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1. Mitigating RF Jamming Attacks at the Physical Layer with Machine Learning Dataset

   https://doi.org/10.5281/zenodo.6304194  

   Jacovic, Marko ; Rivas, Xaime Rey ( January 2022 )

   Abstract

   <p>Data files were used in support of the research paper titled “<em>Mitigating RF Jamming Attacks at the Physical Layer with Machine Learning</em>&#34; which has been submitted to the IET Communications journal.</p> <p>---------------------------------------------------------------------------------------------</p> <p>All data was collected using the SDR implementation shown here: https://github.com/mainland/dragonradio/tree/iet-paper. Particularly for antenna state selection, the files developed for this paper are located in &#39;dragonradio/scripts/:&#39;</p> <ul><li>&#39;ModeSelect.py&#39;: class used to defined the antenna state selection algorithm</li><li>&#39;standalone-radio.py&#39;: SDR implementation for normal radio operation with reconfigurable antenna</li><li>&#39;standalone-radio-tuning.py&#39;: SDR implementation for hyperparameter tunning</li><li>&#39;standalone-radio-onmi.py&#39;: SDR implementation for omnidirectional mode only</li></ul> <p>---------------------------------------------------------------------------------------------</p> <p>Authors: Marko Jacovic, Xaime Rivas Rey, Geoffrey Mainland, Kapil R. Dandekar<br /> Contact: krd26&#64;drexel.edu</p> <p>---------------------------------------------------------------------------------------------</p> <p>Top-level directories and content will be described below. Detailed descriptions of experiments performed are provided in the paper.</p> <p>---------------------------------------------------------------------------------------------</p> <p>classifier_training: files used for training classifiers that are integrated into SDR platform</p> <ul><li>&#39;logs-8-18&#39; directory contains OTA SDR collected log files for each jammer type and under normal operation (including congested and weaklink states)</li><li>&#39;classTrain.py&#39; is the main parser for training the classifiers</li><li>&#39;trainedClassifiers&#39; contains the output classifiers generated by &#39;classTrain.py&#39;</li></ul> <p>post_processing_classifier: contains logs of online classifier outputs and processing script</p> <ul><li>&#39;class&#39; directory contains .csv logs of each RTE and OTA experiment for each jamming and operation scenario</li><li>&#39;classProcess.py&#39; parses the log files and provides classification report and confusion matrix for each multi-class and binary classifiers for each observed scenario - found in &#39;results-&gt;classifier_performance&#39;</li></ul> <p>post_processing_mgen: contains MGEN receiver logs and parser</p> <ul><li>&#39;configs&#39; contains JSON files to be used with parser for each experiment</li><li>&#39;mgenLogs&#39; contains MGEN receiver logs for each OTA and RTE experiment described. Within each experiment logs are separated by &#39;mit&#39; for mitigation used, &#39;nj&#39; for no jammer, and &#39;noMit&#39; for no mitigation technique used. File names take the form *_cj_* for constant jammer, *_pj_* for periodic jammer, *_rj_* for reactive jammer, and *_nj_* for no jammer. Performance figures are found in &#39;results-&gt;mitigation_performance&#39;</li></ul> <p>ray_tracing_emulation: contains files related to Drexel area, Art Museum, and UAV Drexel area validation RTE studies.</p> <ul><li>Directory contains detailed &#39;readme.txt&#39; for understanding.</li><li>Please note: the processing files and data logs present in &#39;validation&#39; folder were developed by Wolfe et al. and should be cited as such, unless explicitly stated differently.  <ul><li>S. Wolfe, S. Begashaw, Y. Liu and K. R. Dandekar, &#34;Adaptive Link Optimization for 802.11 UAV Uplink Using a Reconfigurable Antenna,&#34; MILCOM 2018 - 2018 IEEE Military Communications Conference (MILCOM), 2018, pp. 1-6, doi: 10.1109/MILCOM.2018.8599696.</li></ul> </li></ul> <p>results: contains results obtained from study</p> <ul><li>&#39;classifier_performance&#39; contains .txt files summarizing binary and multi-class performance of online SDR system. Files obtained using &#39;post_processing_classifier.&#39;</li><li>&#39;mitigation_performance&#39; contains figures generated by &#39;post_processing_mgen.&#39;</li><li>&#39;validation&#39; contains RTE and OTA performance comparison obtained by &#39;ray_tracing_emulation-&gt;validation-&gt;matlab-&gt;outdoor_hover_plots.m&#39;</li></ul> <p>tuning_parameter_study: contains the OTA log files for antenna state selection hyperparameter study</p> <ul><li>&#39;dataCollect&#39; contains a folder for each jammer considered in the study, and inside each folder there is a CSV file corresponding to a different configuration of the learning parameters of the reconfigurable antenna. The configuration selected was the one that performed the best across all these experiments and is described in the paper.</li><li>&#39;data_summary.txt&#39;this file contains the summaries from all the CSV files for convenience.</li></ul>
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2. ASYMPTOTIC SIZE OF KLEIBERGEN’S LM AND CONDITIONAL LR TESTS FOR MOMENT CONDITION MODELS

