FPGA-Based Adaptive Encryption Architecture for Secure and Low-LatencyV2X Communication in 5G Networks
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.
Optimal PID Controller Design for 3-DOF Robot manipulator
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 (<!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>PID</m:r></m:oMath><![endif]--> <span style="font-size: 11.0pt; line-height: 115%; font-family: 'Aptos',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: 'Times New Roman'; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: Arial; mso-bidi-theme-font: minor-bidi; position: relative; top: 5.5pt; mso-text-raise: -5.5pt; mso-font-kerning: 0pt; mso-ligatures: none; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;"><!-- [if gte vml 1]><v:shapetype id="_x0000_t75" coordsize="21600,21600" o:spt="75" o:preferrelative="t" path="m@4@5l@4@11@9@11@9@5xe" filled="f" stroked="f"> <v:stroke joinstyle="miter"/> <v:formulas> <v:f eqn="if lineDrawn pixelLineWidth 0"/> <v:f eqn="sum @0 1 0"/> <v:f eqn="sum 0 0 @1"/> <v:f eqn="prod @2 1 2"/> <v:f eqn="prod @3 21600 pixelWidth"/> <v:f eqn="prod @3 21600 pixelHeight"/> <v:f eqn="sum @0 0 1"/> <v:f eqn="prod @6 1 2"/> <v:f eqn="prod @7 21600 pixelWidth"/> <v:f eqn="sum @8 21600 0"/> <v:f eqn="prod @7 21600 pixelHeight"/> <v:f eqn="sum @10 21600 0"/> </v:formulas> <v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"/> <o:lock v:ext="edit" aspectratio="t"/> </v:shapetype><v:shape id="_x0000_i1025" type="#_x0000_t75" style='width:18.75pt; height:16.5pt'> <v:imagedata src="file:///C:/Users/MAANKH~1/AppData/Local/Temp/msohtmlclip1/01/clip_image001.png" o:title="" chromakey="white"/> </v:shape><![endif]--> ) is used. The Intelligent Particle Swarm Optimization (<!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>PSO</m:r></m:oMath><![endif]--> <span style="font-size: 11.0pt; line-height: 115%; font-family: 'Aptos',sans-serif; mso-ascii-theme-font: minor-latin; mso-fareast-font-family: 'Times New Roman'; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: Arial; mso-bidi-theme-font: minor-bidi; position: relative; top: 5.5pt; mso-text-raise: -5.5pt; mso-font-kerning: 0pt; mso-ligatures: none; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;"><!-- [if gte vml 1]><v:shape id="_x0000_i1025" type="#_x0000_t75" style='width:20.25pt;height:16.5pt'> <v:imagedata src="file:///C:/Users/MAANKH~1/AppData/Local/Temp/msohtmlclip1/01/clip_image003.png" o:title="" chromakey="white"/> </v:shape><![endif]--> ) 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.
Kinematics and Dynamic of Robot manipulator.
Blockchain for Enhancing Trust in E-Government Services
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.
GIS-Based Entropy–TOPSIS Ranking of Centralized Rainwater Harvesting Sites Using DEM-Derived Hydrological Indices: Karbala Province, Iraq
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.
Authentication Approach for Sensitive Data in Block Chain –non -fungible token Environment based on Simon Encryption and Steganography Techniques
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).
Blockchain Architecture for Securing Continuous Data Streams in Healthcare IoT Systems
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
Enhancing Covert Communication Systems through Deep Steganography
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.
Treason and Compassion” in Flaubert’s Madam Bovary
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)
The Effect of Ephedrine and Phenylephrine on the Apgar Score of Newborns After Cesarean Section under Spinal Anesthesia: A Comparative Study
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.
Keywords: Ephedrine, Phenylephrine, hypotension during cesarean section, Apgar assessment
The role of artificial intelligence in developing radio content
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.
Building a Proposed Structural Model to Identify the Most Influential Factors in the Success of Machine Learning Applications in the Iraqi Hotel Sector: A Field Study of Four-Star and Deluxe Hotels in Baghdad
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.
Organizational Culture and its Impact on Human Capital: An Analytical Study at the General Company for Electric power Production/Central Region
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.
the General company for electrical power/ central region
, retaining human talent within the organization
Cybersecurity Threats to the Iraqi Hospitality Sector and Mechanisms for Countering Them: An Analytical Study of Iraqi Hotel Organizations
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.
The role of organizational Creation and its impact on academic leadership – an exploratory study of the opinions of a sample of faculty members at the College of Tourism Sciences, Al-Mustansiriya University
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.
deep Learning for Arabic Handwriting Recognition System
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.
Real-time People Counting with Deep Learning: A Solution for Crowd Management
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.
Exploring Authentication Techniques: A Comprehensive Review
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.
Design of a Secure and Accurate Deep Learning-Based Medical System for Stroke Detection
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.
Mother’s Love as Impediment to the Sons’ Emotional Development in Sons and Lovers
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 [1] - 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.
Honey Encryption Techniques: Strengths, Limitations, and Challenges
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.
The Role of Tissue Immune Dysregulation in Cancer and Systemic Diseases
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.
Single-Object Multi-Path Routing in Multi-Objective Networks Using Genetic Algorithm
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.
The impact of artificial intelligence on predicting future government expenditures An applied study in the departments of Nineveh Governorate.
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 extent to which the requirements of the international standard (ISO-9001 / 2008) are met and their impact on the product (A survey sample of the opinions of a sample of employees at the Al-Mamoun factory which manufactures the De Luxe soap product)
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.
Availability of ISO requirements for the product in the organization
Social media coverage of developments in the Palestinian cause. (Operation Tufan of Al-Aqsa) and its role in activating relief and humanitarian support activities. (Facebook "Meta" as an example).
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.
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.
Protecting the environment criminally from pollution
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.
The Semantic Significance of Qur'anic Context and Its Role in Deriving Meanings
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.
The impact of international law on the emergence of constitutions
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.
Discriminatory Intervention in Criminal Proceedings (A Study in Light of Legal Texts and Judicial Applications
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.