Computer-Implemented Security Evaluation Methods, Security Evaluation Systems, and Articles of Manufacture
Computer-implemented security evaluation methods, security evaluation systems, and articles of manufacture are described. According to one aspect, a computer-implemented security evaluation method includes accessing information regarding a physical architecture and a cyber architecture of a facility, building a model of the facility comprising a plurality of physical areas of the physical architecture, a plurality of cyber areas of the cyber architecture, and a plurality of pathways between the physical areas and the cyber areas, identifying a target within the facility, executing the model a plurality of times to simulate a plurality of attacks against the target by an adversary traversing at least one of the areas in the physical domain and at least one of the areas in the cyber domain, and using results of the executing, providing information regarding a security risk of the facility with respect to the target.
Heavy Fossil Hydrocarbon Conversion and Upgrading Using Radio-Frequency or Microwave Energy
Conversion of heavy fossil hydrocarbons (HFH) to a variety of value-added chemicals and/or fuels can be enhanced using microwave (MW) and/or radio-frequency (RF) energy. Variations of reactants, process parameters, and reactor design can significantly influence the relative distribution of chemicals and fuels generated as the product. In one example, a system for flash microwave conversion of HFH includes a source concentrating microwave or RF energy in a reaction zone having a pressure greater than 0.9 atm, a continuous feed having HFH and a process gas passing through the reaction zone, a HFH-to-liquids catalyst contacting the HFH in at least the reaction zone, and dielectric discharges within the reaction zone. The HFH and the catalyst have a residence time in the reaction zone of less than 30 seconds. In some instances, a plasma can form in or near the reaction zone.
The Modifiable Multitasking Environment (ModME) - Open Sources
SIGenBench is a generalization and benchmark framework for the notion of semantic importance. Semantic importance is proposed to model and formalize data importance from various data orderings. It is primarily used in a stream reasoning context, where hidden information can be extracted out of the data streams. There are two main features for SIGenBench: Generalization: it refers to make semantic importance reusable by others. SIGenBench generalizes semantic importance by connecting semantic importance with the state of the art stream reasoning techniques, such as window operational semantics, continuous query languages, etc. Benchmark: it refers to quantify any benefits brought by semantic importance. SIGenBench provides a benchmark system that records the key performance indicators including precision, response time, memory consumption, and throughput. It also provides a data generator that can simulate 9 different patterns for streaming data, which is flexible and sufficient to test semantic importance in various streaming scenarios.
Heavy Fossil Hydrocarbon Conversion and Upgrading Using Radio-Frequency or Microwave Energy
Conversion of heavy fossil hydrocarbons (HFH) to a variety of value-added chemicals and/or fuels can be enhanced using microwave (MW) and/or radio-frequency (RE) energy. Variations of reactants, process parameters, and reactor design can significantly influence the relative distribution of chemicals and fuels generated as the product. In one example, a system for flash microwave conversion of HFH includes a source concentrating microwave or RF energy in a reaction zone having a pressure greater than 0.9 atm, a continuous feed having HFH and a process gas passing through the reaction zone, a HFH-to-liquids catalyst contacting the HFH in at least the reaction zone, and dielectric discharges within the reaction zone. The HFH and the catalyst have a residence time in the reaction zone of less than 30 seconds. In some instances, a plasma can form in or near the reaction zone.
METALLIZATION PATTERN ON SOLID ELECTROLYTE OR POROUS SUPPORT OF SODIUM BATTERY PROCESS
A new battery configuration and process are detailed. The battery cell includes a solid electrolyte configured with an engineered metallization layer that distributes sodium across the surface of the electrolyte extending the active area of the cathode in contact with the anode during operation. The metallization layer enhances performance, efficiency, and capacity of sodium batteries at intermediate temperatures at or below about 200° C.
LITHIUM METAL POUCH CELLS AND METHODS OF MAKING THE SAME (iEdison No. 0685901-18-0015)
A prototypic Li metal pouch cell with 300 Wh/kg and above has been demonstrated and reported in this disclosure. Through the integration of cell design, fabrication and new electrolyte, a record stable cycling of more than 200 cycles are demonstrated with > 80% capacity retention. This is the first time demonstration of high-energy Li metal cells with long-term stable cycling.
BIOSEQUENCE-BASED APPROACH TO ANALYZING BINARIES
In a dynamic computing environment, it is a nontrivial task to verify code running in the environment because most approaches to software similarity require extensive and time-consuming analysis of a binary, or the approaches fail to recognize executables that are similar but nonidentical. A biosequence-based method for quantifying similarity of executable binaries is used to identify allowed codes in a real-world multi-user environment.
BIOSEQUENCE-BASED APPROACH TO ANALYZING BINARIES
In a dynamic computing environment, it is a nontrivial task to verify code running in the environment because most approaches to software similarity require extensive and time-consuming analysis of a binary, or the approaches fail to recognize executables that are similar but nonidentical. A biosequence-based method for quantifying similarity of executable binaries is used to identify allowed codes in a real-world multi-user environment.
CHISSL: Intuitive, Scalable, Interactive Machine Learning
We developed CHISSL, a human-machine interface that utilizes a combination of unsupervised and semi-supervised machine learning to enable a non-expert user to organize large amounts of data instances by her own mental model. The user interacts with individual examples by dragging and dropping to move items between groups, or double-clicking to create new groups. The algorithm rapidly re-evaluates the distance from all instances to those provided by the user. This is used to re-classify the un-labeled data and also to provide recommendations for what recommendations the user sees for each group she has created. Our main contribution is the technique that allows user feedback to be incorporated rapidly, incrementally, and predictably, in a manner that scales easily beyond hundreds of thousands of instances. Our algorithm is partitioned between a lightweight client and a heavyweight server. The server is responsible for initial batch processing and representation of the data. A tree representation of this data is sent to the client, without the need to send the full representation of all instances. This saves an extraordinary amount of memory and bandwidth. All computation that incorporates user feedback is performed in in a web browser without the need to return to the server. This decreases the latency of user interactions and decreases server load, theoretically allowing many analysts to use the system simultaneously.
Serum markers for type II diabetes mellitus
A method for identifying persons with increased risk of developing type 2 diabetes mellitus utilizing selected biomarkers described hereafter either alone or in combination. The present invention allows for broad based, reliable, screening of large population bases and provides other advantages, including the formulation of effective strategies for characterizing, archiving, and contrasting data from multiple sample types under varying conditions. diabetes has not been previously reported in the literature.