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AutoEM is a software application intended to fully automate EM experiments. This automation includes incorporation of a Machine Learning component that will provide feedback analysis and experiment modification in a fully hands-free manner. AutoEM incorporates control of multiple devices, communication with external applications, and user visualization of images, device status, and ML feedback.
Network design goals are often functional with little consideration for security. Growth and maintenance of critical infrastructure mission-focused networks can be ad hoc and preclude large-scale technology replacements, reconfigurations, or even patching. These restrictions are contributing factors to increased vulnerabilities. Over 90% of all attacks begin with phishing and include lateral movement (Frinke 2019). Adopting a software-defined networking (SDN) approach is an effective mitigation strategy for many existing vulnerabilities. SDNs deny-by-default approach to networking restricts an adversary’s freedom of movement without impacting an organization’s mission. SDN implementations require a process that identifies an organization’s mission-specific network communications. A well-defined traffic engineering process ensures that only known devices communicate with each other on specific ports.
A system senses analytes through one or more sensors that detect or measure a physical characteristic. The one or more sensor generate a spectroscopic-data signal corresponding to the detection. An edge device communicatively couples the one or more sensors that communicatively couples a wide-area network coupling a cloud service. The edge device includes a data acquisition device that receives spectroscopic data signals from the one or more sensor and a processor that processes the spectroscopic-data signals to identify an analyte. The edge device also includes a transceiver that transmits data identifying the analytes to the cloud service.
The penetration of distributed energy resources (DER) is growing at much higher rates than predicted 20 years ago. Far from being used only in residential settings, DER are now installed on distribution and transmission circuits. In this position, they do not have the same properties as traditional generators and are more flexible in many cases. The growing penetration and range of uses for DER motivate the need to reliably and safely integrate them into the grid. Operators must be able to rely on them not only for normal operation, but also during abnormal conditions like black starts or adverse cyber scenarios. To that end, we study the communications, device interfaces, and potential consequences of DER operation under abnormal and adversarial conditions. The weaknesses of communications networks are studied based on the industrial protocols used, and the benefits of security features are examined. The device interfaces are found to be vulnerable to attack based on the requirements in the IEEE-1547 standard for DER interconnection and interoperability, which is expected to be adopted in the next ten years. In addition to exploring the requirements of the standard, we show that these vulnerabilities and others do exist and can be used maliciously in a modern storage system DER. Consequences of these vulnerabilities range from exacerbated grid instability, to simultaneous loss of large portions of DER penetration, to physical damage to inverters or DER themselves and other sensitive equipment. We tie these outcomes to specific attacker actions in an effort to give operators a better threat intelligence view that allows them to prioritize mitigations. Finally, we discuss mitigations that could prevent many of the adversarial scenarios described. Some solutions can be added to existing infrastructure, while others may require longer term planning for grid modernization with consideration for security.
Presentation about development of a small, inexpensive sensing and communications device meant for persistent monitoring in a wide range of circumstances. The device provides light, IR, infrasound, sound, ultrasound, magnetometer, accelerometer, temperature, pressure, humidity, and GPS sensing.
While wearable technologies have taken essential parts of our daily lives, concerns on human health are often overseen. Mainly due to extreme proximity or direct physical contact to human skin, wearable communications devices are prone to cause higher levels of electromagnetic field (EMF) exposure at human skin surface than any other type of wireless technologies. Nevertheless, while focusing on theoretical aspects of human EMF exposure in wearable communications, prior work paid little to no attention on exact exposure levels generated by commercial wearable devices that are already widely used by public consumers. In this context, this paper provides an extensive review of SAR from various commercial wearable devices that are currently sold in the market, as well as the analytical framework and the current measurement methodologies for standard compliance tests. To extend the discussion to general wearable communications, this paper presents simulation results adopting representative antenna patterns, which leads to suggestion of separation distances to keep the current safety guidelines. In particular, considering the increasing interest in millimeter wave (mmW), this paper sheds light on EMF exposure evaluated at 60 GHz and compares to results from 2.4 GHz.
Described herein are devices and techniques for remotely controlling user access to a restricted computer resource. The process includes obtaining an image from a communication device of a user. An individual and a landmark are identified within the image. Determinations are made that the individual is the user and that the landmark is a predetermined landmark. Access to a restricted computing resource is granted based on the determining that the individual is the user and that the landmark is the predetermined landmark. Other embodiments are disclosed.
RMEM - a prototyping platform to explore the usage of RMA-based strategies in GPU-to-GPU communication. The implementation relies on libfabric (BSD-2 or GNUv2) to explore different synchronization approach and their associated performance. It is compatible with different network technologies such as InfiniBand, SlingShot-11, and TCP. It provides to the user host-to-host and device-to-device communication. The latter can be initiated either from the host, or from the device.
