442 results about "Software modules" patented technology

The invention relates to a reservoir dam operation safety sky-land project intelligent sensing system and an operation method, and relates to the technical field of hydraulic engineering safety monitoring. The system is composed of a sky-land water conservancy project integrated monitoring and sensing system, a self-adaptive sampling module, a layered distributed architecture and a software and hardware integrated module, and multi-source data such as deformation, seepage, stress strain, vibration and environmental quantity are cooperatively collected through five dimensions of sky domain, airspace, territory, water domain and work domain. The monitoring frequency is dynamically adjusted by using an adaptive sampling strategy, and data cleaning, standardization, space-time registration and fusion processing are completed through a distributed architecture to generate a high-quality comprehensive data set. The system can realize total-factor and whole-process refined monitoring, effectively eliminates data islands, improves data quality and monitoring efficiency, has high reliability, real-time performance and expandability, and provides powerful data support and decision basis for dam safety assessment and intelligent early warning.

Aspects described herein may automatically generate threat models using large language model (LLM). A computing device may send, to LLM, one or more software modules associated with a computing system. The computing device may request the LLM to generate a threat model of the computing system. The computing device may receive, from the LLM, a first output based on the first prompt comprising first information for a first version of the threat model and a penetration test script for the computing system. The computing device may input, to the LLM, the result of the penetration test together with the LLM's previous output, to facilitate the LLM to generate a refined version of the threat model.

The invention relates to the technical field of engineering cost, and discloses a data entry method for engineering cost software, which comprises the following steps of: S1, importing an engineering quantity list file in an Excel format through an interface of the engineering cost software, and automatically analyzing a data structure of the engineering quantity list file; s2, based on a preset intelligent matching algorithm, performing dynamic mapping on the Excel data field and a data field of a project cost software function module; s3, adopting a data type self-adaptive rule to automatically classify and convert numerical values, texts and compound data in the Excel; s4, based on a data association generation algorithm, automatically establishing a hierarchical relationship and a dependency relationship between the engineering quantity list items; s5, executing one-button data import, and writing the processed structured data into a project cost software database in batches; according to the method, high-precision automatic mapping of the Excel field and the software module is realized through an intelligent matching algorithm and a dynamic weight adjustment mechanism based on the feature vector similarity, the matching accuracy is greatly improved, and the manual correction frequency is greatly reduced.

The invention discloses a wearable plantar pressure and three-dimensional gait analysis system, and relates to the technical field of gait analysis, the system comprises a wearable in-shoe plantar pressure analysis subsystem and a three-dimensional gait analysis subsystem; the wearable in-shoe plantar pressure analysis subsystem comprises a pressure sensor module, a pressure integration module, an intelligent transmission module, a detection software module, a power supply module, an instantaneous pressure and balance detection module, a standing balance detection module, a balance and gait detection module and a cloud server; the three-dimensional gait analysis subsystem comprises a hardware unit and a software unit; according to the invention, a wearable plantar pressure and three-dimensional gait analysis collaborative system is constructed, bidirectional verification compensation is realized by means of data fusion of two subsystems, and traditional single-dimensional limitation is broken; pressure sensing and a double-view reconstruction technology are fused, data are dynamically captured, and bidirectional error correction is carried out; the limitation of traditional equipment is solved, the evaluation accuracy and robustness are improved, and a quantitative basis is provided for clinical diagnosis, rehabilitation and the like.

A monitoring and / or food / water / medicine control system and method of use of the systems provide that (i) an experimenter at the computer desktop sets the schedule for feeding / fasting (food or water or medicine) the animal according to their need, and the animal's access to food or water or medicine will be set accordingly. This allows animal scientists, experimentalists, and experimenters to fully control animal feeding scenarios; (ii) the experimenter remotely opens and closes the animal's access to food / water / medicine regardless of the pre-set schedule; (iii) the experimenter checks the animal's status via real-time monitoring; (iv) an artificial intelligence system identifies and tracks the animal's location and its activities; and (v) a software module connects the vision unit and feeding mechanism to the experimenter's desktop to provide full control of both the vision unit and the feeding mechanism, to calculate different parameters of the animal's activities, and to report the animal's feeding / fasting history, activity history, and upcoming scheduled feedings.

