Abstract: The present invention provides a portable refueler for storing a quantity of gaseous fuel, optionally hydrogen, for refueling an end-user vehicle, comprising: a plurality of storage tanks, each storage tank comprising at least one cylinder which is horizontally arranged within an enclosure, wherein the enclosure is configured to be carried by a vehicle, and, a refueling nozzle for discharging a quantity of the gaseous fuel to the end-user vehicle during refueling.

Abstract: In accordance with some embodiments, systems, methods, and media for monitoring a production process of a product are provided. In some embodiments, a system comprises a remote server, a communications connection between the remote server and a facility database, at least one processor coupled to the communication system, and a memory device having stored thereon a set of computer readable instructions. The set of computer readable instructions cause the at least one processor to: receive a first set of data related to the production process, calculate a first monitoring index indicator for the production process based on the first set of data, receive a second set of data related to the production process after one or more performance variables of the production process are modified, calculate a second monitoring index indicator for the production process based on the second set of data, and output a result.

Abstract: In accordance with some embodiments, systems, methods, and media for predicting the conversion time of Mild Cognitive Impairment (MCI) to Alzheimer’s Disease (AD) in a patient are provided. In some embodiments, a system include a memory and a processor coupled to the memory. The processor is configured to: receive a plurality of risk factor indications and a plurality of interaction indications of a patient. Each interaction indication is an indication of interaction between two risk factor indications of the plurality of risk factor indications. The processor is further configured to obtain a trained machine learning model; apply the plurality of risk factor indications and the plurality of interaction indications to the trained machine learning model; and output a result based on the trained machine learning model.

Abstract: Method and apparatus for providing personalized self-help experience in online application. A predictive model is trained to learn a relationship between one or more user features and one or more tags using historical user feature data. High-dimensional vectors representing each of a plurality of questions are generated and stored in the lookup table. The trained predictive model outputs tags probabilities from the incoming user data, using the learned relationship. A user high-dimensional vector is formed based on the tags probabilities. Similarity metrics are calculated between the high-dimensional vector for the respective question and the user high dimensional vector. One or more of the most relevant question titles are returned to a client device for presentation to a user.

Abstract: A data-driven model to predict the returns of the production of corn in the U.S. is described. In one example, the model can account for 25 elements or factors presumed by the U.S. department of agriculture (USDA) to be contributing to the returns from corn production in the US. The model is designed on the basis of a number of parameters, including the selection of a significant set of the 25 factors, the extent or percentage of contribution of each factor, the extent of contribution to unknown factors, the identification of which of the significant factors are interacting, and others. In one example, 7 out of the 25 factors were found to be statistically significant, and 6 interaction terms were identified. The proposed model accurately predicts the returns from corn production in the U.S. with 98.22% accuracy.

Abstract: Aspects of software vulnerability prediction are described. In some examples vulnerability data is obtained from a vulnerability database for the software. The total cumulative vulnerability of the software is estimated using the vulnerability data. The total cumulative vulnerability is based at least in part on a time based nonlinear differential equation model. The time based nonlinear differential equation model generates a complete vulnerability life cycle. A graph is generated to display a cyclic increasing behavior of the complete vulnerability life cycle of the software.

Abstract: Procedures to identify the probabilities for different states in a vulnerability life cycle are described. The probabilities are used to develop a number of statistical models to evaluate the risk factor of a particular vulnerability at time “t”. A transition probability matrix of all states of a particular vulnerability as a function of time is also described. A Markov chain process can be iterated to reach a steady state of the transition probability matrix, with the initial probabilities reaching the absorbing states, including exploited and patched states. A risk factor is also introduced for use as an index of the risk of a vulnerability being exploited. Finally, statistical models that can calculate the risk factor more conveniently without going through the Markovian process are described.

Abstract: A statistical model for predicting an expected path length (“EPL”) of the steps of an attacker is described. The model is based on utilizing vulnerability information along with an attack graph. Using the model, it is possible to identify the interaction among vulnerabilities and individual variables or risk factors that drive the EPL. Gaining a better understanding of the relationship between the vulnerabilities and their interactions can provide security administrators with a better view and understanding of their security status. In addition, a number of different attributable variables and their contribution in estimating the EPL can be ranked. Thus, it is possible to utilize the ranking process to take precautions and actions to minimize the EPL.

Abstract: According to the embodiments, a statistical model is developed to estimate the probability of being in a certain stage of a particular vulnerability in its life cycle. The methodology with the application of Markov chain theory gives the basis for calculating estimates for probabilities for different stages of a life cycle of the vulnerability considered. Using the developed method, it is possible to evaluate the risk level of a particular vulnerability at a certain time. These developments allow an advantage in taking measures to avoid exploitations and introduce patches for the vulnerability before an attacker takes the advantage of that particular vulnerability.