Simple and easily integrated design of flexible and transparent electrode materials affixed to polymer-based substrates hold great promise to have a revolutionary impact on the functionality and performance of energy storage devices for many future consumer electronics. Among these applications are touch sensors, roll-up displays, photovoltaic cells, health monitors, wireless sensors, and wearable communication devices. Here, we report an environmentally friendly, simple, and versatile approach to produce optically transparent and mechanically flexible all-solid-state supercapacitor devices. These supercapacitors were constructed on tin-doped indium oxide coated polyethylene terephthalate substrates by intercalation of a polymer-based gel electrolyte between two reduced graphene oxide (rGO) thin-film electrodes. The rGO electrodes were fabricated simply by drop-casting of graphene oxide (GO) films, followed by a novel low-temperature (≤250 °C) vacuum-assisted annealing approach for the in situ reduction of GO to rGO. A trade-off between the optical transparency and electrochemical performance is determined by the concentration of the GO in the initial dispersion, whereby the highest capacitance (~650 μF cm –2 ) occurs at a relatively lower optical transmittance (24%). Notably, the all-solid-state supercapacitors demonstrated excellent mechanical flexibility with a capacity retention rate above 90% under various bending angles and cycles. In conclusion, these attributes underscore the potential of the present approach to provide a path toward the realization of thin-film-based supercapacitors as flexible and transparent energy storage devices for a variety of practical applications.
The annual reports of organizations are a recurring type of public disclosure that communicates what an organization has done and/or plans to do. Worldwide, organizations use annual reports as powerful instruments for communication that is rich in narrative content and visuals. From the perspective of the leadership of an organization, statutory annual reports are communication devices to stakeholders. By analogy, from the perspective of stakeholders, the annual reports are learning devices that presents stakeholders with contents to generate knowledge about an organization. We have chosen the online accessible U.S. Department of Energy (DOE) Annual Site Environmental Reports (ASERs) as a collection of resources for communicating and learning the environmental management strategies on environmental compliance and environmental sustainability. Environmental Compliance 'consists of regulatory compliance and monitoring programs that implement federal, state, and local requirements, agreements, and permits.' Environmental Sustainability 'promotes and integrates initiatives such as energy and natural resource conservation, waste minimization, green remediation, and the use of sustainable products and services.' Interactive visualizations of textual data designed with visual analytics software can allow stakeholders to interact with statements on the environmental management strategies by performing diverse actions that promote learning. These actions include annotating, comparing, filtering, navigating, selecting and sharing relevant statements. We expect that the possibility of these multiple actions in an interactive manner help stakeholders to learn more effectively about the environmental strategies at U.S. DOE sites. The current case study for the project is a collection of 1,894 annotated (value-added) statements (sentence text) from the eight chapters of the 2017 Savanah River Site (SRS) annual site environmental report. The preliminary interactive visualizations are available online. (authors)
A transceiver device for receiving an interrogation signal at a first carrier frequency and for transmitting a response signal at a second carrier frequency is disclosed. The interrogation signal comprises the first carrier frequency modulated at the second carrier frequency. The communication device includes a sensor coupled to a demodulator. The sensor receives a low frequency input used to further modulate the interrogation signal. The demodulator demodulates the low frequency input from the first carrier frequency to thereby generate the response signal comprising the second carrier frequency and the low frequency input. The demodulator preferably includes a pyroelectric demodulator, a piezoelectric demodulator, or a detector diode. The demodulator preferably has a frequency response less than the first carrier frequency but greater than the second carrier frequency.
This effort explores modeling cyber infrastructure, including communication devices like switches, routers, sensors, and controllers, and physical media attributes like propagation of radio signals, in coordination with power distribution system model layouts. To do this, the project studies real-world configurations to define axioms of how different communication media is deployed with control equipment. These axioms will be used to develop tools to generate realistic cyber infrastructure models from starting power system models. This effort leverages and builds on the co-simulation platform developed by the other RD2C projects. The axioms and tools will be validated and demonstrated with the NS3 simulation tool as part of a co-simulation to show the behavior/impacts of cyber infrastructure on control operations.
While the Experimental Physics and Industrial Control System (EPICS) is widely used at large laboratories for slow controls and instrumentation, the deployment of a full EPICS installation can be difficult, with a steep learning curve to new users. Taking advantage of the pythonSoftIOC module, we developed an EPICS slow controls implementation for Jefferson Lab's Hall B cryotarget written entirely in Python and based on software IOCs that communicate with instruments over Ethernet. Here, this system ran successfully, interfacing with Jefferson Lab's full EPICS network, and we offer it as an example of the capabilities of pythonSoftIOC to build lightweight, yet robust and flexible instrumentation platforms that would be easily adapted for use at a small-scale laboratory. University groups can use these examples to build complete slow controls systems, from device communication to data archiving and display, using open-source, mature EPICS tools and student-friendly Python as an alternative to expensive and proprietary systems such as LabVIEW.
