Naval Information Warfare Center Atlantic

An epistemic logic program is a set of rules written in the language of Epistemic Specifications, an extension of the language of answer set programming that provides for more powerful introspective reasoning through the use of modal operators K and M. We propose adding a new construct to Epistemic Specifications called a world view constraint that provides a universal device for expressing global constraints in the various versions of the language. We further propose the use of subjective literals (literals preceded by K or M) in rule heads as syntactic sugar for world view constraints. Additionally, we provide an algorithm for finding the world views of such programs.

In the last decade, social network analysis (SNA) tools have gained considerable interest in intelligence and security communities, as terrorist networks have become more global, decentralized, and flexible. Additionally, recent concerns have been voiced that virtual worlds provide likely breeding grounds for terrorism recruitment, communication, and coordination activities. This paper outlines research involving a survey of the approaches criminal or terrorist groups can take to covertly advance their causes in virtual environments. In addition, a methodology for collecting, storing, and analyzing information about virtual world cyber-behaviors is presented. As an initial effort, data collection devices were created in the virtual world Second Life (SL). These devices are capable of recording a variety of behavioral data about avatars in SL, and then piping that information to an external database. Information from the database can then be analyzed using SNA. Preliminary results indicate that a combined approach utilizing manual and automated intelligence techniques along with SNA provide valuable insights into the structure, function, and key players within virtual world social networks.

Abstract The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) held seven targeted observing periods (TOPs) during the 2022 austral winter to enhance atmospheric predictability over the Southern Ocean and Antarctica. The TOPs of 5–10-day duration each featured the release of additional radiosonde balloons, more than doubling the routine sounding program at the 24 participating stations run by 14 nations, together with process-oriented observations at selected sites. These extra sounding data are evaluated for their impact on forecast skill via data denial experiments with the goal of refining the observing system to improve numerical weather prediction for winter conditions. Extensive observations focusing on clouds and precipitation primarily during atmospheric river (AR) events are being applied to refine model microphysical parameterizations for the ubiquitous mixed-phase clouds that frequently impact coastal Antarctica. Process studies are being facilitated by high-time-resolution series of observations and forecast model output via the YOPP Model Intercomparison and Improvement Project (YOPPsiteMIIP). Parallel investigations are broadening the scope and impact of the YOPP-SH winter TOPs. Studies of the Antarctic tourist industry’s use of weather services show the scope for much greater awareness of the availability of forecast products and the skill they exhibit. The Sea Ice Prediction Network South (SIPN South) analysis of predictions of the sea ice growth period reveals that the forecast skill is superior to the sea ice retreat phase.

Room-temperature electron-hole liquid has recently been experimentally identified in low-dimensional transition metal dichalcogenides. Here, the authors demonstrate that a first-principles Fermi liquid model effectively predicts the photoluminescence response of this phenomenon. Using density functional theory, in conjunction with previous Raman and photoluminescence spectroscopy results, they present a consistent quantitative picture of the electron-hole liquid phase transition in suspended, heat-strained 1$L$-MoS${}_{2}$ monolayers. They show a 23-fold increase in photoluminescence per unit of direct gap carrier density and 9:1 indirect-direct hole population ratio at high strain.

Recent advances in Rydberg-atom electrometry detail promising applications in radio frequency communications. Presently, most applications use carrier frequencies greater than 1 GHz where resonant Autler–Townes splitting provides the highest sensitivity. This letter documents a series of experiments with Rydberg atomic sensors to collect and process waveforms from the automated identification system (AIS) used in maritime navigation in the very high frequency (VHF) band. Detection in this band is difficult with conventional resonant Autler–Townes based Rydberg sensing and requires a new approach. We show the results of a method called high angular momentum matching excited Raman (HAMMER), which enhances low frequency detection and exhibits superior sensitivity compared to the traditional AC Stark effect. From measurements of electromagnetically induced transparency in rubidium and cesium vapor cells, we show the relationship between incident electric field strength and observed signal-to-noise ratio and find that the sensitivity of the HAMMER scheme in rubidium achieved an equivalent single VHF tone sensitivity of 100μV/m/Hz. With these results, we estimate the usable range of the atomic vapor cell antenna for AIS waveforms given current technology and detection techniques.

