NUST Institutions Library Catalogue Search for 'kw,wrdl: (su-br:"X Window System Computer system")'

Microsoft Windows 2000 core requirements : exams 70-210, 70-215, 70-216, 70-217.

Redmond, WA : Microsoft, 2003 . 4 v. in container : , Title from container, issued in container. | Individual vols. published separately. | To complete the exercises for Windows 2000 server and Windows 2000 Network Infrastructure Administration, you need two computers, each equipped with a network card, internal modems and the minimum configuration listed above. Running the evaluation copy of Windows 2000 Server requires 256MB RAM. 23 cm. +. 0735617716 (set Core Requirements, 2nd edition) | 1572319011 (Exam 70210) | 1572319038 (Exam 70215) | 0735617724 (Exam 70216) | 0735617597 (Exam 70217)

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How computers work

By White, Ron,. Indianapolis, IN : Que, 2002 . xi, 405 p. : , Includes index. | The accompanying CD-ROM contains a guided interactive walkthrough inside a computer, a multimedia-based analysis of a computer, several software products to make your computer work better, and supplemental technology illustrations. 26 cm. +. 0789725495

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Running Linux

By Dalheimer, Matthias Kalle.. Beijing ; | Sebastopol, Calif. : O'Reilly, 2006 . xviii, 951 p. : , Previous ed. by Matt Welsh et al. 2002. | Includes index. 23 cm.. 0596007604

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C++ GUI programming with Qt3

By Blanchette, Jasmin.. Delhi. : Pearson, 2004 . xvi, 440 p. : , Includes index. 24 cm. +. 0131240722

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Introduction to game design, prototyping, and development : from concept to playable game-with Unity® and C# /

By Gibson, Jeremy,. . xxxi, 908 pages : 23 cm. 9780321933164 (paperback) | 0321933168 (paperback)

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Computer Networks /

By Tanenbaum, Andrew S.,. Upper Saddle River, NJ : Prentice Hall, 2003 . xx, 891 p. : 25 cm.. 9788177581652

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Introduction to solid modeling using SolidWorks 2011 /

By Howard, William E.. New York : McGraw-Hill Science/Engineering/Math, 2012 . xiii, 383 p. : , Issues for 2013- cataloged as a serial in LC 26 cm.. 9780073375458 (pbk.)

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Java network security /

By Macgregor, Robert. Upper Saddle River, N.J. : Prentice Hall PTR, 1998 . xii, 232 p. : , Includes Index 24 cm. . 0137615299

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Introduction to solid modeling using SolidWorks 2011 /

By Howard, William E.. New York : McGraw-Hill Science/Engineering/Math, 2012 . xiii, 383 p. : , Issues for 2013- cataloged as a serial in LC 26 cm.. 9780073375458 (pbk.) | 0073375454

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MCSE--NT workstation 4 study guide / (Include CD)

By Perkins, Charles. San Francisco : Network Press, 1998 . xxxvii, 741 p. : 24 cm. +. 078212223X

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eCommerce development. Business to business.

Redmond, Wash. : Microsoft Press, 2000 . xiv, 428 p. : , Accompanying CD-ROM contains files needed to complete lab exercises and includes a copy of Microsoft Internet Explorer to provide a browser that supports frames. | Includes index. 24 cm. +. 0735610436

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The art of memory forensics : detecting malware and threats in Windows, Linux, and Mac memory /

By Ligh, Michael Hale.. . xxiii, 886 pages : 24 cm. 9781118825099 (pbk.) | 1118825098 (pbk.) | 9781118825044 (ebk.) | 1118825047 (ebk.) | 9781118824993 (ebk.) | 1118824997 (ebk.)

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It encyclopaedia.com,vol-4 computer networks and e-commerce

By Diwan, Parag Suri, R.K Kaushik, Sanjay. NEW DELHI PENTAGON PRESS 2001 . 598P 81-86830-18-9

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Hacking the hacker : learn from the experts who take down hackers /

By Grimes, Roger A.,. . xxx, 286 pages ; 23 cm. 9781119396215 | 1119396212

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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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