The classical energy model for wireless interfaces was first established by Feeney and Nilsson (2001), and further confirmed by Ebert et al. (2002) and Shih, Bahl, and Sinclair (2002). Since then, it has been assumed that the network card dominates the consumption of wireless communications of mobile user devices.
Network and Systems: D. Roy Choudhary
On the other hand, all indicators show that we should expect an exponential grow in the number of wireless devices connected. Thus, there is a rough consensus about that densification will become one of the main aspects of next-generation wireless networks, which brings us back to the problem of packet overhearing. In this way, the recent 11ac amendment adds the ability to save energy during TXOPs, but this mechanism is restricted to QoS traffic, and the potential sleeps are coarse, in the range of milliseconds. Any sub-millisecond approach must take into account the timing parameters of the hardware. In fact, some early studies realise the importance of this issue when WiFi technology began to take off commercially (A. Kamerman and Monteban 1997; Havinga and Smit 2000; Jung and Vaidya 2002).
Besides that, the list of general-purpose DES frameworks is even more vast12, and most of them are unknown within the networking community because they are generally more suited for other fields, such as operations research. Among them, the SimPy Python package (Team SimPy 2017) has received increased attention, and has inspired similar frameworks for other languages, such as SimJulia (Lauwens 2017). Nonetheless, some studies showed that SimPy may not scale for large network simulations (Bahouth et al. 2007, @weingartner2009).
Research/Clinical Interest Title Computational Personalized Medicine and Mathematics Description My goals are (i) to apply mathematical tools to advance our understanding of basic medical sciences, (ii) to build computational tools that foster personalized medicine, and (iii) to advance mathematics. I have a multidisciplinary background in medicine, neurology, neuro-oncology, basic medical sciences, and pure and applied mathematics. I take care of patients with brain tumors and neurological diseases. Accurate and timely image segmentation can assist radiologists by transforming medical images into numerical schemes amenable to statistical analysis. I have also developed equations to model molecular networks and gliomas; the equations are built with the goal of approaching the simplest representation of current biological understanding. Simulations have uncovered novel ideas on the long-run behavior of circadian clocks and on fundamental properties of tumors like natural evolution, transformation, migration, recurrence patterns, and response to clinical trials (computational trials). These computational tools can advance medical practice by personalizing medical decisions and by optimizing the timing of delivery of care; examples include cancer, multiple sclerosis, and degenerative disorders of the brain.The models consist of new ordinary and partial differential equations; they pose problems that generate new computational and theoretical mathematics.
