Noor M. Khan

Bio: Noor M. Khan is an academic researcher from University of Engineering and Technology, Lahore. The author has contributed to research in topics: Angle of arrival & Wireless sensor network. The author has an hindex of 20, co-authored 166 publications receiving 1440 citations. Previous affiliations of Noor M. Khan include Mawlana Bhashani Science and Technology University & Mohammad Ali Jinnah University.

A Critical Analysis of Research Potential, Challenges, and Future Directives in Industrial Wireless Sensor Networks

Abstract: In recent years, industrial wireless sensor networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems, and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment, and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper, a detailed discussion on design objectives, challenges, and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines, and possible hazards in industrial atmosphere are discussed. This paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. This paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs.

A Generalized 3-D Scattering Model for a Macrocell Environment With a Directional Antenna at the BS

Abstract: In this paper, a generalized 3-D scattering model is presented for macrocellular land mobile radio cellular systems with a mobile station (MS) located at the center of a 3-D scattering semispheroid and a base station (BS) employing a directional antenna located outside of the semispheroid. The effect of the directional antenna is thoroughly observed on spatial and temporal characteristics of the proposed model. Closed-form expressions for joint and marginal probability density functions (pdf's) of the angle of arrival (AoA) seen at the MS and the BS in correspondence with azimuth and elevation angles are derived. Furthermore, closed-form expressions for propagation path delays and trivariate joint pdf's of the time of arrival (ToA) seen at the MS and the BS in correspondence with azimuth and elevation angles are derived. Moreover, the theoretical results, along with observations, are shown that illustrate the effect of the directional antenna on the spatiotemporal statistics of the proposed 3-D model. The proposed 3-D scattering model is shown to deduce all previously proposed 2-D and 3-D models that assume a uniform distribution of scatters with directional or omnidirectional antennas found in the literature for a macrocell environment. The obtained theoretical results are compared with some notable 2-D and 3-D scattering models to validate the generalization of the proposed model.

Optimization and simulation of reservoir operation with sediment evacuation: a case study of the Tarbela Dam, Pakistan.

Abstract: Many reservoirs around the world are being operated based on rule curves developed without considering the evacuation of deposited sediment. Current reservoir simulation and optimization models fall short of incorporating the concept of sustainability because the reservoir storage losses due to sedimentation are not considered. This study develops a new model called Reservoir Optimization-Simulation with Sediment Evacuation (ROSSE) model. The model utilizes genetic algorithm based optimization capabilities and embeds the sediment evacuation module into the simulation module. The sediment evacuation module is implemented using the Tsinghua university flushing equation. The ROSSE model is applied to optimize the rule curves of Tarbela Reservoir, the largest reservoir in Pakistan with chronic sedimentation problems. In the present study, rule curves are optimized for maximization of net economic benefits from water released. The water released can be used for irrigation, power production, sediment evacuation, and for flood control purposes. Relative weights are used to combine the benefits from these conflicting water uses. Nine sets of rule curves are compared, namely existing rule curves and proposed rule curves for eight scenarios developed for various policy options. These optimized rule curves show an increase of net individual economic benefits ranging from 9 to 248% over the existing rule curves. The shortage of irrigation supply during the simulation period is reduced by 38% and reservoir sustainability is enhanced by 28% through increased sediment evacuation. The study concludes that by modifying the operating policy and rule curves, it is possible to enhance the reservoir's sustainability and maximize the net economic benefits. The developed methodology and the model can be used for optimization of rule curves of other reservoirs with sedimentation problems. Copyright © 2008 John Wiley & Sons, Ltd.

