NUST Institutions Library Catalogue Search for 'kw,wrdl: (su-br:"Islam and literature")'

TH-SOF-1715-A Model-Driven Framework to Generate Data and Presentation Layers' Scaffolding Code for multiplatform Applications

By Mohammad Inayatullah. ISLAMABAD NUST COLLEGE OF EME 2019

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Diagnosing and localizing Covid-19 in High resolution CT(HRCT) scans using Deep learning /

By Munir, Zonaira. . 62p. ; 30cm..

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Age-Specific Study of Airflow Distribution, Aerosol Transport and Deposition in an Unhealthy Human Lung using CFD-DPM Approach /

By Riaz, Hafiz Hamza . . 58p. 30cm.

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Automatic Detection and Recognition of Citrus Fruits Diseases Using Deep Learning Model /

By Faisal, Shah . . 59p. , In a country's economy, agriculture plays a very vital role. Agriculture's yield and production are reduced by plant diseases, resulting in significant economic losses and instability in the food market. In plants, the citrus fruit crop is one of the most important agricultural products in the world, produced and grown in around 140 countries. It has a lot of nutrients, such as vitamin C. However, due to pests and diseases, citrus cultivation is widely affected and suffers significant losses in both yield and quality. The majority of plant diseases exhibit visible symptoms, and the accepted method used today is for a skilled plant pathologist to detect the diseases by examining affected plant leaves under a microscope, which is a costly and time-consuming method. During the last decade, computer vision and machine learning have been widely adopted to detect and classify plant diseases, providing opportunities for early disease detection and bringing improvements to agricultural production. The early detection and accurate diagnosis of plant diseases are essential for reducing their spread and damage to crops. In this work, we presented an automatic system for early detection and recognition of citrus plant diseases based on a deep learning (DL) model to improve accuracy and reduce computational complexity. The most recent transfer learning-based models were applied to our dataset in order to increase classification accuracy. In this work, we successfully proposed a CNN-based pre-trained model (EfficientNetB3, ResNet50, MobiNetV2, (InceptionV3) for the identification and classification of citrus plant diseases using transfer learning. In order to assess the performance of the model, we found that the transfer of an EfficientNetb3 model led to the highest training, validating, and testing accuracies, which were 99.43%, 99.48%, and 99.58%, respectively. The proposed CNN model exceeds other cutting-edge CNN network architectures developed in earlier literature in the identification and categorization of citrus plant diseases. 30cm.

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Experimental Study of Lings Airways /

By Sardar, Hassan . . 55p. , Breathing is phenomenon essential for every mammal on Earth. Key role of respiratory system is transmission of vital gases between air and blood. Conventionally some macroscale techniques for flow visualization in trachea-bronchial region was achieved by using 3D printing of idealized/realistic airways model. Due to limitations in fabrication and CT image resolution, limited amount of experimental study is done on bronchial region. We fabricated simplified model of terminal bronchi airways by using polydimethylsiloxane. Micro-fluidic channel is fabrication by using the 3D printed molds via SLA printer (FormLabs 3+ with layer thickness of 50 μm). The mold is then used to fabricate transparent channel of PDMS which is good for visualization of flow. It is first of its kind of fabrication of terminal bronchial airways by using microfluidic chip fabrication method. Moreover, the chips fabricated using the PDMS have some paybacks like we can easily visualize flow passing through the airways. We use syringe pumps for flow of three breathing conditions sleep, normal and exercise. We demonstrated airways focusing using microscope and visualized fluid flow by using particle image velocimetry method. The statistics evidence good agreement with our experimental results and simulation results from the literature. The results shows that turbulence kinetics energy decreases by using pressurized meter dose inhaler. 30cm.

