International Journal of Innovations in Science & Technology
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Development of A Web based GIS Solution for Flood Inundation Mapping and Assessment in Lahore, Pakistan
Get PDFIntroduction
Geographic information system (GIS) is a strong tool in flood hazard mapping, mitigation, and management. GIS-based approaches provide the wayforward to measure the flood inundation. Integration of web technologies with GIS (Web-GIS) is quite significant to accomplish the aim.
Methodology
In this research, HEC-RAS 1D was used to map the flooded areas around River Ravi at Lahore. The output of HEC-RAS with Web-GIS stack were used to build the interactive flood measuring tool. The Web-GIS stack used for this study was based on Geo Server, PHP, HTML, CSS, and JavaScript. Geo Server provides the OGC implemented standards with vendor specific capabilities like WMS Animator to animate the flood inundation on the User-Interface (UI) and extent animation to make visual interpretations. CQL filter is vendor specific capability in Geo Server used to measure the flood inundation.
Results
The outcomes of HEC-RAS are handy enough to measure, map and present the damages not only to analyst but also to the layman. The working and animated layers are shown in result section of this research.
Conclusion
This web-based flood inundation is robust, user-friendly, and expandable for more features, scenarios, and conditions. This research concludes that visual and web-based data is handy to understand for common person/intellectuals
Identification of Real and Fake Reviews Written in Roman Urdu
Get PDFThe evolution of e-commerce has made reviews a crucial metric for judging the quality of online products or services. These reviews have a significant impact on the decision of the customer. Positive review catches more attraction while negative reviews impact sales of the product. Nowadays, deceptive reviews are being deliberately posted on e-commerce websites and social media stores to promote the product by illegal means. These reviews are sometimes posted in different local languages to build a fake virtual reputation among local customers. Thus, fake review detection is a wider area for ongoing research. This paper proposes several machine-learning approaches to detect fake reviews written in Roman Urdu. Furthermore, a comparative analysis of the performance of nine machine learning models on the given dataset is performed. The dataset is crawled from different e-commerce sites in Pakistan. The results show that the existing Support Vector Machine outperforms the rest of the models with an accuracy of 82%
Flood Inundation Modeling and Damage Assessment in Lahore Using Remote Sensing
Get PDFIntroduction:
Ravi River has a great contribution to the glorious history of Lahore City, the second biggest city in Pakistan. But similar to all rivers of Pakistan, River Ravi occasionally experiences extreme floods. During the past 100 years, two extremely high floods created devastation in Lahore City, which caused enormous loss of properties and lives. To save the main metropolitan areas of Lahore in both these floods, the Shahdara Breaching section, on the western bank of the river, was operated. The potential of loss due to floods has increased even more owing to the rise in population, industrialization, and spring of unplanned settlements in the floodplain of the river.
Importance of Study:
This research provides a solution that has the potential for long-term effects in flood management, hygienic improvement of the area, planned urban development around the river, and improvement of sub-surface water quality.
Novelty Statement:
The present study is focused on determining the flood damage assessment using advanced geospatial techniques with HEC-RAS applications.
Materials and Methods:
The reach of the Ravi River is from Shahdara to Balloki. Flood frequency analysis was performed to calculate a flood return period of five and fifty years. Hydraulic modeling of the river on HEC-RAS is used to find river capacity, its Validation, calibration, assessment of hydraulic capacity, flood inundation extent, and depth analysis.
Results:
It is concluded that a flood of 3643.97 cumecs magnitude corresponds to 5 years return period and 7406.699 cumecs magnitude corresponds to 50 years return period. If the same phenomena occur in a repeating manner, then the built-up settlement near Ravi can meet alarming threats. According to the maximum likelihood classification, the damage assessment was mapped wherein the results show that the buildup area was 15657 acres, the water body was 7059.246 acres, the cultivated area was 38395.3 acres, and uncultivated 59464.51 acres were affected.
Conclusion:
The solution can also address the problems arising due to changes in river course and depletion of natural habitat.