Selected Publications Publication PUBMEDID Inception Modules Enhance Brain Tumor Segmentation. Cahall, DE, Ghulam Rasool, G, Bouaynaya, NC , Fathallah-Shaykh, HM. Front. Comput. Neurosci. 2019, In Press, DOI: 10.3389/fncom.2019.00044. Diagnosing growth in low-grade gliomas with and without longitudinal volume measurements: A retrospective observational study Fathallah-Shaykh, HM, DeAtkine, A, Coffee, E, Khayat, E, Bag, AK, Han, X, Warren, PP, Bredel, M, Fiveash, J, Markert, J, Bouaynaya, N, Nabors, LN. 2019, PLoS Med 16 (5): e1002810. 1002810 Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS Challenge. Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipkova, John Freymann, Justin Kirby, Michel Bilello, Hassan Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc-Andre Weber, Abhishek Mahajan, Ujjwal Baid, Elizabeth Gerstner, Dongjin Kwon, Gagan Acharya, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Francisco J. Albiol, Varghese Alex, Nigel Allinson, Pedro H. A. Amorim, Abhijit Amrutkar, Ganesh Anand, Simon Andermatt, Tal Arbel, Pablo Arbelaez, Aaron Avery, Muneeza Azmat, Pranjal B., W Bai, Subhashis Banerjee, Bill Barth, Thomas Batchelder, Kayhan Batmanghelich, Enzo Battistella, Andrew Beers, Mikhail Belyaev, Martin Bendszus, Eze Benson, Jose Bernal, Halandur Nagaraja Bharath, George Biros, Sotirios Bisdas, James Brown, Mariano Cabezas, Shilei Cao, Jorge M. Cardoso, Eric N Carver, Adrià Casamitjana, Laura Silvana Castillo, Marcel Catà, Philippe Cattin, Albert Cerigues, Vinicius S. Chagas, Siddhartha Chandra, Yi-Ju Chang, Shiyu Chang, Ken Chang, Joseph Chazalon, Shengcong Chen, Wei Chen, Jefferson W Chen, Zhaolin Chen, Kun Cheng, Ahana Roy Choudhury, Roger Chylla, Albert Clérigues, Steven Colleman, Ramiro German Rodriguez Colmeiro, Marc Combalia, Anthony Costa, Xiaomeng Cui, Zhenzhen Dai, Lutao Dai, Laura Alexandra Daza, Eric Deutsch, Changxing Ding, Chao Dong, Shidu Dong, Wojciech Dudzik, Zach Eaton-Rosen, Gary Egan et al. arXiv:1811.02629v2. 2019 Mar 19. Approximate Kernel Reconstruction for Time-Varying Networks. Ditzler G, Bouaynaya N, Shterenberg R, Fathallah-Shaykh HM. BioData Min. 2019 Feb 6;12:5. doi: 10.1186/s13040-019-0192-1. eCollection 2019. 30774716 Global Asymptotic Stability in a Model of NetworksFathallah-Shaykh HM, Freiji A.Dynamical Systems, 2017, 2018, 1:159-183, DOI: 10.1080/14689367.2017.1326464. Key rates for the grades and transformation ability of glioma: model simulations and clinical cases.Scribner E, Hackney JR, Machemehl HC, Afiouni R, Patel KR, Fathallah-Shaykh HM.J Neurooncol. 2017 Apr 27. doi: 10.1007/s11060-017-2444-6. 28451993 Interactive Semi-automated Method Using Non-negative Matrix Factorization and Level Set Segmentation for the BRATS Challenge.Dera, D, Raman, R, Bouaynaya, N and Fathallah-Shaykh, HM. Crimi A,Menze B, Maier O, Reyes M, and Handels H (Eds.).Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017. Springer International Publishing AG. Single Cell Mathematical Model Successfully Replicates Key Features of GBM: Go-Or-Grow Is Not Necessary.Scribner E, Fathallah-Shaykh HM.PloS one. 2017; 12(1):e0169434. 28046101 The Case for Neurological Network Diseases.Machemehl H, Eloubeidi D, Fathallah-Shaykh H.JAMA neurology. 2016; 73(3):261-2. 26783994 Computational Trials: Unraveling Motility Phenotypes, Progression Patterns, and Treatment Options for Glioblastoma Multiforme.Raman F, Scribner E, Saut O, Wenger C, Colin T, Fathallah-Shaykh HM.PloS one. 2016; 11(1):e0146617. 26756205 Automated Robust Image Segmentation: Level Set Method Using Nonnegative Matrix Factorization with Application to Brain MRI.Dera D, Bouaynaya N, Fathallah-Shaykh HM.Bulletin of mathematical biology. 2016; 78(7):1450-76. 27417984 Phase I dose-escalation study of the PI3K/mTOR inhibitor voxtalisib (SAR245409, XL765) plus temozolomide with or without radiotherapy in patients with high-grade glioma.Wen PY, Omuro A, Ahluwalia MS, Fathallah-Shaykh HM, Mohile N, Lager JJ, Laird AD, Tang J, Jiang J, Egile C, Cloughesy TF.Neuro-oncology. 2015; 17(9):1275-83. 26019185 Effects of anti-angiogenesis on glioblastoma growth and migration: model to clinical predictions.Scribner E, Saut O, Province P, Bag A, Colin T, Fathallah-Shaykh HM.PloS one. 2014; 9(12):e115018. 