NUST Institutions Library Catalogue Search for 'kw,wrdl: (su-br:"Functional analysis.")'

Wireless Information Networks : Architecture, Resource Managenment and Mobile data /

By Jack M. Holtzman. Boston Kluwer Academic Publishers 1996 . x,403p.

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Understanding the network -(EBOOK) a practical guide to internetworking /

By Martin, Michael J.. Indianapolis, IN : New Riders, 2000 . xvi, 687 p. : , Describes the various technologies and techniques needed to design, build and manage a multiprotocol local or wide area network (LAN/WAN). 24 cm.. 0735709777

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Application of Machine Learning (E-Book)

By Yagang Zhang. India In-Teh 2010 . viii,280p;

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Fermentation microbiology and biotechnology /

Boca Raton, FL : Taylor & Francis/CRC Press, 2012 . xix, 535 p. : 26 cm.. 9781439855799 (hardcover : alk. paper)

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Email Controls and Detection Engine /

By Quddus, Abdul Moiz . . x, 78 p

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Life Cycle Impact Assessment of Glass Manufacturing In Pakistan /

By Khan, Muhammad Usman Ali . . 76p. , The production of glass packaging requires a lot of energy and resources, and as the world's population rises, particularly in emerging nations, so does the demand for glass packaging. Although developing nations are also suffering from the effects of climate change, there is relatively little study on environmental impact assessment and analysis, notably the environmental impacts brought on by the activities related to glass manufacturing. This work conducted a thorough life cycle assessment (LCA) for the production of glass packaging in Pakistan in order to close this research gap of quantification of the environmental impacts of glass packaging production. The LCA was carried out for three distinct types of glass packaging solutions (amber, flint, and green), considering 1-ton of glass as the functional unit. The creation of several scenarios allowed for the analysis of the effects and the generation of ideas for ways to lessen the negative effects of glass manufacture on the environment. The study's methodology used a cradle-to-gate approach. From the perspective of the life cycle inventory, the main data were gathered from a renowned glass industry situated in one of Pakistan's designated industrial zones, and the secondary data were obtained from the Ecoinvent database. Environmental impacts were measured at midpoint and endpoint levels utilizing the ReCiPe 2016 approach and SimaPro V 9.2 as the software tool. Results indicated that the extraction and processing of raw material had worse impacts on the environment. At plant level the consumption of natural gas for the melting purposes and electricity consumed from national grid had highest impacts on the environment. The comparison of three packaging solutions indicated that the production of green glass was more harmful to the environment, followed by the production of amber glass and flint glass came out to be more environmentally friendly among the three packaging solutions. The alternative scenarios were generated by changing the energy-mix and the cullet ratios and the results were compared with the baseline scenarios for different midpoint and endpoint impact categories. The alternative scenarios for the energy mix were also compared for different kinds of emissions to air especially the greenhouse gas emissions. The report also identified a number of significant implications. This study may serve as a guide for future research on the environmental impact of the glass packaging industry, particularly in Pakistan and other developing nations. In this sense, developing nations would work toward net-zero emissions and sustainable development goals 30cm.

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Therapeutic Potential of Galantamine for Managing the Complications Associated with Ischemic Stroke /

By Ahsan, Mehwish . . 104p. , Ischemic stroke remains the leading cause of illness and second leading cause of death worldwide. Previous research has shown that galantamine has neuroprotective properties, reducing neuronal death and damage in neurodegenerative conditions and improving cognitive function in Alzheimer's disease patients. The investigation looked into the possible mechanisms by which this medication could reduce cell death. Wistar rats were subjected to a temporary 30-minute occlusion of the right middle cerebral artery (MCA) and given an oral dose of 5mg/kg for three weeks. After 18 days of surgery, behavioral assessments were carried out. Galantamine enhanced grip strength, motor function, and muscle strength in rats. Spatial memory and object recognition examinations revealed cognitive improvements, thus indicating enhanced cognitive abilities and memory retention. Moreover, rats subjected to galantamine treatment displayed increased sociability and heightened locomotor activity during social interaction and open-field assessments. Molecular analysis of galantamine treatment in rats showed an upregulation of SOD2 expression, suggesting enhanced antioxidant defense, and a downregulation of TLR4 expression, suggesting a reduction in neuroinflammation, supporting the anti-inflammatory properties of galantamine. The histological analysis done with H&E staining of brain tissue revealed enhanced tissue morphology in the galantamine-treated group, signifying the neuroprotective effects of galantamine. The reduction in neuronal damage, edema, and inflammatory cell infiltration further supported this observation. The results demonstrate that galantamine, potentially through the preservation of a functional cholinergic system, mitigated the impairments caused by stroke in a basic learning and memory test by decreasing cellular death. 30cm.