The invention discloses a real-time adjustment camera focusing method and system, and aims to solve the problem of poor anti-interference capability of an existing focusing mode. The method comprises the following steps: off-line construction of an optimization lookup table and on-line real-time focusing: in an off-line stage, constructing a fixed-focus platform, generating an original lookup table through light spot anti-interference preprocessing and centroid calculation, and then constructing an efficient retrieval data structure to obtain the optimization lookup table; in the online stage, images are collected in real time, the center of mass is obtained through anti-interference processing, compensation is conducted through a preset prediction algorithm during shielding, target reference points are matched through an efficient retrieval data structure, and focusing is triggered according to deviation of the center of mass. The system comprises a hardware module and a software module which cooperatively realize the method. The method improves the anti-interference capability of light spot processing and the matching efficiency of the lookup table, adapts to the interference of illumination fluctuation, shielding and the like of an industrial environment, meets the real-time focusing requirements of high-speed production, is compatible with existing hardware, and is convenient to deploy.

The invention discloses a software architecture recovery method and system based on structural dependence and semantic similarity, and the method comprises the steps: carrying out the coding and embedding of source code files of software through a code pre-training model, extracting the semantic information of the source code files, and calculating the semantic similarity between the source code files; using a code statistical analysis tool to extract a structure dependency relationship between the source code files; in combination with the semantic similarity and the structure dependency relationship, calculating a connection weight between the source code files, and constructing a weighted graph; and dividing the weighted graph into communities representing the software modules by adopting a community detection algorithm, and recovering the software architecture. According to the method provided by the invention, the weighted graph is constructed by combining semantic similarity and structural dependency, and software modular segmentation is carried out by adopting a community detection algorithm, so that the efficiency, accuracy and expandability of software architecture recovery are improved.

A construction process support system that enables diverse users to quickly and intuitively create construction model data according to their intentions using natural language input and grid-based positioning. The system comprises hardware processors, software modules, and databases configured to display user interface pages to terminals and control natural language input messages. When input messages contain grid labels that specify coordinates on pages with character codes regarding construction structures, the system requests a Large Language Model (LLM) to generate instruction codes describing construction model data including the grid labels as position information. The LLM generates the requested instruction codes. The system stores the construction model data as searchable data in the database, forwards input messages to chat areas, and renders each structure as three-dimensional data at grid label positions on page canvases.

The invention discloses an integrated design management system with an automatic registration communication agent engine and a method thereof, and relates to the technical field of software integrated design simulation. The method has a heterogeneous integration breakthrough, the five communication modes are matched with the software without the API / command line / file, different heterogeneous software can support one communication mode, and the integration cost is remarkably reduced; dynamic expansibility is achieved, a newly added software module only needs to deploy a proxy engine and configure registration, and zero-shutdown upgrading of the platform is achieved; high concurrency reliability is achieved, resource conflicts are solved for an instance mechanism, and parallel task efficiency is improved; and full-process automation is achieved, and the cross-software design process execution time is obviously shortened.

The method includes: A breath wake-up processing apparatus sends voice data in first data when detecting that the obtained first data is used for indicating to wake up a first application through breath. A breath wake-up software module stores the voice data, starts the first application, and controls the breath wake-up processing apparatus to stop detecting breath wake-up of the first application. The first application sends a first notification when successfully calling the breath wake-up software module. The breath wake-up software module sends the voice data to the first application. The first application performs voice recognition on the voice data. The first application sends a second notification when determining, based on the voice data, that the voice recognition ends. The breath wake-up software module controls, in response to the second notification, the breath wake-up processing apparatus to start detecting next breath wake-up.

The invention provides a 2D laser radar layered shielding and stepless speed regulation collaborative obstacle avoidance system, which comprises a 2D laser radar device, an industrial personal computer, a single chip microcomputer, a motor control unit, a 2Dslab positioning module and a layered collaborative obstacle avoidance module, according to the module, efficient obstacle avoidance is realized through a four-layer collaborative architecture; comprising a user interaction layer for providing a graphical configuration interface, a map fusion shielding layer for realizing static barrier shielding based on a positioning map, and a dynamic deceleration area sensing layer for dynamically adjusting the sensing range according to the real-time speed and acceleration of a mobile robot, and the stepless speed regulation control layer is used for constructing a speed continuous mapping model to realize smooth transition of the near-obstacle process. According to the invention, through the synergistic effect among the stepless speed regulation control layer, the dynamic deceleration area sensing layer, the map fusion shielding layer and the user interaction layer, the smoothness, the adaptability and the intelligence of the obstacle avoidance decision are realized.