Recommendations:
However, along the Lahore City, the required width is not available. In this condition, an engineering solution is mandatory to pass the flood. Channelization can be proposed to create the width of the river. The reclaimed land should be used for high-quality urban development to increase revenues. For the sake of channel stability, a detailed sediment study should be done
Quantitative Analysis of Image Enhancement Algorithms for Diverse Applications
Get PDFThis research paper introduces a comprehensive comparative analysis of prominent image enhancement algorithms, including Histogram Equalization, Adaptive Histogram Equalization, CLAHE, Gamma Correction, and Unsharp Masking. In the realm of digital image processing, image enhancement plays a crucial role in various applications such as medical imaging, remote sensing, surveillance, and computer vision. Addressing the significance of this research, we present an evaluation of these algorithms using key metrics: Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Structural Similarity Index (SSIM), Contrast Improvement, and Sharpness Improvement. Our methodology encompasses dataset collection, algorithm implementation in MATLAB, and systematic performance evaluation. The results highlight the unique strengths and trade-offs of each algorithm. Histogram Equalization demonstrates moderate improvement in image quality, while Adaptive Histogram Equalization excels in preserving image details despite introducing some distortion. Contrast Limited Adaptive Histogram Equalization strikes a balance between enhancement and computational efficiency. Gamma Correction proves effective for specific adjustments but may compromise overall image quality. Notably, Unsharp Masking stands out with superior sharpness improvement while maintaining image fidelity. In conclusion, the choice of algorithm should be aligned with specific task requirements and the desired balance between image quality and enhancement goals. Considering these outcomes, Unsharp Masking emerges as a promising choice, demonstrating exceptional performance across multiple metrics. This research provides valuable insights for practitioners and researchers seeking to optimize image enhancement algorithms for diverse applications
Lossy Image Compression Unveiled: A Comprehensive Evaluation of DCT, Wavelet Transform, and Vector Quantization
Get PDFThe increasing demand for efficient image storage and transmission has driven extensive research into lossy image compression algorithms. This paper presents a comprehensive comparative analysis of three prominent lossy image compression techniques: Discrete Cosine Transform (DCT), Wavelet Transform, and Vector Quantization (VQ). Employing a diverse dataset and assessing their performance through key metrics, including Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Squared Error (MSE), Bitrate, and Computational Complexity, we meticulously evaluated these techniques across dimensions of image quality, compression efficiency, and computational demands. DCT emerges as a standout performer in preserving image quality, closely followed by Wavelet Transform. While Vector Quantization demonstrates efficiency in compression, its limitations become apparent in the realm of image quality preservation. The comparative analysis unequivocally positions DCT as the optimal choice for applications prioritizing image quality. This preference is substantiated by its remarkable PSNR and SSIM scores. Despite DCT not being the most computationally efficient, its ability to strike a crucial balance between compression efficiency and image quality renders it a well-rounded and effective solution. In conclusion, this research provides valuable insights into the comparative performance of DCT, Wavelet Transform, and VQ in the context of lossy image compression. The findings underscore DCT\u27s superiority in image quality preservation, offering practical guidance for decision-makers in the field. The paper contributes to informed choices based on specific application requirements and emphasizes the pivotal role of DCT as a well-rounded and effective solution
Prediction of Political Instability by Using Pre-Trained Neural Networks
Get PDFThis research aims to enhance and optimise the decision-making process in the political science domain by exploring the potential of machine learning. The aim was to create a pre-trained neural network to predict the political instability in any country (a prediction that aids decision-makers in handling government affairs and crisis prevention). We constructed four pre-trained neural networks, each tailored to a specific indicator (Human Development Index, Currency Strength Index, Tax to GDP Ratio, and Fragile States Index). These indicators are selected based on their strong correlation and how their concurrent performance impacts the political landscape of any country. The neural networks exhibited exceptional performance, achieving accuracy rates above 85%. The model built on the FSI demonstrated an astonishing accuracy of 99.67%, underscoring its potential for comprehensive assessments. The prospect envisions amalgamating the outputs of these pre-trained neural networks into a unified, deep-learning network, poised to yield collective decisions and recommend policy initiatives
Applications of Artificial Intelligence in Various Traits of Life
Get PDFKnowledge Administration (KA) is the method by which an organization creates, shares, applies, and manages its information and knowledge. Although conventional KA has evolved throughout the years, documentation remains its bedrock principle. The considerable shift towards remote and hybrid working, however, has shown the limitations of conventional practices. Artificial intelligence (AI) will close these knowledge gaps and alter the ways in which KA is converted and knowledge is managed. This article reviews research on artificial intelligence (AI) and Knowledge Administration (KA), focusing on how AI can help to improve their KA strategies. In light of the existing literature critical review analyses the most up-to-date methods by analyzing both theoretical and applied works. In addition, the analytical framework presented below is useful for imagining new lines of inquiry and ways to enhance the quality of existing ones
