This technology relates to a system and method for analyzing application installation information. Specifically, it is an application installation information extraction technique that analyzes Android installation logs and DB files.
Existing technologies faced limitations in malware detection within current systems, often addressed by analyzing system call logs and proposing methods to detect malicious activity in Openstack and HDFS using natural language sequence models and LSTM (Long Short-Term Memory). To overcome this, the present technology proposes a configuration that includes a log collection unit, a log analysis unit, and a database generation unit for collecting installation logs, analyzing configuration information, and recording application configuration information.
Accordingly, this technology can improve the ability to provide application configuration information by analyzing log extension files and DB extension files related to configuration data. It holds value for application in the software, IT, and internet sectors.
This technology relates to a harmonic compensation apparatus and method for a single-phase grid-connected inverter. Specifically, it is a single-phase grid-connected inverter harmonic compensation technology combining PI·PR control.
Conventional technologies needed to address the complexity of designing controllers to eliminate harmonics in a stationary reference frame and improve the power factor in grid-connected power systems. Accordingly, this technology proposes a configuration that includes a filtering unit, a current controller, harmonic compensation, and a pulse width modulation unit for a single-phase system interconnected inverter.
As a result, this technology can improve the output quality of a single-phase system interconnected inverter by reducing the Total Harmonic Distortion (THD) value. It has practical value in the fields of electricity, power generation, and energy.
This technology relates to an artificial neural network rule extraction apparatus and method. Specifically, it is an explainable AI technology that extracts the decision basis of artificial neural networks into logical rules.
Existing technologies faced limitations with traditional methods and required a more efficient and accurate approach, especially in extracting rules from artificial neural networks for data with continuous attributes. To address this, the present technology proposes a configuration that includes an artificial neural network rule extractor for learning input datasets, comprising a data learning unit, a first rule extraction unit, a binary classification unit, and a second rule extraction unit.
Accordingly, this technology can improve the accuracy and efficiency of extracting rules from artificial neural networks for data with continuous attributes, overcome the limitations of traditional methods, and provide a more efficient and accurate approach. It has value for utilization in the software, IT, and internet fields.
This technology relates to an event-operation-based multi-action intention inference device and method. Specifically, it is a multi-action intention inference technology that utilizes time-series perceptual information and conflict rules.
Existing technologies sought to address the difficulty of models predicting multiple intentions simultaneously and needed to resolve the lack of information at specific points in time for single intention prediction. To address this, this technology proposes a configuration that includes an input unit, an intention inference module, a heartbeat determination module, and verification of the error module.
Accordingly, this technology can improve the accuracy of action intention prediction and reduce the computational load required for decision-making. It has value for utilization in the healthcare, pharmaceutical, and software sectors.
This technology relates to a naval combat system device and its implementation method for controlling the combat operations of a naval vessel based on artificial intelligence. Specifically, it is a technology that processes reinforcement learning-based tactical and combat execution phases by linking sensors, consoles, platform equipment, and weapon systems with a system cabinet.
Existing naval combat systems faced challenges in providing quick and consistent judgments in complex combat situations when sensor information, platform control, weapon control, and tactical recommendations were operated separately. To address this, this technology proposes a method that integrates simulation data-based learning and combat execution algorithms by configuring sensor interface modules, multi-functional console modules, platform interface modules, weapon interface modules, and a system cabinet.
Accordingly, this technology can link AI-based tactical recommendations with equipment control during detection, control, and engagement processes, which is expected to have ripple effects in naval vessel operation automation, combat system advancement, and virtual training-linked defense systems.
This technology concerns a device and method for preventing the freezing of washing machine drain hoses. Specifically, it is a device technology that prevents washing machine drain hose freezing through ultrasonic vibration.
Existing technologies needed to address the frequent failure of washing machine drainage due to residual freezing in cold environments. This technology proposes a configuration that includes a drain body, a vibrator, an excitation unit, and a controller to prevent freezing of the drain pipe.
Accordingly, this technology can improve the efficiency of preventing drain pipe freezing and residual water in washing machines by using ultrasonic vibration. It has practical value in the fields of TVs, home appliances, and electronic devices.
This technology relates to an indoor positioning system and an indoor positioning method using the same. Specifically, it is an indoor positioning technology utilizing Wi-Fi and device sensor fusion.
Existing technologies, particularly conventional indoor positioning systems, needed to address precision issues in environments with obstacles such as Wi-Fi interference, walls, and human bodies. To address this, this technology proposes a configuration that includes a user terminal with a sensor, a wireless communication receiver, an AP selection unit, a distance measurement unit, a threshold comparison unit, and a position compensation unit.
Accordingly, this technology can improve the precision of indoor positioning systems by utilizing sensor data and Wi-Fi RSS values to estimate the user's location. It is valuable for applications in the IT, internet, software, and smartphone sectors.
This technology relates to a frame for mounting multiple laser radars, a laser radar system including the frame, and a method for integrating sensing data coordinates from the multiple laser radars. In particular, it is an automotive laser radar system technology that integrates coordinates from multiple low-cost LiDARs.
Existing technologies faced the challenge of high manufacturing costs and low precision associated with expensive multi-channel laser radars. To address this, this technology proposes a configuration comprising multiple laser radars positioned on the upper exterior of a vehicle, a frame unit for supporting the laser radars, and a controller for integrating sensed data and virtualized coordinates.