An epistemic logic program is a set of rules written in the language of Epistemic Specifications, an extension of the language of answer set programming that provides for more powerful introspective reasoning through the use of modal operators K and M. We propose adding a new construct to Epistemic Specifications called a world view constraint that provides a universal device for expressing global constraints in the various versions of the language. We further propose the use of subjective literals (literals preceded by K or M) in rule heads as syntactic sugar for world view constraints. Additionally, we provide an algorithm for finding the world views of such programs.

Recent research in extensions of Answer Set Programming has included a renewed interest in the language of Epistemic Specifications, which adds modal operators K ("known") and M ("may be true") to provide for more powerful introspective reasoning and enhanced capability, particularly when reasoning with incomplete information. An epistemic logic program is a set of rules in this language. Infused with the research has been the desire for an efficient solver to enable the practical use of such programs for problem solving. In this paper, we report on the current state of development of epistemic logic program solvers.

Experimental Shack–Hartmann wavefront sensor (SHWFS) measurements were collected for a laser beam that propagated through a weakly compressible shear layer. Complementary computational fluid dynamics (CFD) was also conducted to match the experiment. The path-integrated CFD results were then applied to a SHWFS model such that the experimental and CFD results could be compared. Using both the experimental and CFD wavefront results, it was found that, although the CFD results slightly overestimated the resultant wavefront error, the CFD and experimental results revealed extremely similar wavefront topology. In order to further examine the aberrations imposed onto the laser beam in both datasets, the SHWFS image-plane irradiance patterns and circulation of phase gradients were studied. Similar to the overall wavefront topology, these data reduction approaches revealed similar phenomena in both the experimental and CFD-modeled results. Specifically, appreciable circulation and beam spread of the SHWFS image-plane irradiance patterns were exhibited throughout the shear layer’s braid region. Both of these findings suggest that sharp phase gradients exist in the weakly compressible shear layer and both (1) the SHWFS resolution and (2) the continuous nature of the phase estimate obtained using SHWFS data in a least-squares reconstruction algorithm make these phase gradients challenging to resolve. The findings presented here inform efforts looking to experimentally or computationally study aero-optical environments.

This paper presents a methodology for developing OPNET simulation models representing a wide range of SATCOM deployment scenarios. The model development process includes: developing a set of OPNET process models representing SATCOM network elements, mapping SATCOM link performance analysis results to the simulation model, and automatically generating an OPNET network model representing a SATCOM deployment scenario. The process also includes integrating the SATCOM model with other OPNET network scenarios, which are separately created using the OPNET Modeler. The methodology has been applied to developing the SATCOM Network Planning Toolset (SNPT). Illustrating the capabilities of SNPT, this paper presents the feasibility and effectiveness of the technologies based on the methodologies developed. It shows that an accurate RF layer analysis can be brought to building a simulation model. In comparison with a typical OPNET modeling building process, the amount of effort needed to generate a complex scenario model has been illustrated to show the applicability to SATCOM network planning and evaluation.

The purpose of this paper is to introduce service system governance by exploring systems theory-based service systems. With the growing emphasis on services, and as globalisation has connected the world economically, technically, and socially, increasing emphasis has been placed on delivering customer solutions through the combined products and services offered by globally integrated enterprises. Service-dominant logic (S-D logic) and service science (SS) separately define service, but according to both, the concept of service system is central. First, the paper reviews recent developments in service theory. S-D logic and SS are explored with particular emphasis on the common feature of their concept of service system and how it can be described as a complex system. This is followed by an exploration of systems theory to understand service systems from this perspective. Through this exploration, governance of a service system is introduced. The paper concludes with implications of using systems theory as a theoretical lens to view service system governance.

