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Mahbub Hassan

Other affiliations: University of California, Berkeley, NICTA, HITEC University  ...read more
Bio: Mahbub Hassan is an academic researcher from University of New South Wales. The author has contributed to research in topics: Network packet & Energy harvesting. The author has an hindex of 43, co-authored 273 publications receiving 7817 citations. Previous affiliations of Mahbub Hassan include University of California, Berkeley & NICTA.


Papers
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Journal ArticleDOI
TL;DR: In this paper, the authors provide a comprehensive survey of all of these developments promoting smooth integration of UAVs into cellular networks, including the types of consumer UAV currently available off-the-shelf, the interference issues and potential solutions addressed by standardization bodies for serving aerial users with the existing terrestrial BSs, challenges and opportunities for assisting cellular communications with UAV-based flying relays and BSs.
Abstract: The rapid growth of consumer unmanned aerial vehicles (UAVs) is creating promising new business opportunities for cellular operators On the one hand, UAVs can be connected to cellular networks as new types of user equipment, therefore generating significant revenues for the operators that can guarantee their stringent service requirements On the other hand, UAVs offer the unprecedented opportunity to realize UAV-mounted flying base stations (BSs) that can dynamically reposition themselves to boost coverage, spectral efficiency, and user quality of experience Indeed, the standardization bodies are currently exploring possibilities for serving commercial UAVs with cellular networks Industries are beginning to trial early prototypes of flying BSs or user equipments, while academia is in full swing researching mathematical and algorithmic solutions to address interesting new problems arising from flying nodes in cellular networks In this paper, we provide a comprehensive survey of all of these developments promoting smooth integration of UAVs into cellular networks Specifically, we survey: 1) the types of consumer UAVs currently available off-the-shelf; 2) the interference issues and potential solutions addressed by standardization bodies for serving aerial users with the existing terrestrial BSs; 3) the challenges and opportunities for assisting cellular communications with UAV-based flying relays and BSs; 4) the ongoing prototyping and test bed activities; 5) the new regulations being developed to manage the commercial use of UAVs; and 6) the cyber-physical security of UAV-assisted cellular communications

667 citations

Journal ArticleDOI
TL;DR: The design and development of efficient TiO 2 -based, hybrid, nanostructured photocatalysts has recently been receiving substantial attention for environmental remediation due to their excellent physiochemical properties as mentioned in this paper.
Abstract: The design and development of efficient TiO 2 -based, hybrid, nanostructured photocatalysts has recently been receiving substantial attention for environmental remediation due to their excellent physiochemical properties. This article provides an overview of the synthesis strategies and characteristics of the next-generation TiO 2 -based hybrid photocatalysts, produced in combination with polymers (e.g., polyaniline, polypyrrole, polythiophene) and carbon nanomaterials (e.g., graphene, GO, CNT, carbon quantum dots, carbon nitride). The structural aspects, nanostructure formation process, parameters affecting catalytic activity, photocatalytic mechanisms and photocatalytic applications of TiO 2 -based catalysts for efficient photocatalytic degradation of gaseous/volatile organic pollutants in water/air are reviewed. Further, current research trends, means to increase catalytic performance and future prospects of high-performance TiO 2 -based hybrid photocatalytic materials, are briefly summarized.

654 citations

Journal ArticleDOI
TL;DR: The communication security issues facing the popular wearables is examined followed by a survey of solutions studied in the literature, and the techniques for improving the power efficiency of wearables are explained.
Abstract: As smartphone penetration saturates, we are witnessing a new trend in personal mobile devices—wearable mobile devices or simply wearables as it is often called. Wearables come in many different forms and flavors targeting different accessories and clothing that people wear. Although small in size, they are often expected to continuously sense, collect, and upload various physiological data to improve quality of life. These requirements put significant demand on improving communication security and reducing power consumption of the system, fueling new research in these areas. In this paper, we first provide a comprehensive survey and classification of commercially available wearables and research prototypes. We then examine the communication security issues facing the popular wearables followed by a survey of solutions studied in the literature. We also categorize and explain the techniques for improving the power efficiency of wearables. Next, we survey the research literature in wearable computing. We conclude with future directions in wearable market and research.

486 citations

Journal ArticleDOI
TL;DR: A facile ultrasonic approach with chemical activation using KOH to prepare activated GQDs or aGQDs enriched with both free and bound edges with superior luminescence holds potential for use in biomedical imaging and related optoelectronic applications.
Abstract: Graphene quantum dots (GQDs) with their edge-bound nanometer-size present distinctive properties owing to quantum confinement and edge effects. We report a facile ultrasonic approach with chemical activation using KOH to prepare activated GQDs or aGQDs enriched with both free and bound edges. Compared to GQDs, the aGQDs we synthesized had enhanced BET surface area by a factor of about six, the photoluminescence intensity by about four and half times and electro-capacitance by a factor of about two. Unlike their non-activated counterparts, the aGQDs having enhanced edge states emit enhanced intense blue luminescence and exhibit electrochemical double layer capacitance greater than that of graphene, activated or not. Apart from their use as part of electrodes in a supercapacitor, the superior luminescence of aGQDs holds potential for use in biomedical imaging and related optoelectronic applications.

402 citations

Journal ArticleDOI
TL;DR: In this article, a mathematical model is analyzed in order to study the natural convection boundary layer flow along an inverted cone, where the shape of nanosize particles on entropy generation with based fluid is considered.

353 citations


Cited by
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Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

01 Jan 2002

9,314 citations

Journal ArticleDOI
TL;DR: In this article, a comprehensive tutorial on the potential benefits and applications of UAVs in wireless communications is presented, and the important challenges and the fundamental tradeoffs in UAV-enabled wireless networks are thoroughly investigated.
Abstract: The use of flying platforms such as unmanned aerial vehicles (UAVs), popularly known as drones, is rapidly growing. In particular, with their inherent attributes such as mobility, flexibility, and adaptive altitude, UAVs admit several key potential applications in wireless systems. On the one hand, UAVs can be used as aerial base stations to enhance coverage, capacity, reliability, and energy efficiency of wireless networks. On the other hand, UAVs can operate as flying mobile terminals within a cellular network. Such cellular-connected UAVs can enable several applications ranging from real-time video streaming to item delivery. In this paper, a comprehensive tutorial on the potential benefits and applications of UAVs in wireless communications is presented. Moreover, the important challenges and the fundamental tradeoffs in UAV-enabled wireless networks are thoroughly investigated. In particular, the key UAV challenges such as 3D deployment, performance analysis, channel modeling, and energy efficiency are explored along with representative results. Then, open problems and potential research directions pertaining to UAV communications are introduced. Finally, various analytical frameworks and mathematical tools, such as optimization theory, machine learning, stochastic geometry, transport theory, and game theory are described. The use of such tools for addressing unique UAV problems is also presented. In a nutshell, this tutorial provides key guidelines on how to analyze, optimize, and design UAV-based wireless communication systems.

1,395 citations