Significance of Education Data Mining in Student’s Academic Performance Prediction and Analysis
Get PDFData Mining (DM) is relevant to extract the hidden patterns from the voluminous amount of the data. Applying DM, in education is an evolving interdisciplinary research domain, which is also called as educational data mining (EDM). At present, student data about their academics is available to identify important hidden trends to be explored for enhancing student academic performance. In higher education, forecasting student success is essential for helping with course selection and creating individualized study schedules. It helps instructors and managers keep tabs on students, ensure their development, and modify training programs for the best results. Growth and development of any nation depend on educational institutions since they are fundamental social foundations. It is now feasible to use past data for effective learning and prediction of future behavior in a variety of troublesome areas thanks to the development of DM as a potent approach. Educational institutions may make wise judgments and promote improvements in the education sector by utilizing the possibilities of DM supported EDM approaches. It is feasible to pinpoint improvement areas and direct upcoming skill development by examining pupils\u27 performance on various academic evaluations. Furthermore, this procedure lessens the frequency of official warnings and ineffective student expulsions, fostering a more encouraging and fruitful learning atmosphere. In this work, a unique algorithm that combines classification and clustering approaches to predict students\u27 academic success has been suggested. Real-time student datasets from several academic institutes in higher education were used to test the suggested approach. The findings show that the suggested model worked well for predicting students\u27 academic achievement
Comparative Analysis of Urban Sprawl through KNN and Random Forest Classification (RFC) ML Techniques
Get PDFThe majority of optimization strategies fail to take into account the dynamic impact of urban sprawl on the spatial criteria that underlie decision-making processes. Furthermore, the integration of the existing simulation methodology with land use optimization techniques to arrive at a sustainable judgment regarding the appropriate site involves intricate procedures. The urban heat island phenomenon is a prominent consequence of urban expansion and human activities, leading to elevated temperatures within cities compared to their rural surroundings. The extent of sprawl was estimated through ML algorithms and it was revealed that RFC provided promising results that were near to statistics by various administrative authorities. Urban vegetation plays a crucial role in countering the urban heating effect by providing cooling mechanisms through evaporation and shading. In this context, a study was conducted in Allama Iqbal Town, Lahore, focusing on the assessment of land use changes, as well as the analysis of Normalized Difference Vegetation Index and Land Surface Temperature data for the years 2000, 2010, and 2023, obtained from Landsat 5 and Landsat 8 satellite imagery. The findings reveal significant land use changes of 7.52% (36.2 km2) in the study area. The built-up areas expanded by 50.76%, while smart green spaces decreased by 48.30%. The relationships between NDVI and LST demonstrate a robust negative relationship (R² = 0.99). This research underscores the potential of utilizing GIS and remote sensing techniques to inform urban planning, decision-making, and policy formulation, ultimately contributing to the creation of sustainable urban environments in Allama Iqbal Town
Variability of Geomorphological Characteristics and the Altered Hydrological Regime of the Upper Indus Basin, Pakistan
Get PDFThe administration of watersheds holds significant relevance in the field of water resources engineering and management. The main objective of this research is to assess the geomorphological attributes of the Upper Indus Basin (UIB) in Pakistan, with a particular emphasis on its hydrological phenomena. The demarcation of the boundaries of the 21 sub-basins within the UIB was achieved by employing ArcGIS software. The findings indicate that the subbasins demonstrate a range of drainage patterns, varying from sub-dendritic to dendritic. This suggests that there is a consistent texture and absence of structural influence within the subbasins. The research identified a range of stream orders, extending from 3.76 to 365.73 km, indicating a diversity in bifurcation ratios that spans from 3.00 to 5.40. The findings of this investigation suggest the presence of geologic formations that offer favorable conditions. The total length of streams and the number of stream segments demonstrate an upward trend in first-order streams, whereas they decline as the stream order advances. The Drainage Density (DD) of all sub-watersheds has a variation ranging from 0.170 to 0.231 km-1, indicating the presence of regions characterized by materials with notable resistance and porosity. The observed low drainage intensity in these watersheds suggested that the capacity to remove surface runoff is insufficient, rendering them susceptible to the occurrence of flooding, gully erosion, and landslides. Greater infiltration capacity and less runoff are correlated with higher elongation ratios. The findings derived from our study are intended to provide a significant contribution to the development of a sustainable water management strategy for the UIB in the upcoming years. The main focus of this work is to analyze the geomorphological characteristics of mountainous watersheds located in the UIB of Pakistan and assess their influence on hydrologic processes