arXiv subjects

Muhammad Ismail

Publications and source records attributed to Muhammad Ismail.

23 records · Page 2Linked to original sources

arXiv2020

Metastatic melanoma-A review of current and future perspective

Metastatic Melanoma, the fifth most common cancer in the western countries and the most common malignancy diagnosed in United States present itself as the most lethal treatment resistant cancer worldwide. In addition to the reactive oxygen species(ROS), mutations in the genes encoding receptors and non-receptor tyrosine/serene/threonine protein kinases are known to be involved in its etiology. Kinases are molecular players of cell survival, growth, and proliferation and migration that mediate their effects via various signal transduction pathways. A number of such molecular players have been previously found to be mutated and hyper phosphorylated in melanoma. Although, several systemic therapies including cytotoxic chemotherapy, targeted drugs, hormonal therapy, radiation therapy, bio-chemotherapy, and therapies that inhibit negative regulation of immune system have been approved from U. S. Food and Drug Administration (FDA) for metastatic melanoma treatment. However, no systemic therapy has meaningfully changed its survival end points so far and surgery still presents primary treatment option for advanced and metastatic melanomaa due to its highly resistant nature towards systemic drugs, high rate of severe, life-threatening, or fatal side effects, and un satisfactory overall response rate. Therefore, there is still a need to develop therapies that target the unique molecular profile of melanoma tumors.

q-bio.MN↗

arXiv2019

Blockchain-based Charging Coordination Mechanism for Smart Grid Energy Storage Units

Energy storage units (ESUs) enable several attractive features of modern smart grids such as enhanced grid resilience, effective demand response, and reduced bills. However, uncoordinated charging of ESUs stresses the power system and can lead to a blackout. On the other hand, existing charging coordination mechanisms suffer from several limitations. First, the need for a central charging coordinator (CC) presents a single point of failure that jeopardizes the effectiveness of the charging coordination. Second, a transparent charging coordination mechanism does not exist where users are not aware whether the CC is honest or not in coordination charging requests among them in a fair way. Third, existing mechanisms overlook the privacy concerns of the involved customers. To address these limitations, in this paper, we leverage the blockchain and smart contracts to build a decentralized charging coordination mechanism without the need for a centralized charging coordinator. First ESUs should use tokens for anonymously authenticate themselves to the blockchain. Then each ESU sends a charging request that contains its State-of-Charge (SoC), Time-to-complete-charge (TCC) and amount of required charging to the smart contract address on the blockchain. The smart contract will then run the charging coordination mechanism in a self-executed manner such that ESUs with the highest priorities are charged in the present time slot while charging requests of lower priority ESUs are deferred to future time slots. In this way, each ESU can make sure that charging schedules are computed correctly. Finally, we have implemented the proposed mechanism on the Ethereum test-bed blockchain, and our analysis shows that execution cost can be acceptable in terms of gas consumption while enabling decentralized charging coordination with increased transparency, reliability, and privacy preserving.

cs.CR↗

arXiv2019

A New Weighting Scheme in Weighted Markov Model for Predicting the Probability of Drought Episodes

Drought is a complex stochastic natural hazard caused by prolonged shortage of rainfall. Several environmental factors are involved in determining drought classes at the specific monitoring station. Therefore, efficient sequence processing techniques are required to explore and predict the periodic information about the various episodes of drought classes. In this study, we proposed a new weighting scheme to predict the probability of various drought classes under Weighted Markov Chain (WMC) model. We provide a standardized scheme of weights for ordinal sequences of drought classifications by normalizing squared weighted Cohen Kappa. Illustrations of the proposed scheme are given by including temporal ordinal data on drought classes determined by the standardized precipitation temperature index (SPTI). Experimental results show that the proposed weighting scheme for WMC model is sufficiently flexible to address actual changes in drought classifications by restructuring the transient behavior of a Markov chain. In summary, this paper proposes a new weighting scheme to improve the accuracy of the WMC, specifically in the field of hydrology.

stat.AP↗

arXiv2018

Deep Recurrent Electricity Theft Detection in AMI Networks with Random Tuning of Hyper-parameters

Modern smart grids rely on advanced metering infrastructure (AMI) networks for monitoring and billing purposes. However, such an approach suffers from electricity theft cyberattacks. Different from the existing research that utilizes shallow, static, and customer-specific-based electricity theft detectors, this paper proposes a generalized deep recurrent neural network (RNN)-based electricity theft detector that can effectively thwart these cyberattacks. The proposed model exploits the time series nature of the customers' electricity consumption to implement a gated recurrent unit (GRU)-RNN, hence, improving the detection performance. In addition, the proposed RNN-based detector adopts a random search analysis in its learning stage to appropriately fine-tune its hyper-parameters. Extensive test studies are carried out to investigate the detector's performance using publicly available real data of 107,200 energy consumption days from 200 customers. Simulation results demonstrate the superior performance of the proposed detector compared with state-of-the-art electricity theft detectors.

cs.LG↗

arXiv2017

From D2D to Ds2D: Prolonging the Battery Life of Mobile Devices via Ds2D Communications

Emerging device centric systems (DCS) such as device-to-device (D2D) communications are considered as a standard part of future mobile networks, where operators/consumers involve the devices in direct communication to improve the cellular system throughput, latency, fairness, and energy efficiency. However, battery life of mobile devices involved in such communications is crucial for 5G smartphone users to explore the emerging applications in DCS. It is anticipated that the owners of 5G-enabled smartphones use their devices more extensively to talk, text, email, and surf the Web more often than do customers with 4G smartphones or traditional handsets, which puts a significantly higher demand on the battery life. Smartphones are currently equipped with multiple radio interfaces that enable them to access different types of wireless networks including LTE-direct and Wi-Fi-direct, besides cellular networks. Such a capability is not well explored within the context of DCS. This article proposes a new scheme to support the emerging features in DCS where a D2D-enabled mobile device (sink device or a file/content requester) aggregates the radio resources of multiple mobile devices (source devices or file/content providers) via its multiple radio interfaces such that the scheme is referred to as devices-to-device (Ds2D) communications. Ds2D communication scheme ensures an optimal packet split among the source mobile devices to improve the file/content transfer latency (FTL), energy efficiency, and battery life. Simulation results demonstrate that the proposed optimal packet split scheme among multiple source devices participating in Ds2D communication scheme guarantees an improvement in mobile battery life over wide range of data rate levels in comparison with the random packet split strategy and traditional D2D communication paradigm between the sink and source mobile devices.

cs.NI↗