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Muhammad Ali

Publications and source records attributed to Muhammad Ali.

49 records · Page 3Linked to original sources
arXiv2020

Stable Dispersion of Coal Fines during Hydraulic Fracturing Flowback in Coal Seam Gas Reservoirs An Experimental Study

In subterranean coal seam gas CSG reservoirs, massive amounts of small-sized coal fines are released during the production and development stages, especially during hydraulic fracturing stimulation. These coal fines inevitably cause mechanical pump failure and permeability damage due to aggregation and subsequent pore throat blockage. This aggregation behavior is thus of key importance in CSG production and needs to be minimized. Consequently, such coal fines dispersions need to be stabilized, which can be achieved by the formulation of improved fracturing fluids. Here, we thus systematically investigated the effectiveness of two additives; ethanol, 0.5 wt percent and SDBS, 0.001 and 0.01 wt percent, on dispersion stability for a wide range of conditions: pH 6 to 11, salinity of 0.1 to 0.6 M NaCl brine. Technically, the coal suspension flowed through a glass bead proppant pack, and fines retention was measured. We found that even trace amounts of sodium dodecylbenzene sulfonate SDBS i.e. 0.001 wt per cent drastically improved dispersion stability and reduced fines retention. The retention was further quantified by fractal dimensional analysis, which showed lower values for suspensions containing SDBS. This research advances current CSG applications and thus contributes to improved energy security.

physics.flu-dyn↗
arXiv2020

A Review of 5G Front-End Systems Package Integration

Increasing data rates, spectrum efficiency and energy efficiency have been driving major advances in the design and hardware integration of RF communication networks. In order to meet the data rate and efficiency metrics, 5G networks have emerged as a follow-on to 4G, and projected to have 100X higher wireless date rates and 100X lower latency than those with current 4G networks. Major challenges arise in the packaging of radio-frequency front-end modules because of the stringent low signal-loss requirements in the millimeter-wave frequency bands, and precision-impedance designs with smaller footprints and thickness. Heterogeneous integration in 3D ultra-thin packages with higher component densities and performance than with the existing 2D packages is needed to realize such 5G systems. This paper reviews the key building blocks of 5G systems and the underlying advances in packaging technologies to realize them.

eess.SP↗
arXiv2020

Synthesizing Averaged Virtual Oscillator Dynamics to Control Inverters with an Output LCL Filter

In commercial inverters, an LCL filter is considered an integral part to filter out the switching harmonics and generate a sinusoidal output voltage. The existing literature on the averaged virtual oscillator controller (VOC) dynamics is for current feedback before the output LCL filter that contains the switching harmonics or for inductive filters ignoring the effect of filter capacitance. In this work, a new version of averaged VOC dynamics is presented for islanded inverters with current feedback after the LCL filter thus avoiding the switching harmonics going into the VOC. The embedded droop-characteristics within the averaged VOC dynamics are identified and a parameter design procedure is presented to regulate the output voltage magnitude and frequency according to the desired ac-performance specifications. Further, a power dispatch technique based on this newer version of averaged VOC dynamics is presented to simultaneously regulate both the active and reactive output power of two parallel-connected islanded inverters. The control laws are derived and a power security constraint is presented to determine the achievable power set-point. Simulation results for load transients and power dispatch validate the proposed version of averaged VOC dynamics.