A Generalized Model for the Spatial Characteristics of the Cellular Mobile Channel

Abstract: In this paper, we present an intensive study of the spatial characteristics of the cellular mobile channel for picocell, microcell, and macrocell environments. We review the previous physical channel models and make appropriate comments/corrections wherever needed. We find that almost all physical channel models proposed so far are specific to particular cellular environments and that no general model exists in the literature. Thus, we propose a generalized physical channel model, referred to as the eccentro-scattering model, and derive the expressions for the probability density function (pdf) in an angle of arrival (AoA) of the multipath signals at a base station (BS) for the picocell, microcell, and macrocell environments using the two most commonly used scatterers' distributions, i.e., uniform and Gaussian. The derived formulas, in closed form, can be further used in designing beamwidth and channel tracking algorithms and assessing the performance of smart antennas. We discuss the relations between the results obtained for different cellular environments in the uniform and the Gaussian scattering and investigate the effects of the standard deviation of the scatter density and size of the scattering disc on the pdf of AoA at the BS. Previous work on the AoA statistics considering either the shape of the scattering regions or the distribution of scatterers within that region can more easily be reproduced using the provided general formula. We prove that assuming the scatterers to be either uniformly or Gaussian distributed in sparsely populated areas gives almost the same distribution of AoA of multipaths at the BS.

Streamflow Variations in Monthly, Seasonal, Annual and Extreme Values Using Mann-Kendall, Spearmen’s Rho and Innovative Trend Analysis

Abstract: The present study investigates the variations in the monthly, seasonal and annual streamflow timeseries at twenty (20) stations over the upper Indus river basin (UIRB) by using Mann-Kendall (MK), Spearman’s rho (SR) and innovative trend analysis (ITA) methods. Moreover, variations in extreme flows were investigated by dividing the daily streamflow timeseries into two categories; extremely low ( 90th percentile) flows. At monthly time scale, 240 timeseries were investigated, out of which 134, 138 and 159 timeseries manifested significant trends by using MK, SR and ITA methods, respectively. Whereas, seasonal and annual flows showed significant trends over 57, 62 and 75 timeseries based on MK, SR and ITA methods, respectively. Extremely low flows exhibited significant increasing trends over seven (07) stations and significantly decreasing trends over three (03) stations whereas, four (04) stations exhibited significantly decreasing trends in extremely high flows. Therefore, it may be concluded that the variations in the extremely low flows will be more pronounced compared to extremely high flows in the future. This may constitute constant pressure on water resources availability in the lower Indus plains where most of the country’s population is dependent on agricultural activities.

Minimum Design Loads for Buildings and Other Structures

Abstract: Minimum Design Loads for Buildings and Other Structures provides requirements for general structural design and includes means for determining dead, live, soil, flood, wind, snow, rain, atmospheric ice, and earthquake loads, as well as their combinations, which are suitable for inclusion in building codes and other documents. This Standard, a revision of ASCE/SEI 7-05, offers a complete update and reorganization of the wind load provisions, expanding them from one chapter into six. The Standard contains new ultimate event wind maps with corresponding reductions in load factors, so that the loads are not affected, and updates the seismic loads with new risk-targeted seismic maps. The snow, live, and atmospheric icing provisions are updated as well. In addition, the Standard includes a detailed Commentary with explanatory and supplementary information designed to assist building code committees and regulatory authorities. Standard ASCE/SEI 7 is an integral part of building codes in the United States. Many of the load provisions are substantially adopted by reference in the International Building Code and the NFPA 5000 Building Construction and Safety Code. Structural engineers, architects, and those engaged in preparing and administering local building codes will find this Standard an essential reference in their practice. Note: New orders are fulfilled from the second printing, which incorporates the errata to the first printing.

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Abstract: Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002–2013 of machine learning methods that were used to address common issues in WSNs. The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.

Animal Tissue Techniques.

Abstract: Clearly, the possibility that Van Peenen's statements are correct exists, but no molecular geneticist would contend that these assertions have been established, in any but a very few cases, which appear at present to be atypical. The educated lavman, for whom this book is intended, will find the author's leaps from the level of the quoted material into sophisticated physical chemistry and back again disconcerting at least, if not completely confusing. It can be said, however, that the authors have assembled an excellent group of illustrations; lecturers in elementary genetics wishing to locate clear illustrations to use as slides would do well to look in this book first.