   https://doi.org/10.1017/S0266466616000347  

   Andrews, Donald W.K. ; Guggenberger, Patrik ( October 2017 , Econometric Theory)

   An influential paper by Kleibergen (2005, Econometrica 73, 1103–1123) introduces Lagrange multiplier (LM) and conditional likelihood ratio-like (CLR) tests for nonlinear moment condition models. These procedures aim to have good size performance even when the parameters are unidentified or poorly identified. However, the asymptotic size and similarity (in a uniform sense) of these procedures have not been determined in the literature. This paper does so. This paper shows that the LM test has correct asymptotic size and is asymptotically similar for a suitably chosen parameter space of null distributions. It shows that the CLR tests also have these properties when the dimension p of the unknown parameter θ equals 1. When p ≥ 2, however, the asymptotic size properties are found to depend on how the conditioning statistic, upon which the CLR tests depend, is weighted. Two weighting methods have been suggested in the literature. The paper shows that the CLR tests are guaranteed to have correct asymptotic size when p ≥ 2 when the weighting is based on an estimator of the variance of the sample moments, i.e., moment-variance weighting, combined with the Robin and Smith (2000, Econometric Theory 16, 151–175) rank statistic. The paper also determines a formulamore »for the asymptotic size of the CLR test when the weighting is based on an estimator of the variance of the sample Jacobian. However, the results of the paper do not guarantee correct asymptotic size when p ≥ 2 with the Jacobian-variance weighting, combined with the Robin and Smith (2000, Econometric Theory 16, 151–175) rank statistic, because two key sample quantities are not necessarily asymptotically independent under some identification scenarios. Analogous results for confidence sets are provided. Even for the special case of a linear instrumental variable regression model with two or more right-hand side endogenous variables, the results of the paper are new to the literature.« less
3. Experimentation Framework for Wireless Communication Systems under Jamming Scenarios Dataset

   https://doi.org/10.5281/zenodo.4749668  

   Jacovic, Marko ( January 2021 )