eess.SY↗
arXiv2019

Ad Delivery Algorithms: The Hidden Arbiters of Political Messaging

Political campaigns are increasingly turning to digital advertising to reach voters. These platforms empower advertisers to target messages to platform users with great precision, including through inferences about those users' political affiliations. However, prior work has shown that platforms' ad delivery algorithms can selectively deliver ads within these target audiences in ways that can lead to demographic skews along race and gender lines, often without an advertiser's knowledge. In this study, we investigate the impact of Facebook's ad delivery algorithms on political ads. We run a series of political ads on Facebook and measure how Facebook delivers those ads to different groups, depending on an ad's content (e.g., the political viewpoint featured) and targeting criteria. We find that Facebook's ad delivery algorithms effectively differentiate the price of reaching a user based on their inferred political alignment with the advertised content, inhibiting political campaigns' ability to reach voters with diverse political views. This effect is most acute when advertisers use small budgets, as Facebook's delivery algorithm tends to preferentially deliver to the users who are, according to Facebook's estimation, most relevant. Our findings point to advertising platforms' potential role in political polarization and creating informational filter bubbles. Furthermore, some large ad platforms have recently changed their policies to restrict the targeting tools they offer to political campaigns; our findings show that such reforms will be insufficient if the goal is to ensure that political ads are shown to users of diverse political views. Our findings add urgency to calls for more meaningful public transparency into the political advertising ecosystem.

cs.CY↗
arXiv2019

Discrimination through optimization: How Facebook's ad delivery can lead to skewed outcomes

The enormous financial success of online advertising platforms is partially due to the precise targeting features they offer. Although researchers and journalists have found many ways that advertisers can target---or exclude---particular groups of users seeing their ads, comparatively little attention has been paid to the implications of the platform's ad delivery process, comprised of the platform's choices about which users see which ads. It has been hypothesized that this process can "skew" ad delivery in ways that the advertisers do not intend, making some users less likely than others to see particular ads based on their demographic characteristics. In this paper, we demonstrate that such skewed delivery occurs on Facebook, due to market and financial optimization effects as well as the platform's own predictions about the "relevance" of ads to different groups of users. We find that both the advertiser's budget and the content of the ad each significantly contribute to the skew of Facebook's ad delivery. Critically, we observe significant skew in delivery along gender and racial lines for "real" ads for employment and housing opportunities despite neutral targeting parameters. Our results demonstrate previously unknown mechanisms that can lead to potentially discriminatory ad delivery, even when advertisers set their targeting parameters to be highly inclusive. This underscores the need for policymakers and platforms to carefully consider the role of the ad delivery optimization run by ad platforms themselves---and not just the targeting choices of advertisers---in preventing discrimination in digital advertising.

cs.CY↗
arXiv2019

Agent-based Vs Agent-less Sandbox for Dynamic Behavioral Analysis

Malicious software is detected and classified by either static analysis or dynamic analysis. In static analysis, malware samples are reverse engineered and analyzed so that signatures of malware can be constructed. These techniques can be easily thwarted through polymorphic, metamorphic malware, obfuscation and packing techniques, whereas in dynamic analysis malware samples are executed in a controlled environment using the sandboxing technique, in order to model the behavior of malware. In this paper, we have analyzed Petya, Spyeye, VolatileCedar, PAFISH etc. through Agent-based and Agentless dynamic sandbox systems in order to investigate and benchmark their efficiency in advanced malware detection.

cs.CR↗
arXiv2018

Biosensing-by-learning Direct Targeting Strategy for Enhanced Tumor Sensitization

Objective:We propose a novel iterative-optimizationinspired direct targeting strategy (DTS) for smart nanosystems, which harness swarms of externally manipulable nanoswimmers assembled by magnetic nanoparticles (MNPs) for knowledgeaided tumor sensitization and targeting. We aim to demonstrate through computational experiments that the proposed DTS can significantly enhance the accumulation of MNPs in the tumor site, which serve as a contrast agent in various medical imaging modalities, by using the shortest possible physiological routes and with minimal systemic exposure. Methods: The epicenter of a tumor corresponds to the global maximum of an externally measurable objective function associated with an in vivo tumor-triggered biophysical gradient; the domain of the objective function is the tissue region at a high risk of malignancy; swarms of externally controllable magnetic nanoswimmers for tumor sensitization are modeled as the guess inputs. The objective function may be resulted from a passive phenomenon such as reduced blood flow or increased kurtosis of microvasculature due to tumor angiogenesis; otherwise, the objective function may involve an active phenomenon such as the fibrin formed during the coagulation cascade activated by tumortargeted "activator" nanoparticles. Subsequently, the DTS can be interpreted from the iterative optimization perspective: guess inputs (i.e., swarms of nanoswimmers) are continuously updated according to the gradient of the objective function in order to find the optimum (i.e., tumor) by moving through the domain (i.e., tissue under screening). Along this line of thought, we propose the computational model based on the gradient descent (GD) iterative method to describe the GD-inspired DTS, which takes into account the realistic in vivo propagation scenario of nanoswimmers.