A Decision Support System for prescription verification may include software and / or hardware configured to supplement analysis and decision-making in the workflow of a pharmacist and / or take action regarding certain steps in the prescription fulfillment process. The Decision Support System may include a plurality of software modules each configured to provide information to a user for a particular review, evaluation, or check regarding the Prescription Verification process. One or more the software modules of the Decision Support System may use or be implemented as an artificial intelligence (AI) module or algorithm, e.g., one or more decision trees, predictive models, large language models (LLMs), RAG enhanced LLMs, or rules-based engines. Decision Support System is configured to check information regarding the patient receiving the medication, the provider prescribing the medication, and the medication itself to ensure data accuracy and to determine whether it is safe to dispense the medication to the patient.

Kernel-mode security software detects a trigger event indicative of a specific stage in the lifecycle of a target software entity executing in user mode. In response, the security software identifies a target object residing in memory (e.g., loaded library, chunk of code, etc.) according to a current content of the user-mode call stack, and determines whether the target object is malicious. Various methods described herein detect malicious modifications of a loaded module, such as overload, stomping, and unhooking, among others. Other methods described herein detect dynamically swapped libraries and malicious shellcode, among others.

The invention discloses a self-checking router network communication system, which belongs to the technical field of router network communication, and comprises a hardware module and a software module, the hardware module comprises a central processing unit used for executing system instructions and processing data, a storage unit used for storing temporary data, basic starting programs and key configuration files, and a network interface used for being connected with an external network. The software module comprises a self-checking program used for carrying out comprehensive self-checking on system hardware and software, a communication protocol stack used for realizing encapsulation, de-encapsulation and transmission of network data, and a network management module used for configuring, monitoring and managing the system; the self-checking items of the self-checking program comprise network card detection, power supply detection, connectivity detection of network connection and accuracy detection of a routing table; the system can discover and process network communication faults in time and guarantee stable operation of the network.

A method is provided for configuring an SIL simulation of a control unit running on a computer, software modules for the control unit, which have a plurality of tasks, being installed on the computer for the SIL simulation of the control unit, the tasks being processed in a predetermined clock cycle having a periodic period between the individual clock time points, and the computer including a plurality of processor cores, on which a plurality of virtual machines run, which each process predetermined tasks. A possibility is thus provided for minimizing the computing time of an SIL test.

The invention discloses a software defect prediction method based on cGAN and DGRRC, and the method comprises the steps: extracting static code features and defect labels of a software module, and carrying out the preprocessing, and obtaining an original sample set; inputting defect tags in the original sample set into a conditional generative adversarial network (cGAN) for defect sample synthesis and data expansion to obtain a class balanced expansion set; a dynamic greedy correlation-redundancy feature selection DGRRC method is adopted to screen features in the class-balanced expansion set according to correlation and redundancy, and a data set containing core features is obtained; and inputting the data set containing the core features into a Meta-Ensemble model based on an attention mechanism to carry out fusion and software defect prediction. The method combines the advantages of generative data enhancement, feature selection and ensemble learning, and aims to improve the accuracy and robustness of defect prediction from multiple aspects.

A data processing system (DPS) uses platform protection technology (PPT) to protect some or all of the code and data belonging to certain software modules. The PPT may include a virtual machine monitor (VMM) to enable an untrusted application and a trusted application to run on top of a single operating system (OS), while preventing the untrusted application from accessing memory used by the trusted application. The VMM may use a first extended page table (EPT) to translate a guest physical address (GPA) into a first host physical address (HPA) for the untrusted application. The VMM may use a second EPT to translate the GPA into a second HPA for the trusted application. The first and second EPTs may map the same GPA to different HPAs. Other embodiments are described and claimed.

The invention provides a software defect prediction method based on a dynamic path adaptive graph convolution network, and the method comprises the steps: constructing graph structure data of a software module, inputting the graph structure data into the graph convolution network to learn a dependency relationship between modules, carrying out the adaptive weight distribution of a multi-hop path through a dynamic path weighting convolution layer, and carrying out the prediction of a software defect. The long-path noise interference is suppressed based on the path length attenuation coefficient; optimizing an adjacent matrix in real time based on a multi-head attention mechanism, enhancing a key dependency edge and pruning redundant connection; and embedding a dynamic path score and an adaptive graph updating algorithm into a classification objective function, updating a training weight in combination with a balance strategy, and outputting a defect prediction result through the optimized model. According to the method, the problems of insufficient dependent modeling, noise accumulation and performance degradation in a class imbalance scene of a traditional graph convolutional network under a static graph hypothesis can be effectively solved.

