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Deep Learning Approaches for Retinal Disease Identification in Fundus Imaging: A Comprehensive Overview
Full text linkVision impairment is becoming a major health concern, especially in elderly people. While in the medical field, manually detecting ocular pathology has significant difficulty. Therefore, deep learning diagnostic techniques are widely used for identifying eye diseases and play a crucial role in diagnosing vision-related problems. Examination of fundoscopy allows for analyzing eyes for diagnosis of eye diseases, including Diabetic retinopathy (DR), Cataracts, Glaucoma, Age‑related macular degeneration, Pathologic Myopia, and more. In this paper, we propose a concise review of introducing most of the DL, hybrid, and ensemble models utilized for the purpose of identification and classification of eye diseases. Various datasets, feature extraction techniques, and metrics for performance evaluation are discussed. The chosen papers come from conferences and scholarly publications published from 2019 to 2024. We evaluate the performance of chosen researches using different datasets, the most common ones include ocular disease intelligent recognition, Indian DR image dataset, EyePACS, methods to evaluate segmentation and indexing techniques in the field of retinal ophthalmology, methods to evaluate segmentation and indexing techniques in the field of retinal ophthalmology-version 2, DIARETDB, Structured analysis of the retina, high-resolution fundus, digital retinal images for vessel extraction, online retinal fundus image dataset for Gl analysis and research, retinal fundus multi-disease image dataset and Kaggle datasets. The detection studies that have been reviewed show that the accuracy of these approaches varies between 73% and 99%, the sensitivity ranges from 69% to 99% and precision is between 89% and 99%. The results show that great accuracy is consistently achieved with DL algorithms compared to traditional Machine learning approaches. However, there are still some challenges and limitations remaining including excessive resource consumption and over-fitting due to dataset size and diversity issues. This review offers useful insight for researchers and healthcare professionals to comprehend AI technologies properly for the detection, classification, and diagnosis of retinal diseases. We succinctly summarize the methodologies of all the chosen studies and focus on the elements that define the aim of the studies
Forecasting of the Infant Mortality Rate in Iraq
Full text linkThis study investigates applying the GM(1,1) model to forecast the infant mortality rate (IMR) in Iraq from 2025 to 2034, utilizing historical data spanning 2015–2024. The findings indicate a consistent decline in IMRs during the analyzed period, reflecting effective public health interventions. The model’s parameters were estimated using the Ordinary Least Squares method, revealing an intercept of 0.0278 and a slope of 26.7693. The forecasting accuracy of the GM(1,1) model was exceptional, demonstrated by a Mean Absolute Percentage Error of only 0.2869% and a precision rate of 99.7131%, categorizing the forecasts as highly accurate. Projected IMRs show a continued decline, decreasing from 20.55 deaths per 1000 live births in 2025 to approximately 16.00 by 2034. These results underscore the utility of the GM(1,1) model in providing reliable forecasts to inform health policy and intervention strategies aimed at improving maternal and child health in Iraq
Environmental Impact Assessment of Sulaymaniyah Solid Waste Dumpsite Using Leachate and Soil Pollution Indices
Full text linkGlobal urban population is rising that resulting more waste production. Globally, municipal solid waste (MSW) generation considered as a serious threat on the global environment and human wellbeing. Leachate from solid waste dumps poses significant environmental and health risks, particularly due to contamination in soil and water caused by heavy metals. In this study, environmental impacts of MSW are assessed and estimated for Sulaymaniyah city, KRG, Iraq, which is located at 10 km south of the city in the Tanjaro dumpsite. Soil and leachate samples were collected and analyzed for various expected pollutant, to assess the environmental contamination through using pollution indices. For assessing the leachate pollution index (LPI), some parameters were determined, such as potential of hydrogen (pH), total dissolved solid, biochemical oxygen demand (BOD5), and chemical oxygen demand (COD), and chloride (Cl). LPI value (20.1377) is much higher than the related standards. High concentrations of metals, such as cadmium (Cd), iron (Fe), manganese (Mn), copper (Cu), chromium (Cr), nickel (Ni), and zinc (Zn), found in the soil near the site, however, the contamination level is not serious based on the checked pollution indices, such as pollution index (PI) and nemerow PI (PInemerow). PI for Cd, Fe, Mn, Cu, Cr, Ni, and Zn were 0.158, 0.024, 0.088, 0.176, 0.613, 0.786, and 0.225, respectively, whereas, PInemerow value was 0.606, which classified the soil as a non-contaminated soil. Results of this study reveals that the Tanjaro dumpsite needs an engineered landfill and decent leachate treatment right away; since present conditions far over safe limits and threaten soil and water quality