physics.med-ph↗
arXiv2017

Towards In-Transit Analytics for Industry 4.0

Industry 4.0, or Digital Manufacturing, is a vision of inter-connected services to facilitate innovation in the manufacturing sector. A fundamental requirement of innovation is the ability to be able to visualise manufacturing data, in order to discover new insight for increased competitive advantage. This article describes the enabling technologies that facilitate In-Transit Analytics, which is a necessary precursor for Industrial Internet of Things (IIoT) visualisation.

cs.CY↗
arXiv2017

On Quantifying Knowledge Segregation in Society

With rapid increase in online information consumption, especially via social media sites, there have been concerns on whether people are getting selective exposure to a biased subset of the information space, where a user is receiving more of what she already knows, and thereby potentially getting trapped in echo chambers or filter bubbles. Even though such concerns are being debated for some time, it is not clear how to quantify such echo chamber effect. In this position paper, we introduce Information Segregation (or Informational Segregation) measures, which follow the long lines of work on residential segregation. We believe that information segregation nicely captures the notion of exposure to different information by different population in a society, and would help in quantifying the extent of social media sites offering selective (or diverse) information to their users.

cs.SI↗
arXiv2016

Experimental and theoretical analyses of strongly polarized photon emission from non-polar InGaN quantum dots

We present a comprehensive investigation of the polarization properties of non-polar a-plane InGaN quantum dots (QDs) and their origin with statistically significant experimental data and rigorous k.p modelling. The unbiased selection and study of 180 individual QDs allow us to compute an average polarization degree of 0.90, with a standard deviation of only 0.08. When coupled with theoretical insights, we show that a-plane InGaN QDs are highly insensitive to size differences, shape anisotropies, and indium content fluctuations. Furthermore, 91% of the studied QDs exhibit a polarization axis along the crystal [1-100] axis, with the other 9% polarized orthogonal to this direction. When coupled with their ability to emit single-photons, a-plane QDs are good candidates for the generation of linearly polarized single-photons, a feature attractive for quantum cryptography protocols.

cond-mat.mes-hall↗
arXiv2006

New Basis for the Standard Model for Electroweak Interactions

The standard model for electroweak interactions uses the concepts of weak hypercharge and local gauge invariance of the Lagrangian density under the gauge group SU(2) x U(1). Taylor has remarked that U(1), being a multiply-connected group, in general, should have different coupling strengths for singlets and doublets. But in the development of the standard model, even for U(1), the coupling strength has been taken to be the same for all the multiplets without a priori justification. Wilczek has pointed out that the assignment of hypercharge values to left- and right-handed leptons and quarks is very peculiar. However, no solution has been provided. Ellis has also reservations for the rather bizarre set up of group representations and hypercharges. It has also been noticed that, in addition to the above weak points of the model, the generator of the group U(1) is changed at different stages during a single analysis. In this paper, a new basis is provided that avoids these peculiar and odd concepts and hypercharge assignments, and a satisfactory solution is given for the first time. This is done by generalising the expression for the transformation law for 4-vector potential in electromagnetism. It gives exactly the same results as obtained in the standard model for electroweak interactions.

hep-ph↗
arXiv2002

Recent measurements of proton electric form factor and antiproton-proton elastic scattering

The Chou-Yang model based on multiple diffraction theory has already been used by us to predict the characteristics of antiproton-proton elastic scattering at very high energies. But the recent precise data on proton elastic form factor obtained at JLab essentially deviates from the dipole approximation. We have parametrized the data for the form factor. The computations have been made by using the new expression for the form factor. The implications of the new form factor on the characteristics of antiproton-proton elastic scattering at very high energy have been studied.

hep-ph↗