Knowledge Verification Method Based on Artificial Intelligence-based Knowledge Graph Construction

The knowledge graph connects real-world entities and concepts through their relationships, connects all different types of information to obtain a relationship network, and can analyze “relationship” issues. Creating a knowledge graph is a continuous process, and it needs to continuously learn new knowledge and update existing knowledge in the library as time and events change. However, since the accuracy of the updated new knowledge cannot be guaranteed, the new knowledge must be verified. This paper aims to study the knowledge verification method based on artificial intelligence-based knowledge graph construction. Based on the analysis of the knowledge graph construction process, the knowledge graph construction method and the knowledge verification method, knowledge verification is realized by constructing a probabilistic soft logic model. The experimental results show that the recall rate, F1 value, and AUC value of the candidate knowledge set are verified by the knowledge verification model proposed in this paper. Therefore, it can be inferred that the knowledge verification model proposed in this paper is effective.

Research on Aiming and Tracking Ability Evaluation Model of Laser-guided Missile

Laser guidance is a continuous process, during which a lot of operational data and corresponding changes are generated. Aiming at the live-fire drill shooting training and assessment evaluation of a certain type of laser-guided missile, this paper analyzes the principle of laser guidance, studies the weighting system of the information field based on the importance of characteristic intervals, integrates and processes the data and outputs the aiming effect picture and sheet, and constructs the aiming and tracking ability evaluation model. Stationary targets and moving targets are tested respectively, and the verification model can realize the calculation of laser information field, the integration of coordinate data, the output of aiming effect diagram, and the evaluation of the shooter’s aiming and tracking ability expressed in a percentage system. The model realizes data collection, integration and processing based on MATLAB software, and builds graph and table output ports, which can realize low delay processing of a large amount of short-term data.

Intracycle power and ventilation mode as potential contributors to ventilator-induced lung injury

Background High rates of inflation energy delivery coupled with transpulmonary tidal pressures of sufficient magnitude may augment the risk of damage to vulnerable, stress-focused units within a mechanically heterogeneous lung. Apart from flow amplitude, the clinician-selected flow waveform, a relatively neglected dimension of inflation power, may distribute inflation energy of each inflation cycle non-uniformly among alveoli with different mechanical properties over the domains of time and space. In this initial step in modeling intracycle power distribution, our primary objective was to develop a mathematical model of global intracycle inflation power that uses clinician-measurable inputs to allow comparisons of instantaneous ICP profiles among the flow modes commonly encountered in clinical practice: constant, linearly decelerating, exponentially decelerating (pressure control), and spontaneous (sinusoidal). Methods We first tested the predictions of our mathematical model of passive inflation with the actual physical performance of a mechanical ventilator–lung system that simulated ventilation to three types of patients: normal, severe ARDS, and severe airflow obstruction. After verification, model predictions were then generated for 5000 ‘virtual ARDS patients’. Holding constant the tidal volume and inflation time between modes, the validated model then varied the flow profile and quantitated the resulting intensity and timing of potentially damaging ‘elastic’ energy and intracycle power (pressure–flow product) developed in response to random combinations of machine settings and severity levels for ARDS. Results Our modeling indicates that while the varied flow patterns ultimately deliver similar total amounts of alveolar energy during each breath, they differ profoundly regarding the potentially damaging pattern with which that energy distributes over time during inflation. Pressure control imposed relatively high maximal intracycle power. Conclusions Flow amplitude and waveform may be relatively neglected and modifiable determinants of VILI risk when ventilating ARDS.

Cognitive Based Authentication Protocol for Distributed Data and Web Technologies

The objective of the verification process, besides guaranteeing security, is also to be effective and robust. This means that the login should take as little time as possible, and each time allow for a successful authentication of the authorised account. In recent years, however, online users have been experiencing more and more issues with recalling their own passwords on the spot. According to research done in 2017 by LastPass on its employees, the number of personal accounts assigned to one business user currently exceeds 191 profiles and keeps growing. Remembering these many passwords, especially to applications which are not used every week, seems to be impossible without storing them either on paper, in a password manager, or saved in a file somewhere on a PC. In this article a new verification model using a Google Street View image as well as the user’s personal experience and knowledge will be presented. The purpose of this scheme is to assure secure verification by creating longer passwords as well as delivering a ‘password reminder’ already embedded into the login scheme.

Verification of composed web service using Synthesized Nondeterministic Turing Model (SNTMM) with Multiple Tapes and Stacks

To verify the composed Web services, a general view of what traits of a service need to be identified is still lacking. The existing verification model did not address any mechanism for getting alternative services if we failed to reach the desired service and partially concentrated on the reachability problem for a deterministic and non-deterministic system in sequential. This paper proposes a Synthesised Non-deterministic Turing Machine Model (SNTMM) by combining the Multistacked Non-deterministic Turing Machine (MSNTM) model and Multitaped Non-deterministic Turing Machine (MTNTM) model to verify the composed Web services for both deterministic and non-deterministic systems in parallel. The deceased transition and departed service marking algorithm have been proposed to address each participated service’s reachability in composing service for all possible input in parallel. This article shows an example to demonstrate the meticulousness of the model. The experimental results show that the performance of the proposed model is measured efficiently