25506702 A multilayer grow-or-go model for GBM: effects of invasive cells and anti-angiogenesis on growth.Saut O, Lagaert JB, Colin T, Fathallah-Shaykh HM.Bulletin of mathematical biology. 2014; 76(9):2306-33. 25149139 Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother.Khan J, Bouaynaya N, Fathallah-Shaykh HM.EURASIP journal on bioinformatics & systems biology. 2014; 2014(1):3. 24517200 Proper orthogonal decomposition for parameter estimation in oscillating biological networks.Rehm A, Scribner E, Fathallah-Shaykh HM.Journal of computational and applied mathematics. 2014 March 01; 258:135-150. c-Src and neural Wiskott-Aldrich syndrome protein (N-WASP) promote low oxygen-induced accelerated brain invasion by gliomas.Tang Z, Araysi LM, Fathallah-Shaykh HM.PloS one. 2013; 8(9):e75436. 24069415 Fractal dimension of the Drosophila circadian clock.Fathallah-Shaykh HM.Fractals. 2011 December; 19(4):423-430. Dynamics of the Drosophila circadian clock: theoretical anti-jitter network and controlled chaos.Fathallah-Shaykh HM.PloS one. 2010; 5(10):e11207. 20967246 Mathematical model of the Drosophila circadian clock: loop regulation and transcriptional integration.Fathallah-Shaykh HM, Bona JL, Kadener S.Biophysical journal. 2009; 97(9):2399-408. 19883582 Noise and rank-dependent geometrical filter improves sensitivity of highly specific discovery by microarrays.Fathallah-Shaykh HM.Bioinformatics (Oxford, England). 2005; 21(23):4255-62. 16179359 Logical networks inferred from highly specific discovery of transcriptionally regulated genes predict protein states in cultured gliomas.Fathallah-Shaykh HM.Biochemical and biophysical research communications. 2005; 336(4):1278-84. 16169516 Genomic discovery reveals a molecular system for resistance to oxidative and endoplasmic reticulum stress in cultured glioma.Fathallah-Shaykh HM.Archives of neurology. 2005; 62(2):233-6. 15710851 Mathematical algorithm for discovering states of expression from direct genetic comparison by microarrays.Fathallah-Shaykh HM, He B, Zhao LJ, Badruddin A.Nucleic acids research. 2004; 32(13):3807-14. 15266007 Genomic expression discovery predicts pathways and opposing functions behind phenotypes.Fathallah-Shaykh HM, He B, Zhao LJ, Engelhard HH, Cerullo L, Lichtor T, Byrne R, Munoz L, Von Roenn K, Rosseau GL, Glick R, Sherman C, Farooq K.The Journal of biological chemistry. 2003; 278(26):23830-3. 12700229 Mathematical modeling of noise and discovery of genetic expression classes in gliomas.Fathallah-Shaykh HM, Rigen M, Zhao LJ, Bansal K, He B, Engelhard HH, Cerullo L, Roenn KV, Byrne R, Munoz L, Rosseau GL, Glick R, Lichtor T, DiSavino E. Oncogene. 2002; 21(47):7164-74. 12370806 Gene transfer into brain parenchyma elicits antitumor effects.Fathallah-Shaykh HM, Kafrouni AI, Zhao LJ, Smith GM, Forman J.Cancer research. 2000; 60(7):1797-9. 10766160 Gene transfer of IFN-gamma into established brain tumors represses growth by antiangiogenesis.Fathallah-Shaykh HM, Zhao LJ, Kafrouni AI, Smith GM, Forman J.Journal of immunology (Baltimore, Md. : 1950). 2000; 164(1):217-22. 10605014 Priming in the brain, an immunologically privileged organ, elicits anti-tumor immunity.Fathallah-Shaykh HM, Gao W, Cho M, Herrera MA.International journal of cancer. 1998; 75(2):266-76. 9462718 Cloning of a leucine-zipper protein recognized by the sera of patients with antibody-associated paraneoplastic cerebellar degeneration.Fathallah-Shaykh H, Wolf S, Wong E, Posner JB, Furneaux HM.Proceedings of the National Academy of Sciences of the United States of America. 1991; 88(8):3451-4. 2014264 2ff7e9595c
Comments