Tactical networks are highly dynamic environments characterized by constrained resources, limited bandwidth, and intermittent connectivity. The limits on communication cause significant delays in the delivery of information to edge users. This paper focuses on an approach to improve the timeliness of access to information via prediction and pre-staging. The approach also incorporates a learning mechanism to dynamically adapt the information prediction algorithm. This capability has been integrated into the DisService peer-to-peer information dissemination system, which opportunistically exploits any available connectivity to address the challenging environment. The extended system, called DisServicePro (for Proactive) predicts the information needs of edge users using their mission description, including the routes that users may take as part of the mission. DisServicePro extends the capabilities of DisService by efficiently and proactively disseminating information to the edge nodes by means of replication and forwarding policies. The proactive behavior is the result of the integration of policies and a distributed learning algorithm that takes into account the history of previously requested information, along with the characteristics of the target nodes and the mission. As new information becomes available, DisServicePro matches it against the mission profile and pushes relevant information to the edge nodes. Information that is selected to be pushed is sorted based on the predicted time to use as well as the confidence value of the prediction.

Department of Defense (DoD) satellite systems and the networks they provide access to, have evolved over the years to support the “net-centric” vision of a joint and interoperable end-to-end communications solution for the deployed tactical satellite communications (SATCOM) user. Although great strides have been made in reaching the net-centric goal, full DoD SATCOM Internet Protocol (IP) convergence between the user community, the DoD SATCOM Gateways and the Defense Information Service Network [DISN] has been challenging from both a technical and Information Assurance (IA) standpoint. An additionally significant contributing factor is the exponential increase in user SATCOM capacity requirements resulting in the need for expanded Gateway capabilities. Until a full IP convergence approach is implemented throughout the DoD SATCOM Gateway enterprise, more and more legacy Time Division Multiplexed (TDM) equipment will be required at these Gateways to satisfy emerging/future user SATCOM requirements. Physical limitations exist at all the DoD Gateway sites. This paper is a result of an analysis that was sponsored by the Office of the Assistant Secretary of Defense (OASD)/Network and Information Integration (NII) with a goal to analyze technical options that would decrease the ever growing equipment footprint at the DoD Enterprise Satellite Gateway sites by migrating traditional circuit switched equipment to an all IP, joint and interoperable system while also promoting full IP convergence and interoperability between the tactical SATCOM users and the DISN.

With the recent explosion in availability and use of internet social media, citizens now utilize these resources to transmit information quickly about events as they unfold. However, for responding personnel in emergency situations, it is often difficult to sift through the enormous quantity of data within such sources to find the most pertinent information. The ability to filter messages is critical to, for example, identify firsthand accounts from persons within the direct vicinity of events. Nevertheless, on social media platforms such as Twitter, location-based information is often missing or unreliable. This paper outlines an approach to probabilistically identify the likely locations of individuals on Twitter based on their content, and from socially connected users with more reliable geographic information. We utilize measurements of user content similarity and Gaussian mixture modeling to infer “hotspots” of the likely location of users in emergencies. We are able to achieve upwards of 70% accuracy of Twitter user home cities without using any prior knowledge of geographic boundaries to look within.

The geometric embedding of an ideal in the algebraic integer ring of some number field is called an ideal lattice. Ideal lattices and the shortest vector problem (SVP) are at the core of many recent developments in lattice-based cryptography. We utilize the matrix of the linear transformation that relates two commonly used geometric embeddings to provide novel results concerning the equivalence of the SVP in these ideal lattices arising from rings of cyclotomic integers.

An Android application (app), called Real Time Range Tracker, was developed as part of a Naval Innovation Science and Engineering program and provides near real-time “line of sight” range between mobile smart devices. In order to properly design tests and analyze test results, the accuracy of the data generated by the app must be fully understood along with any associated measurement uncertainties. This paper discusses the methods used to assess the app's performance and resulting analysis of the range accuracy. The app's stationary range accuracy was found to be 4.2 meters (13.8 feet) and the mobile-to-mobile range accuracy was found to be 95.7 meters (314 feet) for speeds up to 70 mph and ranges up to 20 miles apart. Additionally, sources of accuracy error are discussed and quantified. Based upon this information, a worst-case accuracy prediction equation is provided for cases where test conditions are known. This equation was found to adequately predict an accuracy that was worst-case when compared to actual data sets obtained during testing.