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Evaluation of different metal cutting models during machining of Inconel-718 /

By Hamza, M Ghazi . . 42p. , Inconel-718 is a nickel-based aerospace alloy that has large domain of applications in the aerospace industry and also in ground-based turbines. Machining of Inconel-718 is a very difficult process as it is able to retain its strength even at high temperatures resulting in a lot of tool wear and making it difficult to machine, thus making it a topic of interest among researchers. In order to study the orthogonal machining process of this material, development of a FEM model, in Abaqus software, which can simulate the process with good accuracy is extremely important. To simulate the plastic deformation and damage of Inconel-718, during the machining process, different material modelling techniques are available in the literature. Among these material models, Johnson Cook Plasticity model is widely accepted as being more accurate. When modelling the machining process using FEM, the Johnson Cook Plasticity model is utilized to forecast the plastic deformation and behaviour of a material. However, there are different values of parameters, involved in the JC model equation, available in the literature which have been derived experimentally. Using these different values of parameters in the simulation process of machining brings a variation in the output values. Thus, the need to evaluate these different models arises. This research will focus on identifying which model proves to be more accurate in predicting the cutting forces during machining of Inconel-718. Results obtained from each model will be compared to the experimental results and a conclusion will be derived about which model is preferrable to be used in simulation this process in future. 30cm.

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Development of Reinforced Metal Tubing for Vascular Applications /

By Arshad, Aimen . . 53p , Coronary artery diseases remain one of the leading causes of mortality, with the incidence of death rate being 20% in Pakistan. The disease causes deposition of plaque on the lumen of the blood vessels that narrow the coronary arteries (blood) hindering the blood flow to the heart and rest of the tissues. The treatment procedure of the disease involves delivering the expandable device (balloon/stent) to the target region. Guide catheters plays a crucial role for the advancement of these treatment devices (stent/balloon). Guide catheters are hollow tubular structures of 100-110 cm in length, which are required to provide support, and facilitate the delivery of the stent/balloon at the target region. The guide catheter is made to enter the body via the wrist/femoral artery. From here, it traverses all the way to the heart while passing through blood vessels of varying diameter, and a tortuous anatomy of the body. In fact, the pathway of the guide catheter is not a straight, rather a curved path. It is important for the guide catheter to have certain mechanical characteristics to reach the heart without causing any vascular trauma. The performance of the guide catheter heavily relies on its braided shaft, and the outer jacket. Spontaneous movement of the catheter due to its instability, coronary dissections due to a high push force, and arterial spasms resulting from the friction are a few common problems of guide catheters used commercially. The current research is focused on catering these challenges by optimizing the pitch of the braided shaft and jacketing the shaft with a polymer unique to commercial catheters. In order to find the best guide catheter to meet the challenges presented in the literature, three guide catheters of varying pitch were designed, and coated with a polyimide jacket material. The protypes were tested for performance under mechanical, and physically testing and the candidate performing the best was selected. The guide catheter that performed the best in providing the longitudinal stiffness, reducing the friction, and decreasing the push force was chosen, and bench tested. 30cm.

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Identifying Neurophysiological Correlates of Frontotemporal Dementia: Resting State EEG and Phase Synchronization Analysis /