   Abstract

   <p>Data files were used in support of the research paper titled &#34;“Experimentation Framework for Wireless<br /> Communication Systems under Jamming Scenarios&#34; which has been submitted to the IET Cyber-Physical Systems: Theory &amp; Applications journal. </p> <p>Authors: Marko Jacovic, Michael J. Liston, Vasil Pano, Geoffrey Mainland, Kapil R. Dandekar<br /> Contact: krd26&#64;drexel.edu</p> <p>---------------------------------------------------------------------------------------------</p> <p>Top-level directories correspond to the case studies discussed in the paper. Each includes the sub-directories: logs, parsers, rayTracingEmulation, results. </p> <p>--------------------------------</p> <p>logs:    - data logs collected from devices under test<br />     - &#39;defenseInfrastucture&#39; contains console output from a WARP 802.11 reference design network. Filename structure follows &#39;*x*dB_*y*.txt&#39; in which *x* is the reactive jamming power level and *y* is the jaming duration in samples (100k samples &#61; 1 ms). &#39;noJammer.txt&#39; does not include the jammer and is a base-line case. &#39;outMedian.txt&#39; contains the median statistics for log files collected prior to the inclusion of the calculation in the processing script. <br />     - &#39;uavCommunication&#39; contains MGEN logs at each receiver for cases using omni-directional and RALA antennas with a 10 dB constant jammer and without the jammer. Omni-directional folder contains multiple repeated experiments to provide reliable results during each calculation window. RALA directories use s*N* folders in which *N* represents each antenna state. <br />     - &#39;vehicularTechnologies&#39; contains MGEN logs at the car receiver for different scenarios. &#39;rxNj_5rep.drc&#39; does not consider jammers present, &#39;rx33J_5rep.drc&#39; introduces the periodic jammer, in &#39;rx33jSched_5rep.drc&#39; the device under test uses time scheduling around the periodic jammer, in &#39;rx33JSchedRandom_5rep.drc&#39; the same modified time schedule is used with a random jammer. </p> <p>--------------------------------</p> <p>parsers:    - scripts used to collect or process the log files used in the study<br />         - &#39;defenseInfrastructure&#39; contains the &#39;xputFiveNodes.py&#39; script which is used to control and log the throughput of a 5-node WARP 802.11 reference design network. Log files are manually inspected to generate results (end of log file provides a summary). <br />         - &#39;uavCommunication&#39; contains a &#39;readMe.txt&#39; file which describes the parsing of the MGEN logs using TRPR. TRPR must be installed to run the scripts and directory locations must be updated. <br />         - &#39;vehicularTechnologies&#39; contains the &#39;mgenParser.py&#39; script and supporting &#39;bfb.json&#39; configuration file which also require TRPR to be installed and directories to be updated. </p> <p>--------------------------------</p> <p>rayTracingEmulation:    - &#39;wirelessInsiteImages&#39;: images of model used in Wireless Insite<br />             - &#39;channelSummary.pdf&#39;: summary of channel statistics from ray-tracing study<br />             - &#39;rawScenario&#39;: scenario files resulting from code base directly from ray-tracing output based on configuration defined by &#39;*WI.json&#39; file <br />             - &#39;processedScenario&#39;: pre-processed scenario file to be used by DYSE channel emulator based on configuration defined by &#39;*DYSE.json&#39; file, applies fixed attenuation measured externally by spectrum analyzer and additional transmit power per node if desired<br />             - DYSE scenario file format: time stamp (milli seconds), receiver ID, transmitter ID, main path gain (dB), main path phase (radians), main path delay (micro seconds), Doppler shift (Hz), multipath 1 gain (dB), multipath 1 phase (radians), multipath 1 delay relative to main path delay (micro seconds), multipath 2 gain (dB), multipath 2 phase (radians), multipath 2 delay relative to main path delay (micro seconds)<br />             - &#39;nodeMapping.txt&#39;: mapping of Wireless Insite transceivers to DYSE channel emulator physical connections required<br />             - &#39;uavCommunication&#39; directory additionally includes &#39;antennaPattern&#39; which contains the RALA pattern data for the omni-directional mode (&#39;omni.csv&#39;) and directional state (&#39;90.csv&#39;)</p> <p>--------------------------------</p> <p>results:    - contains performance results used in paper based on parsing of aforementioned log files<br />  </p>
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4. Smart paper transformer: new insight for enhanced catalytic efficiency and reusability of noble metal nanocatalysts

   https://doi.org/10.1039/c9sc05287a  

   Jin, Qijie ; Ma, Lei ; Zhou, Wan ; Shen, Yuesong ; Fernandez-Delgado, Olivia ; Li, XiuJun ( March 2020 , Chemical Science)

