Physical Layer Security: Detection of Active Eavesdropping Attacks by Support Vector Machines

This article presents a framework for converting wireless signals into structured datasets, which can be fed into machine learning algorithms for the detection of active eavesdropping attacks at the physical layer. More specifically, a wireless communication system, which consists of an access point (AP), K legitimate users and an active eavesdropper, is considered. To detect the eavesdropper who breaks into the system during the authentication phase, we first build structured datasets based on different features and then apply sophisticated support vector machine (SVM) classifiers to those structured datasets. To be more specific, we first process the signals received by the AP and then define a pair of statistical features based on the post-processing of the signals. By arranging for the AP to simulate the entire process of transmission and the process of constructing features, we form the so-called artificial training data (ATD). By training SVM classifiers on the ATD, we classify the received signals associated with eavesdropping attacks and nonattacks, thereby detecting the presence of the eavesdropper. Two SVM classifiers are considered, including a classic twin-class SVM (TC-SVM) and a single-class SVM (SC-SVM). While the TC-SVM is preferred in the case of having perfect channel state information (CSI) of all channels, the SC-SVM is preferred in the realistic scenario when we have only the CSI of legitimate users. We also evaluate the accuracy of the trained models depending on the choice of kernel functions, the choice of features and on the eavesdropper's power. Our numerical results show that careful parameter-tuning is required for exceeding an eavesdropper detection probability of 95%

Comparative study about the performance of three types of modified natural treatment systems for rice noodle wastewater

© 2019 Elsevier Ltd In this study, three semi-pilot scale systems (vertical flow constructed wetland, multi-soil layering, and integrated hybrid systems) for treating real rice noodle wastewater were operated parallelly for the first time in a tropical climate at a loading rate of 50 L/(m2·d) for more than 7 months to determine the optimal conditions and to compare their treatment performance. The results demonstrated that these systems were appropriate for the removal of organics, suspended solids, and total coliform (Tcol). The highest reductions in chemical oxygen demand (CODCr, 73.2%), phosphorus (PO4-P, 54%), and Tcol (4.78 log MPN/100 mL inactivation) were obtained by the integrated hybrid system, while the highest removal efficiencies of ammonium (NH4-N, 60.64%) and suspended solids (80.49%) were achieved in the vertical-flow-constructed wetland and multi-soil layering systems respectively

Stem cell-based therapy for human diseases.

Recent advancements in stem cell technology open a new door for patients suffering from diseases and disorders that have yet to be treated. Stem cell-based therapy, including human pluripotent stem cells (hPSCs) and multipotent mesenchymal stem cells (MSCs), has recently emerged as a key player in regenerative medicine. hPSCs are defined as self-renewable cell types conferring the ability to differentiate into various cellular phenotypes of the human body, including three germ layers. MSCs are multipotent progenitor cells possessing self-renewal ability (limited in vitro) and differentiation potential into mesenchymal lineages, according to the International Society for Cell and Gene Therapy (ISCT). This review provides an update on recent clinical applications using either hPSCs or MSCs derived from bone marrow (BM), adipose tissue (AT), or the umbilical cord (UC) for the treatment of human diseases, including neurological disorders, pulmonary dysfunctions, metabolic/endocrine-related diseases, reproductive disorders, skin burns, and cardiovascular conditions. Moreover, we discuss our own clinical trial experiences on targeted therapies using MSCs in a clinical setting, and we propose and discuss the MSC tissue origin concept and how MSC origin may contribute to the role of MSCs in downstream applications, with the ultimate objective of facilitating translational research in regenerative medicine into clinical applications. The mechanisms discussed here support the proposed hypothesis that BM-MSCs are potentially good candidates for brain and spinal cord injury treatment, AT-MSCs are potentially good candidates for reproductive disorder treatment and skin regeneration, and UC-MSCs are potentially good candidates for pulmonary disease and acute respiratory distress syndrome treatment

A formal proof of the Kepler conjecture

This article describes a formal proof of the Kepler conjecture on dense sphere packings in a combination of the HOL Light and Isabelle proof assistants. This paper constitutes the official published account of the now completed Flyspeck project