Wireless sensor networks (WSNs) are resource-constrained self-organizing networks that are often deployed in hostile and inaccessible environments in order to collect data. Benign system faults such as malfunctioning hardware, software glitches, and environmental hazards may impact overall system reliability but can often be mitigated by appropriate fault tolerance mechanisms. However, in an adversarial context, more subtle and difficult challenges to reliability can be faced and must be considered. This paper focuses the well-studied man-in-the-middle (MITM) attack problem where an attacker tampers with the characteristics of the network by mediating a link between legitimate nodes that does not have the properties required for correct network operation. This paper develops attack scenarios for unique network topologies, presents a timing and location-based analysis of MITM attack scenarios for each, and characterizes the limits of MITM detectability via timing analysis as a function of distance.

An analysis of face images was done to determine if a correlation can be made between matching performance and characteristics of face images at the visible and near infrared (NIR) spectrums. The Contrast Limited Adaptive Histogram Equalization (CLAHE) technique was used to preprocess images prior to using a commercial matcher.

Although the entropy of a given signal-type waveform is technically zero, it is nonetheless desirable to use entropic measures to quantify the associated information. Several such prescriptions have been advanced in the literature but none are generally successful. Here, we report that the Fourier-conjugated 'total entropy' associated with quantum-mechanical probabilistic amplitude functions (PAFs) is a meaningful measure of information in non-probabilistic real waveforms, with either the waveform itself or its (normalized) analytic representation acting in the role of the PAF. Detailed numerical calculations are presented for both adaptations, showing the expected informatic behaviours in a variety of rudimentary scenarios. Particularly noteworthy are the sensitivity to the degree of randomness in a sequence of pulses and potential for detection of weak signals.

The DoD M&S Steering Committee has noted that the current DoD and Service's modeling and simulation resource repository (MSRR) services are not up-to-date limiting their value to the using communities. However, M&S leaders and managers also determined that the Department needs a functional M&S registry card catalog to facilitate M&S tool and data visibility to support M&S activities across the DoD. The M&S Catalog will discover and access M&S metadata maintained at nodes distributed across DoD networks in a centrally managed, decentralized process that employs metadata collection and management. The intent is to link information stores, precluding redundant location updating. The M&S Catalog uses a standard metadata schemas based on the DoD's Net-Centric Data Strategy Community of Interest metadata specification. The Air Force, Navy and OSD (CAPE) have provided initial information to participating DoD nodes, but plans on the horizon are being made to bring in hundreds of source providers.

The Finding Responsive Intelligence in Multimodal Analysis (FRIDAY) project seeks to accelerate the development of artificial general intelligence (AGI) by integrating multiple, complex holonic algorithms into high‑fidelity flight simulators for next‑generation drone training and performance enhancement. Building on a one‑year deep‑analysis effort, FRIDAY proposes a hierarchical control architecture—Human → LLM Manager → LLM Executors—through which mission directives are translated into actionable drone behaviors. Central to the effort is an agentic LLM system that orchestrates swarms of specialized LLM‑agents, each tasked with mastering distinct operational capabilities. By grounding these agents in a modular skill set, the system can rapidly configure and deploy drone units tailored to diverse mission profiles. If realized, FRIDAY could transform military drone operations: autonomous platforms would dynamically adapt to battlefield conditions, conduct sophisticated reconnaissance, and execute precision tasks with minimal human oversight. The modular skill framework enables swift fielding of specialized drone formations for applications ranging from search‑and‑rescue and persistent surveillance to target acquisition and kinetic engagement. This work outlines the conceptual design, simulation‑based validation strategy, and anticipated operational benefits, offering a roadmap for leveraging AGI‑driven autonomy especially in an offline manner.