Photonic crystals containing graphene nanolayers have been attracting increasing attention due to their distinctive properties. In this paper, we present a theoretical analysis on the transmission properties of magneto-photonic crystals containing graphene nanolayers by using the transfer matrix method. The investigation shows that unidirectional defect modes with high transmittance can be achieved in the proposed structure, and broad flat-top photonic conduction bands (PCBs) can also be found between the graphene-induced photonic band gap and the Bragg gap. Furthermore, the study on the PCBs indicates that the relationship between the number of PCBs (n) and the period number of the structure (N) can be expressed as n = N − 1(N = 2,3,4…). And, new and unexpected photonic band gaps among PCBs are observed. The effects of chemical potential of graphene, thickness of defect layer, and incident angle on transmission properties are also discussed. The research results may provide a valuable reference for the design and fabrication of optical communication devices, such as isolators, switches, multichannel filters, and so on.
Resource constraints on the computing continuum require that we make smart decisions for serving AI-based services at the network edge. AI-based services typically have multiple implementations (e.g., image classification implementations include SqueezeNet, DenseNet, and others) with varying trade-offs (e.g., latency and accuracy). The question then is how should AI-based services be placed across Function-as-a-Service (FaaS) based edge computing systems in order to maximize total Quality-of-Service (QoS). To address this question, we propose a problem that jointly aims to solve (i) edge AI service placement and (ii) request scheduling. These are done across two time-scales (one for placement and one for scheduling). Here we first cast the problem as an integer linear program. We then decompose the problem into separate placement and scheduling subproblems and prove that both are NP-hard. We then propose a novel placement algorithm that places services while considering device-to-device communication across edge clouds to offload requests to one another. Our results show that the proposed placement algorithm is able to outperform a state-of-the-art placement algorithm for AI-based services, and other baseline heuristics, with regard to maximizing total QoS. Additionally, we present a federated learning-based framework, FLIES, to predict the future incoming service requests and their QoS requirements. Our results also show that our FLIES algorithm is able to outperform a standard decentralized learning baseline for predicting incoming requests and show comparable predictive performance when compared to centralized training.
Coal fly ash (CFA) is both a valuable waste material and a potential source of environmental contamination. The inclusion of metals such as rare-earth elements offer a possible incentive towards waste valorization if the metals can be extracted and recovered in an economical manner. Rare-earth elements (REEs) have many technological applications and are critically important in the manufacture of electric vehicles, communication devices, and industrial magnets. However, the global supply of rare-earth elements has faced shortages and price shocks. Current methods for separating and isolating individual rare-earth elements use large amounts of energy and organic solvents, raising concerns over environmental impacts. These factors have led to the investigation of nontraditional sources and separation techniques for these elements. Here, we describe a column-based system that uses a newly developed ligand-associated organosilica sorbent to concentrate and separate rare-earth elements from fly ash leachate. The fly ash used in this study originally contained 0.024 wt% rare-earth elements and the final oxide powder after enrichment contained > 10 wt% rare-earth elements, which is a enrichment of > 400 times. This process requires no additional organic solvents after the sorbent media has been synthesized, offering an alternative to the current standard using solvent extraction for rare-earth element recovery.
Pure spin currents, unaccompanied by dissipative charge flow, are essential for realizing energy-efficient nanomagnetic information and communications devices. Thin-film magnetic insulators have been identified as promising materials for spin-current technology because they are thought to exhibit lower damping compared with their metallic counterparts. However, insulating behavior is not a sufficient requirement for low damping, as evidenced by the very limited options for low-damping insulators. Here, we demonstrate a new class of nanometer-thick ultralow-damping insulating thin films based on design criteria that minimize orbital angular momentum and structural disorder. Specifically, we show ultralow damping in <20 nm thick spinel-structure magnesium aluminum ferrite (MAFO), in which magnetization arises from Fe 3+ ions with zero orbital angular momentum. Here, these epitaxial MAFO thin films exhibit a Gilbert damping parameter of ~0.0015 and negligible inhomogeneous linewidth broadening, resulting in narrow half width at half-maximum linewidths of ~0.6 mT around 10 GHz. Our findings offer an attractive thin-film platform for enabling integrated insulating spintronics.
Methods to integrate different crystal orientations, strain states, and compositions of semiconductors in planar and preferably flexible configurations may enable nontraditional sensing-, stimulating-, or communication-device applications. Here, we combine crystalline-silicon nanomembranes, patterning, membrane transfer, and epitaxial growth to demonstrate planar arrays of different orientations and strain states of Si in a single membrane, which is then readily transferable to other substrates, including flexible supports. As examples, regions of Si(001) and Si(110) or strained Si(110) are combined to form a multicomponent, single substrate with high-quality narrow interfaces. We perform extensive structural characterization of all interfaces and measure charge-carrier mobilities in different regions of a 2D quilt. The method is readily extendable to include varying compositions or different classes of materials.