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Adaptive Hemodynamic Signal Estimation Using Kalman Estimator /

By Quddusi, Basiq Warrad . . 80p. , Functional Near Infrared Spectroscopy (fNIRS) is a technology that measures changes in the oxygenation level of blood present in brain whenever an activity is performed by human being. It is a non-invasive technique and uses near infrared light to detect changes in the concentration of two chromophores i.e., oxygenated and deoxygenated haemoglobin. During the recording, information related to neural activity in fNIRS signals gets compromised. This is due to the interference of noises from the environment outside as well as inside the human body. External noises can be light in the room and powerline noise. Internal noises are physiological noises such as cardiac, respiratory and mayer waves. Therefore, during analysis, it is required to remove these noises first and then extract main activity signal i.e., hemodynamic signal. Many techniques and methods have been proposed and practiced up to this date. Among them the most popular technique is General Linear Modelling (GLM). GLM models the signal by breaking it down into sum of all components present in the signal along with an error term. Previous studies and research that have used GLM for the reconstruction of activity signal used single frequency value for each noise but in reality, the frequency for each noise varies with the level of activity performed by the subject. This can lead to less accurate reconstruction of activity signal. In this study, this problem is kept under consideration and a method is developed to keep account for all the values of frequency that can corrupt fNIRS signal. Ranges of frequencies are considered instead of single values. These frequency ranges are first extracted using Continuous Wavelet Transform (CWT) and their possible magnitudes are estimated using Kalman filter. Similarly, activity signal is extracted from fNIRS signal using Discrete Wavelet Transform (DWT) and then its magnitude is estimated using Kalman filter. Output of these two steps is fed to GLM for reconstruction of possible hemodynamic signal. Results from this method are compared with the results of conventional GLM and significant improvement is observed both visually and statistically. 30cm,.

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Global street design guide /

. xxv, 396 pages : , Recommended by Cyrus Qureshi 28 cm. 9781610917018 | 1610917014

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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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Brain-Computer Interface for Mental State Detection of Drivers /