The Effectiveness of Geographic Information Systems in Sustainable Urban Planning in Iraq: An Analytical Study of Experts’ Opinions
Full text linkThis descriptive analytical study assesses the effectiveness of geographic information systems (GIS) in supporting sustainable urban planning in Iraq. The study aims to gather and analyze the opinions of specialists and experts in urban planning, environmental management, and GIS across various cities in Iraq. A sample of 100 experts from Baghdad, Basra, Erbil, Mosul, and Najaf was selected based on their experience and competence in projects utilizing GIS. Data was collected through a structured questionnaire consisting of closed-ended questions and a Likert scale, focusing on four main dimensions: Experts’ knowledge and use of GIS, the effectiveness of GIS in urban planning, its role in achieving sustainable development goals (SDGs), and the challenges faced in implementing these systems in Iraq. Data analysis was conducted using the Statistical Package for the Social Sciences statistical analysis software. The results showed that most experts had a good level of knowledge of GIS and considered it an effective tool in improving the accuracy of urban planning and facilitating decision-making. However, some challenges were identified, such as the lack of updated data and the technical capacity to use complex software. The study also indicated that GIS significantly contributes to achieving SDGs, especially in the areas of environmental sustainability and monitoring urban expansion. However, there is a need to improve institutional support and provide updated data and financial resources to implement GIS more effectively. Regarding statistical analysis, the results of the analysis of variance test showed significant differences in the effectiveness of GIS based on experience level, with more advanced experts showing greater effectiveness in using the system. The t-test revealed a significant difference between those who received formal GIS training and those who did not, with the trained group demonstrating higher knowledge levels. Finally, the correlation analysis results indicated a positive relationship between GIS knowledge and its effectiveness in urban planning. This study provides valuable insights into the effectiveness of GIS in enhancing sustainable urban planning in Iraq, highlighting the challenges faced in its implementation in this context
Medical Medical Waste Management and Treatment Techniques: Insights from Sulaymaniyah Governorate, Kurdistan Region- Iraq
Full text linkInadequate medical waste management (MWM) has serious consequences for the environment and human health. Therefore, developing an optimal MWM system in healthcare facilities is of great importance . Unlike previous research, this study aimed to evaluate the MWM techniques practiced at private hospitals in Sulaymaniyah City. Qualitative and quantitative data collection and analytical methodologies were employed. Direct observation was conducted according to the guidelines established by the World Health Organization (WHO), along with semi-structured interviews for qualitative data collection. The quantitative data on waste generation rates for the present study were derived from the pre-existing records maintained by the General Directorate of Health in Sulaymaniyah. The statistical and graphing software GraphPad Prism version 9.5.1 was used to analyze the data. The analysis revealed that the quantity of the hospitals’ monthly medical waste generation ranged between 274.0 ± 167.5 kg and 1212 ± 391.6 kg. Moreover, monthly medical waste generation per bed per hospital ranged between 20.20 ± 6.527 kg and 3.177 ± 0.8819 kg. It was also found that the daily generation rate ranges between 0.0576 and 0.827 kg/bed. Concerning management practice, all the studied hospitals have a separation system, a collection system, on-site temporary storage, and personal protective equipment. Meanwhile, 83% of the studied hospitals deliver training courses for their waste management staff. In addition, the three treatment techniques practiced are autoclave shredder systems, incineration, and deep burial
Hybrid Encryption and Steganography for Secure Image Data Hiding
Full text linkSecure communication is becoming increasingly important in modern digital societies, where sensitive information is frequently exchanged over open networks. Traditional steganographic and cryptographic methods alone often fail to achieve a balance between imperceptibility, capacity, and robustness. To address these limitations, experimental results show a Peak Signal-to-Noise Ratio (PSNR) of 68 dB, indicating excellent visual quality, and a data-hiding capacity of 15 bits per pixel. It provides higher data payloads than conventional steganographic methods (typically 1–2 bpp) while still maintaining a very high PSNR of 68 dB. Furthermore, we highlight the improvements over existing works in terms of imperceptibility, robustness, and security. This revision makes the abstract more comprehensive and self-contained. Comparative analysis further highlights the superiority of this method over conventional techniques, offering an optimal balance between security, imperceptibility, and embedding capacity