A system for providing a safety critical operating environment container architecture, the system including a computing device having a memory communicatively connected to at least one multi-core processor, the memory containing instructions configuring the processer to receive at least a software module to be executed on the at least one multi-core processor, create a separate virtual environment for the at least a software module, wherein creating the virtual environment further includes generating a virtualization layer and allocating a dedicated private static memory space through the virtualization layer, wherein the separate virtual environment includes a dedicated operating system, integrate the at least a software module into the virtual environment by instantiating, the software module into at least one software container, wherein the at least one software container includes a plurality of dedicated software packages and execute the software module on each software container for each virtual environment.

The invention provides a multi-modal fusion anti-campus-spoofing monitoring method based on privacy protection, and the method consists of software and hardware modules, such as a quantum dot sensor, a millimeter-wave radar, a data processing terminal, an early warning terminal, a data synchronization module, a feature extraction algorithm, a multi-modal fusion model and the like. The method comprises the steps of multi-source data acquisition, time-space synchronization, feature extraction, multi-modal fusion, behavior classification and graded early warning, and high-precision and full-scene monitoring of campus spoofing behaviors is realized. Through a heterogeneous sensing network of a quantum dot sensor and a millimeter wave radar, hardware-level time synchronization is realized by adopting a PTP protocol, space-time alignment is performed on a micro-motion waveform entropy and a radar point cloud feature based on a feature fusion algorithm of an attention mechanism, and three-level classification of a deception behavior is realized in combination with a hybrid network. And finally, a hierarchical response mechanism is triggered through an edge computing node, so that the problem of monitoring blind areas of a traditional campus monitoring system in a private place is solved, and meanwhile, the recognition accuracy rate of 95% or above is achieved.

A computer-implemented XR platform is configured for teaching, training, instructing, diagnostic, therapeutic and / or care delivery. The XR platform includes a plurality of software modules. A combined extended reality display and computing device is adapted for implementing one or more of the plurality of modules. A classifier system automatically identifies, classifies, and documents data comprising criteria adapted to fulfill a requirement for at least one code relating to health or wellness.

Disclosed herein are systems, apparatuses, and methods for configuring and using one or more modular software libraries for use with large language models (LLMs) for automatically generating code from one or more user task queries. The systems, apparatuses, and methods compare a user's task query to generate code for a task with only headers of docstring. After identifying potentially relevant code from the most closely matching headers, the systems, apparatuses, and methods combine the user's task query with the identified docstring bodies as a prompt to one or more LLMs to converge upon software modules, functions, classes, and / or submodules (e.g., software code components) that contain relevant code. The systems, apparatuses, and methods then generate code responsive to the user's task query from the selected modules, functions, classes, and submodules.

The invention relates to the field of chip clamps, in particular to a hearing aid output limit adjusting method, which comprises an adjusting system, and the adjusting system comprises a hardware module and a software module. The hardware module comprises a DSP module, a collection module, a power amplifier module and a power supply module. The software module comprises a signal processing module, a user interface module and a system management module; the DSP module is used for realizing a complex signal processing algorithm and analyzing sound signals in real time through cooperation of an efficient digital signal processor and an artificial intelligence algorithm, and the method is used through modular connection, collects and analyzes user hearing signals in real time, dynamically adjusts output limitation in combination with hearing conditions and environmental factors of a user, and improves the user experience. In this way, comfort of the user in various hearing scenes can be guaranteed, hearing of the user can be effectively protected, perfect balance between the amplification effect and the comfort of the user is achieved, habits of the user are conveniently recorded in cooperation with the DSP module and the system management module, and user experience is improved.

