96.8 percent using the NSL-KDD dataset. These findings highlight the model\'s strength in both accurate medical diagnostics and reliable network threat detection.

E-commerce represented one of various new technologies that triggered with development of the internet. This causes the security aspect of e-commerce to be one of important factors, especially to prevent unwanted things such as data leaks and financial losses. Authentication is a critical aspect of securing digital systems and protecting user data. This paper reviews and compared three primary authentication methods: single factor authentication (SFA), two-factor authentication(2FA), and multi-factor authentication (MFA). SFA, the simplest method, relies on a single layer of security, such as passwords or PINs, but is highly vulnerable to modern cyber threats. 2FA enhanced security by combining two distinct factors, such as a password and One-time password (OTP), reducing the risks of credential theft. MFA further strengthens authentication by incorporating multiple layers, including biometric and contextual elements, making it the most secure approach but also the most complex and resource intensive. The discussion highlights the trade-offs between these methods in terms of security, usability, scalability, cost, and risk mitigation. While SFA may suffice for low-risk applications, MFA is essential for environments requiring robust security. The study conclude that the choice of authentication method should depend on a specific use case, balancing security needs with user convenience and organization resources.

Crowd management plays a vital role in ensuring safety, efficiency, and resource optimization in environments such as public events, transportation hubs, shop-ping malls, and workplaces. Traditional people counting methods, including manual observations and sensor-based approaches, often suffer from limitations in accuracy, scalability, and adaptability to dynamic conditions. This research pre-sent a real-time people counting system utilizing deep learning techniques, specifically the YOLO (You Only Look Once) object detection framework. The proposed system processes video streams to accurately detect and count individuals, offering a robust and automated solution for crowd analysis. By leveraging YOLO’s high-speed processing and accuracy, the system effectively identifies people within complex and varying environments, addressing challenges such as occlusions, lighting variations, and high-density crowds. Experimental evaluations demonstrate the system\'s strong performance, achieving an accuracy of 95% in static environments and 87% in dynamic conditions. These results highlight the model’s reliability, efficiency, and potential applications in real-time crowd monitoring, security surveillance, and urban planning. Future improvements include integrating advanced tracking algorithms and multi-camera setups to enhance detection accuracy and consistency across different perspectives. This research un-derscores the transformative potential of deep learning in crowd management, paving the way for smarter, safer, and more responsive public spaces.

Automated handwriting recognition is a crucial element in numerous applications across diverse fields. This problem has been the subject of significant investigation during the past three decades because to its complex nature. Research has mostly concentrated on the identification and interpretation of handwritten text in Latin languages. There is a scarcity of research conducted on the Arabic language. Therefore, it is crucial to build Children\'s Arabic handwriting recognition software and apps. In this study, we offer three models for the recognition of children\'s Arabic handwriting using deep learning. In this paper, an ensemble learning is employed for the Recognition Arabic handwriting, the proposed ensemble learning combined three model, the first with three convolution layer and the second with four convolution layer and the third model is CNN using BI LSTM. Hijja, a recent collection of handwritten Arabic by children that was gathered in Saudi Arabia, is used in training process. The most relevant work achieves less accuracy from our models for the same data sets. The three models achieve accuracies 87,88, and 89, when they work independently. The performance enhanced by use the ensemble and soft voting that increases the accuracy up to 92% which better than some works selected from the literature.