Cascading Overtopping-Induced Dam Failures in a Transboundary Basin: Hydrodynamic Modeling from Gawshan to Darbandikhan Dam
Full text linkThis study investigates the cascading failure potential of a multi-dam system in the transboundary Diyala (Sirwan) River basin, spanning Iran and Iraq. Using a two-dimensional hydrodynamic model developed in Hydrologic Engineering Center’s River Analysis System 6.6, the study simulates overtopping- and piping-induced breach scenarios at Gawshan Dam and assesses their propagation through downstream reservoirs including Zhave, Daryan, and Hirwa, culminating at Darbandikhan Dam. The results highlight the formation of a compound flood wave that exceeds crest elevations, particularly under overtopping scenarios, leading to overtopping failure at Darbandikhan Dam despite emergency discharge operations. Scenario 1, representing full reservoir conditions and sequential overtopping failure, was identified as the most severe. The model outputs show a rise in water surface elevation from 485.0 m to 495.5 m within 412 min at Darbandikhan Reservoir, causing structural overtopping. Extensive inundation impacts both Iranian upstream settlements and Iraqi downstream communities, submerging over 20 villages and 80 km2 of agricultural land. The findings underline the need for transboundary coordination, reservoir reoperation protocols, and updated Emergency Action Plans to mitigate the risk of cascading dam failures in seismically active regions
Enhancing Oat Yield and Yield components by Salicylic Acid in Different agro-ecosystem
Full text linkClimate elements including temperature, humidity, and precipitation all are effects on crop growth and development especially in the arid and semi-arid areas of Northern parts of Iraq. Recently, the stresses of global climate change appear as an effective challenge, so, this study was carried out at two different locations in the Northern part of Iraq; Koya/Erbil and Altun Kopru/Kirkuk to study the effects of salicylic acid (SA) (0, 100, 200, and 300 ppm) twice as foliar spraying on five oat varieties. Results indicate that the Koya district environment significantly improved most studied characteristics, except for panicle number, compared to Altun Kopru. Except the harvest index (HI) which was non-significant, 100 and 200 ppm of SA improved significantly all studied characteristics compared to the control and 300 ppm of SA. Kangaroo, ICARDA Short, and ICARDA Tall varieties were the tallest plants (85.969, 83.469, and 82.833 cm) respectively. Each of Possum and ICARDA Short varieties were superior in panicle number, seed yield, biological yield, and straw yield. Kangaroo variety has the lowest harvest index (42.695%)significantly compared to all other varieties, whereas ICARDA Short variety was the lowest in panicle grain weight(0.898 g/panicle-1)
Enhanced Integer-Based Homomorphic Encryption Scheme with Windowing Mechanism for Securing Electronic Health Records
Full text linkThe frequent breaches of healthcare data annually make robust encryption mechanisms crucial, especially those that preserve the usefulness of the data while ensuring privacy. This study addresses specific integer-based homomorphic encryption systems and their critical vulnerabilities. The vulnerability identified in these systems is the possibility of decryption using other values, such as factors or primes, instead of the claimed unique secret key. We propose an enhanced cryptographic formula to address this vulnerability using a double random value technique that ensures decryption depends solely on the designated secret key. We also apply a windowing technique for prime selection to enhance the key properties against pattern detection attacks. Security analysis shows that the enhanced system prevents decryption using values other than the dedicated key while maintaining additive and multiplicative homomorphism. Performance evaluations show that the improved system maintains decryption times and ciphertext expansion ratios similar to the original system, with a reasonable decryption time reduction. Statistical testing results using the National Institute of Standards and Technology tests demonstrate the robustness of the proposed approach compared to the original, with the windowing technique exhibiting superior randomness properties
Exploring Post-Quantum Cryptography: Evaluating Algorithm Resilience against Global Quantum Threats
Full text linkCryptographic algorithms perform a vital part in protecting information in general and safeguarding digital platforms. Nevertheless, improvements in quantum computing pose important concerns to traditional cryptographic approaches, demanding the development of quantum-resistant explanations. This study offers an inclusive investigation of post-quantum cryptographic algorithms, assessing their flexibility, competence, and practicality in justifying quantum risks. Through an equivalent approach, the research identifies optimistic applicants for upcoming cryptographic standards. Moreover, the study highlights the international essential for embracing these algorithms to ensure secure communication and data protection in the quantum era. These conclusions aim to notify the progress of strong cryptographic systems that address the appearing objections of quantum technologies