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This technology involves manufacturing leather fabric with excellent antibacterial properties using zinc zeolite and applying it as a shoe material. Specifically, it is an antibacterial leather manufacturing technology that applies a zinc zeolite composition during the leather dyeing and finishing process and subsequent coating process.
Existing antibacterial leather often uses chemicals that raise concerns about harmfulness to achieve antibacterial performance, and it has limitations in sufficiently suppressing odor and athlete's foot fungus problems caused by sweat and bacteria when wearing shoes. This technology proposes a method of treating raw leather material with zinc zeolite chemicals and coating the surface with a coating composition containing acrylic binder, urethane binder, and zinc zeolite.
Accordingly, this technology can simultaneously enhance both the antibacterial and physical properties of leather, offering industrial applicability in shoes, functional leather products, eco-friendly antibacterial materials, and household goods.
This technology relates to hybrid shoes with replaceable heels that can be securely attached to and detached from the shoe body. Specifically, it is a structural technology that disperses front-to-back and lateral pressure generated during walking by utilizing a curved front hook and a streamlined rear hook.
Existing replaceable heel structures made it difficult for users to easily change heels or posed a risk of the heel wobbling or detaching during walking, thereby limiting practicality and safety. To address this, this technology proposes a method that enhances fastening stability by positioning front and rear hooks at the rear of the shoe body and dispersing the pressure acting on the replaceable heel through their respective curved structures.
As a result, this technology allows for the use of various heel designs with a single shoe body and can be combined with flexible display panels, among other things, to expand into areas such as custom fashion shoes, functional footwear, and personalized wearable products.
This technology relates to a skin brightening cosmetic material and cosmetic composition containing a mixed extract of Poria cocos, soybean, licorice, and citrus unshiu peel as an active ingredient. Specifically, it is a cosmetic composition and manufacturing technology that regulates melanin formation and skin tone changes using a plant-based mixed extract.
Existing skin brightening cosmetics often rely on specific ingredients or have limitations in sufficiently achieving desired effects such as overall skin tone improvement, hyperpigmentation relief, and reduction of yellow undertones. This technology proposes a method of applying an extract, obtained by mixing Poria cocos, soybean, licorice, and citrus unshiu peel in specific weight ratios, followed by ethanol extraction, concentration, and freeze-drying, to skin toner and cream compositions.
Accordingly, this technology is expected to inhibit melanocyte growth, melanin formation, tyrosinase activity, and related gene expression, making it valuable for use in functional cosmetics, skin tone improvement products, and the natural product-based beauty material industry.
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.
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 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.