By Ali, Salwa . . 123p. , The need to develop more efficient neuropsychological biomarkers is paramount in the identification of neurodegenerative diseases, tracking the efficiency of treatment and in an effort to avoid the huge financial cost required. While previous research utilizing neuroimaging techniques has pinpointed changes in functional connectivity (FC) as promising biomarkers for frontotemporal dementia (FTD), the constraints of cost and availability of neuroimaging equipment underscore the necessity for accessible alternatives. Electroencephalography (EEG) has emerged as a viable option due to its increasing robustness, wider usage, and affordability. To this end, the research focuses on a resting-state EEG data created from AD, FTD, and HC groups. Here ground data were obtained from nineteen leads using a clinical EEG device when the subjects were in a resting state and their eyes were closed. Another challenge was to follow strict standards for data quality and quality management for data quality to enhance consistency. It is a cross-sectional study, including data from MiniMental State Examination conducted on each participant, and tapes recorded from 20 AD patients, 20 FTD patients, and 20 HC. The Neuroimaging Data Structure (BIDS) format was utilized to present both preprocessed and raw EEG data. The foremost aim was to determine the Feasibility, Sensitivity, and Specificity of the preprocessed, feature extracted, time-efficient, and artifact reduced EEG-derived FC patterns as markers in FTD. Phase-lock values (PLVs) were computed among nineteen pairs of electrodes across five frequency bands using MATLAB and the Hilbert transform. Significant variations in brain connectivity were identified through statistical analyses. The study revealed significant differences in alpha and beta frequency patterns among the control, Alzheimer's, and FTD groups, particularly in frontal and temporal regions. These differences suggest alterations in neural activity associated with cognitive processing, potentially serving as biomarkers for distinguishing between the three groups. Alterations in beta frequency PLV were noted across various EEG pairs, indicating disruptions in neural communication and coordination. These alterations suggest xvi compensatory mechanisms or hyperactivity in frontal and prefrontal regions, alongside potential cognitive and motor deficits due to decreased PLV in central and temporal regions. While no statistically significant differences were observed in delta and theta frequency synchronization between groups, trends suggest potential regions of interest for further research, aligning with existing literature exploring neural oscillations in neurodegenerative diseases. Similarly, no significant differences were observed in gamma frequency synchronization between groups, indicating relatively preserved neural synchronization in this frequency range across control, Alzheimer's, and FTD patients. In summary, both Alzheimer's and FTD demonstrate significant reductions in alpha and beta frequency values, particularly in frontal and temporal regions, compared to healthy controls. These findings underscore the altered functional network topology in AD and FTD, offering valuable insights into the neural mechanisms underlying these conditions. The study's results contribute to the development of electrophysiological markers, potentially enhancing the clinical diagnosis and understanding of AD and FTD. The specificity and sensitivity of EEG-derived FC patterns highlight their potential as costeffective, accessible biomarkers for neurodegenerative disease. 30cm.

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Āb-i kaus̲ar /

By Amīn, Muḥammad. Faiṣalābād: Idārah-yi Tablīgh al-Islām ; [n.d.] . 320 pages. , Religion

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Design and Development of Toroidal Propeller for Drone Applications /

By Ali, Aarib Irfan . . 182p. , The demand for low-noise and ecient propulsion systems for unmanned aerial vehicles has driven research into unconventional propeller designs. One such promising conguration is the toroidal propeller, which has gained attention for its potential to reduce noise emissions while maintaining or improving aerodynamic performance. The research follows a methodology that begins with an extensive literature review and operating point selection to dene the design requirements and constraints. A validated computational setup was developed using unsteady RANS-based CFD simulations. Several toroidal propeller concepts were initially generated, out of which a baseline model was selected for further study. The baseline design was optimized using a Design of Experiments response surface methodology and obtain an optimized propeller with maximum thrust and reduced noise. Sensitivity analysis was carried out to assess the inuence of individual parameters on thrust, torque, and noise. The optimized design showed signicant improvements in thrust with considerable reduction in noise as compared to initial concepts. Aeroacoustic analysis was also performed to evaluate the noise characteristics of the toroidal conguration. Using broadband noise models, the toroidal propeller demonstrated promising reductions in tonal noise components, making it suitable for operations in noise-sensitive environments. To validate the computational ndings, experimentation validation was also performed. The optimized toroidal propeller was evaluated using ve dierent materials: ABS, PLA, PETG, CF PETG, and an Engineering Resin via Finite Element Analysis. Suitable manufacturing methods were employed and a custom test bench conguration XXII was built to test the propeller thrust and noise. The propeller was tested under controlled conditions for thrust and noise. The experimental results matched closely with the computational results and veried the validity of toroidal propelelr as viable replacement of traditional propellers for UAVs, oering advantages in both thrust and acoustic performance. The toroidal propeller showed higher value of thrust over complete range of RPM and and delivering upto 35% more thrust than traditional propeller at 15,000RPM. In addition, it also had a lower acoustic signature and was 11% quieter than the traditional propeller. The successful integration of computational design, optimization, and experimental validation demonstrates the practical potential of this novel propeller architecture. Furthermore, the research lays a foundation for future work involving transient LES acoustic modeling, in-ight testing, and applicationspecic customization of toroidal designs. 30cm.

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