The invention relates to the field of system engineering modeling, and particularly discloses a SysML-based modeling method, system and product, and in the modeling method, a functional architecture design step comprises the following steps: creating a functional architecture document, sequentially creating each functional module, and defining a subordination relationship of the functional modules; defining the input and output function data of the function module, and defining the function data and the direction at the same time; reading and identifying the functional architecture document, and creating a module definition diagram and an internal block diagram; the physical architecture design step specifically comprises the following steps: defining a software module for realizing each functional module; defining a physical data type and a data packaging mode for realizing each piece of functional data; and generating a state machine diagram for describing an interaction relationship and state driving logic of corresponding physical data when the software module runs, and defining a data transmission channel by determining a port and a protocol. According to the method, the problem of low efficiency of modeling design and communication cooperation caused by semantic limitation and structural mixing of a traditional SysML modeling method can be solved.

The invention discloses an interactive story machine based on an ROS and a large model and a control method of the interactive story machine. The story machine comprises an input module, an ROS system, a large model module, an audio output unit and a color ink screen. According to the invention, through cooperative work of software and hardware modules, an ROS system is used as an intelligent scheduling center, and meanwhile, a large model module is introduced, so that user interaction input modes and personalized demands of different user types can be understood and responded, and personalized story contents are dynamically generated; for the hearing-impaired user type, based on a barrier-free interaction mode, generating image prompt information and a smooth sign language action sequence, and driving a color ink screen to perform visual presentation through an optimized rendering instruction; and for a non-hearing-impaired user type, synchronously generating a story text fragment, a matched image illustration and voice information based on a multi-mode interaction mode, and providing an immersive story reading environment for different types of child users.

The invention discloses an ultrasonic welding pseudo soldering detection system and method, and relates to the technical field of ultrasonic welding detection, the system comprises a hardware assembly and a visual software module, the hardware assembly comprises an upper camera, a lens, an annular light source, a PLC lower computer and the like, and the visual software module configures program instructions such as initialization, image acquisition, feature detection and the like; according to the detection method, images are collected through the upper camera, detection of the expanded material size, the grid edge width, the grid area and the peripheral overflow area is completed in sequence, and pseudo soldering is automatically judged in combination with a visual algorithm. Non-destructive online full detection is achieved, the detection precision reaches + / -0.01 mm, the single-station detection rhythm is smaller than or equal to 1 second, the problems that traditional detection products are large in waste and high in misjudgment risk are solved, the method is suitable for new energy power battery copper-aluminum bar metal ultrasonic welding products, and the detection efficiency and the quality control level are improved.

The invention relates to the technical field of battery capacity testing, and discloses a lead-acid battery capacity testing system, which comprises a hardware platform and a software module, and is characterized in that the hardware platform comprises a single chip microcomputer, an ADC detection circuit, a nixie tube display module, a discharge control circuit, a key input module, a cooling fan and a current expansion interface; the software module runs on the single chip microcomputer, is based on an embedded operating system, and is configured to acquire a voltage signal and a current signal of the lead-acid battery in real time through the ADC detection circuit; and calculating the battery capacity by adopting a current integration method based on the current signal, and judging a discharge cut-off point based on the voltage signal. Through deep cooperation of a hardware platform and a software module, accurate and automatic testing of the capacity of the lead-acid battery is achieved, a current integration method is adopted as a core calculation principle, discharging cut-off judgment is carried out in combination with a voltage signal, and the accuracy and reliability of a capacity testing result are ensured.

The invention discloses a complex sea condition take-off and landing interaction platform based on a virtual reality technology and a design method. The complex sea condition take-off and landing interaction platform comprises a virtual take-off and landing simulation platform software module and a virtual take-off and landing hardware system. The virtual take-off and landing simulation platform software module is used for providing environment configuration, task scenario and simulation test functions; and the virtual take-off and landing hardware system is used for receiving driving operation input of a user and feeding back a virtual reality visualization effect and six-degree-of-freedom motion of the cabin. According to the invention, on the basis of complex sea condition take-off and landing motion safety evaluation requirements of the amphibious aircraft, simulation verification of a whole process of task scenario setting-human-in-the-loop simulation verification-execution condition evaluation can be realized through software module and hardware system design, and a coupling task efficiency result of unit operation and a design scheme is evaluated; and the complex sea condition take-off and landing adaptability design scheme iteration of the amphibious aircraft is supported.

A system and method for provisioning confidential data such as unique credentials is described. The technique initializes a whitebox cryptographic software module to a particular PKI client to soft-lock whitebox cryptographic operations to the particular PKI client and uniquely encrypting the credentials with a node-locking key (NLK) derivable from a digital certificate.