Abstract: Aspects of software vulnerability prediction are described. In some examples vulnerability data is obtained from a vulnerability database for the software. The total cumulative vulnerability of the software is estimated using the vulnerability data. The total cumulative vulnerability is based at least in part on a time based nonlinear differential equation model. The time based nonlinear differential equation model generates a complete vulnerability life cycle. A graph is generated to display a cyclic increasing behavior of the complete vulnerability life cycle of the software.

Abstract: A system and method for automatically trimming and reclassifying workout data is disclosed. The system receives data associated with a workout of a user from at least one sensor associated with the user, the workout being classified as a first type of workout. The system processes the data to identify at least one time interval during the workout that does not correspond to the first workout type. The system prompts the user to select whether to remove or reclassify a subset of the data that is associated with the identified time interval. If the user chooses to do so, the system removes or reclassifies the subset of the data that is associated with the identified time interval. The system generates and provides workout depictions using the data, at least one of which illustrates only the remaining data that was not removed or reclassified.

Abstract: Method and apparatus for providing personalized self-help experience in online application. A predictive model is trained to learn a relationship between one or more user features and one or more tags using historical user feature data. High-dimensional vectors representing each of a plurality of questions are generated and stored in the lookup table. The trained predictive model outputs tags probabilities from the incoming user data, using the learned relationship. A user high-dimensional vector is formed based on the tags probabilities. Similarity metrics are calculated between the high-dimensional vector for the respective question and the user high dimensional vector. One or more of the most relevant question titles are returned to a client device for presentation to a user.

Abstract: A powertrain includes a transmission case, a transfer case, a front axle housing, and a webbed brace. The transfer case and front axle housing are directly fastened to the transmission case. The webbed brace is directly fastened to the transmission case, the transfer case, and the front axle housing to form a powerplant system. The webbed brace is configured such that a bending frequency of the powerplant system falls within a predefined range.

Abstract: A constant-velocity joint includes an outer race, inner race, end cap, and seal. The outer race defines a cavity, an opening to the cavity, and a through hole configured to receive a fastener. The inner race is disposed within the cavity and is rotatably connected to the outer race via a plurality of ball bearings. The end cap is secured to the outer race and covers the opening. The seal is disposed between the outer race and the end cap. The seal defines a channel that is in fluid communication with the cavity and the through hole. The channel is configured to vent air between the cavity and through hole.

Abstract: A vehicle has a transfer case that is configured to receive power from a transmission, and transfer the power to one or both of a front axle and a rear axle. The transfer case has an output, such as an output rod, that delivers the power to a differential on one of the axles. A driveshaft has a single constant-velocity joint thereon. A first shaft of the driveshaft is directly connected to the output of the transfer case by a fixed connection, such as a spline connection, that inhibits axial slipping. The first shaft is connected on its other end to the constant-velocity joint. A second shaft of the driveshaft is connects to the constant-velocity joint to the differential. The driveshaft can also have a clamp at the splint to inhibit axial slipping at the spline connection.

Abstract: A driveshaft includes a shaft defining a passageway and a constant velocity joint defining an interior and having a cover defining a hole. A grommet is disposed in the hole and defines a fluid passage into the interior. The CV joint is coupled to the shaft such that the shaft is disposed against the grommet with the passageway and the fluid passage in fluid communication to vent air from the interior into the passageway.

Abstract: System and method for enabling data transformation topologies to be transported and/or distributed within a network of devices. In one embodiment, the system comprises: a network apparatus which runs a computer program configured to: (i) generate a plurality mathematical processes to be applied; and (ii) create an instruction set comprising an ordered list of ones of the processes, and information identifying one or more data types to be utilized with each of the processes. The system further comprises a plurality of user devices which run a second computer program configured to: (i) receive access to the processes and the instruction set; and (iv) perform the mathematical processes in the order provided by the instruction set to arrive at transformed data.

Abstract: A driveshaft assembly of a vehicle includes a yoke assembly having a shaft extending between a yoke and a flange. The yoke assembly further includes a bearing having an inner race integrally formed on an outer surface of the shaft, an outer race circumscribing the inner race, and a plurality of rotating elements rollably engaging between the inner and outer races. A tube is attached to the flange.

Abstract: A powertrain includes a transmission case, a transfer case, a front axle housing, and a webbed brace. The transfer case and front axle housing are directly fastened to the transmission case. The webbed brace is directly fastened to the transmission case, the transfer case, and the front axle housing to form a powerplant system. The webbed brace is configured such that a bending frequency of the powerplant system falls within a predefined range.