By Arif, Saad . . 169p. , Background: Each year millions of vehicles suffer crashes on the roads globally due to deteriorated mental state of the drivers during driving tasks which result in higher casualties. Drowsy driving is the leading cause of high fatality rate which is instigated due to sleep deprivation, fatigue, and anxiety, etc. Vehicular, and driver’s behavioral data-dependent systems detect the drowsiness after its onset when an accident is more likely, and they are also subject to false identification. The drowsy mental state of drivers must be detected earlier for in-time warning to avoid fatal losses, and also the system must be less intrusive, and adaptable for normal driving tasks. Detection systems using physiological signals from human organs are comparatively underexplored in which bodily states of the subject can be identified earlier and with more reliability. It is postulated that all the bodily states are primarily originated from the human brain which could be a promising region to detect drowsiness at an earlier stage. Among many physiological signals, electroencephalography (EEG), and functional near-infrared spectroscopy (fNIRS) are chosen for this study because they are proved to be more portable, easy to use, non-invasive, and reliable brain modalities for human mental state detection. Aim and Objectives: This study aimed to design a passive brain-computer interface (pBCI) scheme for the earlier detection of driver drowsiness with minimum intrusion into the driving task. Design objectives for the pBCI scheme were to select the channel of interest (COI), online detection with a shorter time window, minimum recalibration and setup time, and development of a widely applicable standard as an inter-subject transfer framework (iSTF) to cater to the inter-subject variability. All these objectives lead to such a pBCI system that is readily available for any subject, anytime, easy to use with minimal design, and yet detecting the drowsiness correctly at an earlier stage to avoid life losses. Methodology: Multichannel EEG and fNIRS brain signals from anterior, posterior, and lateral brain regions of sleep-deprived drowsy subjects were acquired during the simulated driving task for post hoc analysis. Initial pBCIschemes used labeled EEG data acquired from prefrontal (PFC), frontal, and occipital cortices for extracting the eight spectral, and eight temporal xvi features of EEG signals. Seven supervised machine learning classifiers were used to do the cross-validated binary classification of drowsy, and alert brain states. Initial design only achieved a few objectives and generated the need to use different modalities to meet all the requirements. The final pBCI scheme used labeled fNIRS data acquired from PFC and dorsolateral prefrontal cortices (DLPFC) for extracting the six cerebral oxygen regulation (CORE) and three hemodynamic signal features. CORE states of wakefulness and non-rapid eye movement (NREM) sleep stages were used to design a novel standard framework for wide applicability, and sleep stage classification using the vector phase analysis (VPA) approach. VPA was used for classifying microsleep/lapse, and drowsiness detection was done using the proposed brain hemodynamic patterns. Results: 𝛿, 𝜃, 𝛼, 𝛽 band powers as EEG spectral features achieved 82% accuracy in 10 s detection window. Signal skewness, variance, mean, peak as EEG temporal features achieved 87.2% accuracy in 1 s detection window. Ensemble classifier declared F8 as COI for earlier drowsiness detection using both the EEG pBCI schemes. Only the objectives of the short detection window and COI were achieved with the initial designs. In the final design with fNIRS, the novel VPA features: CORE vector gradients, achieved 94.1% accuracy in 5 s detection window for NREM sleep stage classification using ensemble classifier with the least computation time of 44 ms. Precise spatial localization of fNIRS declared AF8 position in right DLPFC as COI. The novel sleep stages-based threshold criteria along with VPA were crossvalidated as a standard iSTF for online microsleep detection with the least recalibration and setup time. Feature selection and achieved results were validated with various statistical significance tests. All the design objectives were attained with the fNIRS-based pBCI scheme. Conclusion: The aim to detect the driver's drowsiness earlier with minimum intrusion into the driving task, is accomplished. The presented fNIRS-based adaptive pBCI scheme is readily available for any subject, anytime, easy to wear with minimal ergonomic design, capable of real-time, correct, and early detection of the driver drowsiness to lessen the life losses in vehicular driving scenarios. The recommended research directions will surely justify, improve, and broaden the application horizons of the presented design 30cm..

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Star Shaped Silver Nanoparticles For Titanium Implant Coatings /

By Mushtaq, Aqsa. . 69p.; , Titanium implants are extensively used in the medical and healthcare industries because of their exceptional mechanical strength and biocompatibility. However, there are still concerns with reducing infection and enhancing implant integration with the surrounding bone tissue. In order to improve the antibacterial and biocompatibility of titanium implants, this study prepares star like silver nanoparticles and coat them on titanium discs (Ti-6Al-4V). The process of creating silver nanostars involved heating polyvinylpyrrolidone (PVP) and ethylene glycol solution along with silver precursor solution at 190°C for 30 minutes and reducing silver nitrate with 4×10⁻² M NaOH. PVP and ethylene glycol were used to stabilize the nanostar. Different properties of nanoparticles such as Surface morphology, functional groups, chemical composition, phase and purity, visual characterization, surface charge and stability were characterized by using SEM, FTIR, Raman spectroscopy, XRD, UV-Vis spectroscopy and zeta analysis. To enhance surface qualities, titanium discs were heated and given alkaline treatments. Simulated body fluid (SBF) and nanostar-coated discs interacted, and contact angle was measured in order to test biocompatibility. The antibacterial efficacy of tryptic soy broth (TSB) and TSA was evaluated against Staphylococcus aureus and there was a significant decrease in biofilm activity observed on 96 well plate.7 days and 14 days coated disc shows 83% and 95% inhibition to biofilm and there was a decrease in contact angle of both discs with increasing coating period, and 14 day coated disc shows contact angle of 22° indicating high hydrophilicity that leads to better Osseo integration and biocompatibility. These findings demonstrated that the silver nanostar coatings considerably increased the antibiofilm activity and make titanium implants more bio absorbable, which may promote Osseo integration and decrease bacterial adherence. This work demonstrates the effectiveness of coatings of silver nanoparticles, marking a significant advance in clinical applications. 30cm..

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Full Duplex Communication System on ADALM PLUTO /