Consequently, this technology can improve precision and reduce the manufacturing cost of laser radar systems by implementing multi-channel laser radars using multiple low-cost laser radars. It offers significant value for applications in the automotive, mobility, electronic device, and electronic component sectors.
This technology relates to a monitoring system that monitors services deployed using a service mesh architecture. Specifically, it is a Service Mesh-based Microservice QoS Monitoring and Recovery Technology.
Existing technologies needed to address the complexity and challenges of service monitoring in microservice architectures by providing a service monitoring system that ensures service quality and efficient recovery procedures. Therefore, this technology proposes a configuration that includes an execution unit, an analysis section, a decision unit, and service discovery for monitoring services and ensuring service quality within a service mesh architecture.
Accordingly, this technology can improve monitoring and recovery processes in microservice architectures by providing a service monitoring system that ensures service quality and efficient recovery procedures. It offers valuable applications in the IT, internet, and software sectors.
This technology pertains to a bus stop operation system that manages passenger stop requests and whether buses can pass without stopping at bus stops. Specifically, it is a technology that displays scheduled stop information by linking bus information display devices, bus electronic display boards, control terminals, and integrated management servers.
At existing bus stops, it is difficult for drivers to clearly know if there are passengers waiting to board. Conversely, buses might unnecessarily stop at stops where no passengers are waiting, leading to decreased operational efficiency. Therefore, this technology proposes a method where, when a passenger selects a specific bus number on the display device, the control terminal analyzes that bus as a target for stopping and displays the scheduled stop information on the electronic display board and to the bus.
Accordingly, this technology can clearly communicate passengers' intent to board while reducing unnecessary stops, making it applicable to smart bus stops, public transportation operation management, and improving the efficiency of traffic services.
This technology relates to a failure recovery method for integrated cloud systems that include multiple platforms. Specifically, it is a technology for automatically recovering from workload failures in multi-platform clouds.
Existing technologies needed to ensure rapid service recovery without resource waste by addressing the problem of workload failure recovery in multi-platform cloud environments. This technology proposes a configuration that includes a method and system for integrating cloud systems, encompassing components such as alarm sensors, integrated management platforms, and platforms for workload deployment.
Accordingly, this technology can improve the efficiency of workload failure recovery in multi-platform cloud environments by reducing downtime and resource waste. It has value for utilization in the IT, internet, and software fields.
This technology relates to a microscope-based augmented reality navigation method, an apparatus for performing the same, and a recording medium. Specifically, it is an AR navigation technology that aligns intraoperative microscopic images with a 3D brain model.
Conventional technologies could not account for brain deformation over time and faced limitations such as errors caused by matching the skull instead of the brain. This technology addresses these issues by proposing a configuration that includes a rigid registration unit, simulation considerations, and an augmented reality controller.
Accordingly, this technology can improve the accuracy of navigation systems by providing real-time deformation of the brain model and enhancing surgeons' ability to confirm the precise shape of brain tissue during surgery. It has valuable applications in the healthcare, pharmaceutical, software, and electronics sectors.
This technology concerns a device and method for preventing cache side-channel attacks in blockchain wallet systems, and a recording medium for performing the method. Specifically, it is a security technology that protects blockchain wallet keys from cache side-channel attacks.
Existing technologies had a security vulnerability where blockchain wallet passwords or private keys could be exposed through cache side-channel attacks. To address this, this technology proposes a method that manages cache occupancy status and access patterns during wallet execution, and controls transaction processing and private key operations to prevent them from being inferred by external attackers.
As a result, this technology can enhance the protection level of blockchain wallet private keys and improve the security and reliability of digital asset trading services. It has value for use in the finance, insurance, software, IT, and internet sectors.
This technology relates to an ontology-based event calculus rule generation apparatus and method for recognizing human behavioral intentions. Specifically, it is a rule generation technology that recognizes human behavioral intentions using ontology and event calculus.
Existing technologies needed to overcome the limitations of conventional methods by directly defining event rules for actions, reflecting the expert knowledge of system developers rather than domain experts. To address this, the present technology proposes a configuration that includes a rule converter, an event recognizer, and an event calculus knowledge base for generating event rules for actions to recognize intent.
Accordingly, this technology can improve the application of expert knowledge for intent recognition and enable more efficient system development for healthcare. It holds value in the healthcare, pharmaceutical, and software sectors.
This technology relates to a system and method for blocking potential risks in naval combat systems that utilize reinforcement learning. Specifically, it is a technology that controls the AI's level of intervention during combat simulation and operational execution through the AI terminal's tactical inference module and AI mode provision module.
Existing reinforcement learning-based combat systems, if trained solely on achieving objectives, could not sufficiently reflect rules of engagement, operational guidelines, and the necessity of human intervention, potentially leading to dangerous decision-making. To address this, this technology proposes a method that provides definitions of intervention levels, such as AI Mode 0 to 5, and performs tactical inference and constraint reflection according to the corresponding mode before the agent acts.
Accordingly, this technology can progressively manage the autonomy level of military AI and secure the supervisory capability of operational personnel, thereby contributing to ensuring the safety of defense AI, naval combat systems, and high-risk reinforcement learning systems.