   Although noble metal nanocatalysts show superior performance to conventional catalysts, they can be problematic when balancing catalytic efficiency and reusability. In order to address this dilemma, we developed a smart paper transformer (s-PAT) to support nanocatalysts, based on easy phase conversion between paper and pulp, for the first time. The pulp phase was used to maintain the high catalytic efficiency of the nanocatalysts and the transformation to paper enabled their high reusability. Herein, as an example of smart paper transformers, a novel chromatography paper-supported Au nanosponge (AuNS/pulp) catalyst was developed through a simple water-based preparation process for the successful reduction of p -nitrophenol to demonstrate the high catalytic efficiency and reusability of the noble metal nanocatalyst/pulp system. The composition, structure, and morphology of the AuNS/pulp catalyst were characterized by XRD, TGA, FE-SEM, ICP, TEM, FT-IR, and XPS. The AuNS/pulp catalyst was transformed into the pulp phase during the catalytic reaction and into the paper phase to recover the catalysts after use. Owing to this smart switching of physical morphology, the AuNS/pulp catalyst was dispersed more evenly in the solution. Therefore, it exhibited excellent catalytic performance for p -nitrophenol reduction. Under optimal conditions, the conversion rate of p -nitrophenol reached nearlymore »100% within 6 min and the k value of AuNS/pulp (0.0106 s −1 ) was more than twice that of a traditional chromatography paper-based catalyst (0.0048 s −1 ). Additionally, it exhibited outstanding reusability and could maintain its high catalytic efficiency even after fifteen recycling runs. Accordingly, the unique phase switching of this smart paper transformer enables Au nanosponge to transform into a highly efficient and cost-effective multifunctional catalyst. The paper transformer can support various nanocatalysts for a wide range of applications, thus providing a new insight into maintaining both high catalytic efficiency and reusability of nanocatalysts in the fields of environmental catalysis and nanomaterials.« less
5. Behavioral interactions of bed bugs with long-lasting pyrethroid-treated bed nets: challenges for vector control

   https://doi.org/10.1186/s13071-022-05613-z  

   Hayes, Christopher C. ; Schal, Coby ( December 2022 , Parasites & Vectors)

   Widespread vector control has been essential in reducing the global incidence and prevalence of malaria, despite now stalled progress. Long-lasting insecticide-treated nets (LLINs) have historically been, and remain, one of the most commonly used vector control tools in the campaign against malaria. LLINs are effective only with proper use, adherence, retention and community adoption, which historically have relied on the successful control of secondary pests, including bed bugs. The emergence of pyrethroid-resistant bed bugs in malaria-endemic communities and failure to control infestations have been suggested to interfere with the effective use of LLINs. Therefore, the behavioral interactions of bed bugs with commonly used bed nets should be better understood.

   To investigate the interactions between bed bugs (Cimex lectulariusL.) and LLINs, insecticide-susceptible and pyrethroid-resistant bed bugs were challenged to pass through two commonly used LLINs in two behavioral assays, namely host (blood meal)-seeking and aggregation-seeking assays. The proportions blood-fed and aggregated bed bugs, aggregation time and mortality were quantified and analyzed in different bed bug life stages.

   Overall, both the insecticide-susceptible bed bugs and highly resistant bed bugs showed a varying ability to pass through LLINs based on treatment status and net design. Deltamethrin-treated nets significantly impeded both feeding andmore »aggregation by the susceptible bed bugs. While none of the tested LLINs significantly impeded feeding (passage of unfed bed bugs through the nets) of the pyrethroid-resistant bed bugs, the untreated bed net, which has small mesh holes, impeded passage of fed bed bugs. Mortality was only seen in the susceptible bed bugs, with significantly higher mortality on deltamethrin-treated nets (63.5 ± 10.7%) than on permethrin-treated nets (2.0 ± 0.9%).

   Commonly used new LLINs failed to prevent the passage of susceptible and pyrethroid-resistant bed bugs in host- and aggregation-seeking bioassays. The overall low and variable mortality observed in susceptible bed bugs during both assays highlighted the potential of LLINs to impose strong selection pressure for the evolution of pyrethroid resistance. Already, the failure to control bed bug infestations has been implicated as a contributing factor to the abandonment or misuse of LLINs. For the first time to our knowledge, we have shown the potential of LLINs in selecting for resistant secondary pest populations and so their potential role in stalling malaria control programs should be further investigated.

   The emergence of pyrethroid-resistant bed bugs in malaria-endemic communities may interfere with the effective use of pyrethroid-impregnated bed nets. We assessed the interactions of two bed bug strains with commonly used bed nets using two behavioral assays, namely host (blood meal)-seeking by unfed bed bugs and aggregation-seeking by freshly fed bed bugs. These assays assessed the passage of bed bugs through various bed nets in response to host cues and aggregation stimuli, respectively. Conditioned paper is a section of file folder paper that has been exposed to bed bugs and has been impregnated with feces and aggregation pheromone; it is attractive to aggregation-seeking fed bed bugs. An unconditioned ramp is a similar section of file folder paper that allows bed bugs to traverse the bed net and gain access to a blood-meal source.

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