Measurement of the Higgs boson production via vector boson fusion and its decay into bottom quarks in proton-proton collisions at s \sqrt{s} = 13 TeV

A preprint version of the article is available at arXiv:2308.01253v2 [hep-ex], https://arxiv.org/abs/2308.01253v2 . Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/HIG-22-009 (CMS Public Pages). Report number: CMS-HIG-22-009, CERN-EP-2023-110.A measurement of the Higgs boson (H) production via vector boson fusion (VBF) and its decay into a bottom quark-antiquark pair (bb¯) is presented using proton-proton collision data recorded by the CMS experiment at s√ = 13 TeV and corresponding to an integrated luminosity of 90.8 fb−1. Treating the gluon-gluon fusion process as a background and constraining its rate to the value expected in the standard model (SM) within uncertainties, the signal strength of the VBF process, defined as the ratio of the observed signal rate to that predicted by the SM, is measured to be μqqHHbb¯ = 1.01 +0.55−0.46. The VBF signal is observed with a significance of 2.4 standard deviations relative to the background prediction, while the expected significance is 2.7 standard deviations. Considering inclusive Higgs boson production and decay into bottom quarks, the signal strength is measured to be μincl.Hbb¯ = 0.99 +0.48−0.41, corresponding to an observed (expected) significance of 2.6 (2.9) standard deviations.SCOAP3, STFC; Marie-Curie program and the European Research Council and Horizon 2020 Gran

Search for dark matter particles in W+W− events with transverse momentum imbalance in proton-proton collisions at √s = 13 TeV

A preprint version of the article is available at arXiv:2310.12229v2 [hep-ex], https://arxiv.org/abs/2310.12229v2 . Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/EXO-21-012 (CMS Public Pages).A search for dark matter particles is performed using events with a pair of W bosons and large missing transverse momentum. Candidate events are selected by requiring one or two leptons (ℓ = electrons or muons). The analysis is based on proton-proton collision data collected at a center-of-mass energy of 13 TeV by the CMS experiment at the LHC and corresponding to an integrated luminosity of 138 fb−1. No significant excess over the expected standard model background is observed in the ℓνqq and 2ℓ2ν final states of the W+W− boson pair. Limits are set on dark matter production in the context of a simplified dark Higgs model, with a dark Higgs boson mass above the W+W− mass threshold. The dark matter phase space is probed in the mass range 100–300 GeV, extending the scope of previous searches. Current exclusion limits are improved in the range of dark Higgs masses from 160 to 250 GeV, for a dark matter mass of 200 GeV.SCOAP3

Search for direct production of GeV-scale resonances decaying to a pair of muons in proton-proton collisions at s\sqrt{s} = 13 TeV

A preprint version of the article is available at arXiv:2309.16003v2 [hep-ex], https://arxiv.org/abs/2309.16003v2 . Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables, including additional supplementary figures, can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/EXO-21-005 (CMS Public Pages). Report number: CMS-EXO-21-005, CERN-EP-2023-165.A search for direct production of low-mass dimuon resonances is performed using s√ = 13 TeV proton-proton collision data collected by the CMS experiment during the 2017-2018 operation of the CERN LHC with an integrated luminosity of 96.6 fb−1. The search exploits a dedicated high-rate trigger stream that records events with two muons with transverse momenta as low as 3 GeV but does not include the full event information. The search is performed by looking for narrow peaks in the dimuon mass spectrum in the ranges of 1.1-2.6 GeV and 4.2-7.9 GeV. No significant excess of events above the expectation from the standard model background is observed. Model-independent limits on production rates of dimuon resonances within the experimental fiducial acceptance are set. Competitive or world's best limits are set at 90% confidence level for a minimal dark photon model and for a scenario with two Higgs doublets and an extra complex scalar singlet (2HDM+S). Values of the squared kinetic mixing coefficient ε2 in the dark photon model above 10−6 are excluded over most of the mass range of the search. In the 2HDM+S, values of the mixing angle sin(θH) above 0.08 are excluded over most of the mass range of the search with a fixed ratio of the Higgs doublets vacuum expectation tanβ = 0.5.SCOAP3