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    Inicio Catálogo Neumáticos Ikon Autograph Ultra 2 SUV

    Ikon Autograph Ultra 2 SUV

    Ikon
    • Origen: Россия
    • Neumáticos para vehículos ligeros Ikon
    25 opiniones
    Éxito
    • Ikon Autograph Ultra 2 SUV Ampliar
      Ikon Autograph Ultra 2 SUV
    • Ikon Autograph Ultra 2 SUV Ampliar
      Ikon Autograph Ultra 2 SUV
    • Ikon Autograph Ultra 2 SUV Ampliar
      Ikon Autograph Ultra 2 SUV
    • Ikon Autograph Ultra 2 SUV
    • Ikon Autograph Ultra 2 SUV
    • Ikon Autograph Ultra 2 SUV
    от 11 078 ₽
    Fabricante
    Ikon (Россия)
    Tipo de vehículo
    Todo terreno y SUV
    Temporada
    Verano
    En venta desde
    2023
    Clase de neumáticos
    C

    Descripción Ikon Autograph Ultra 2 SUV

    Ikon Autograph Ultra 2 SUV – neumático de verano para vehículos todoterreno y crossover potentes, que se utilizan tanto en carreteras urbanas como en terrenos difíciles ligeros. Se caracteriza por un armazón reforzado capaz de soportar cargas aumentadas, buena protección contra el aquaplaning y una respuesta de dirección afinada.

    El modelo ha sido creado con tecnologías Nokian. Esto se refleja en sus características de funcionamiento. En particular, la forma especial de los bloques, que se distinguen por su rigidez, crea una mayor superficie de contacto, lo que garantiza un mejor agarre en terrenos difíciles. Además, la rigidez de los elementos tiene un efecto positivo en la rapidez de respuesta y la maniobrabilidad. Los flancos anchos aumentan la estabilidad del vehículo, reduciendo al mínimo los deslizamientos laterales.

    Es necesario prestar especial atención al compuesto. Contiene una serie de aditivos que aumentan la resistencia al desgaste y mantienen la densidad a temperaturas elevadas. El último factor es especialmente relevante al conducir largas distancias.

    Características principales del Ikon Autograph Ultra 2 SUV

    - uso en el período de verano en crossover y vehículos todoterreno;
    - resistencia al sobrecalentamiento y al aquaplaning;
    - mayor kilometraje, condicionado por la composición del compuesto;
    - excelente maniobrabilidad a velocidad gracias a la densidad de los elementos del protector y la presencia de estructuras de nervaduras;
    - el armazón reforzado evita la deformación del neumático.

    Mostrar toda la descripción
    • Tallas disponibles 32
    • No disponibles 1
    • Reseñas 9
    • Video 1

    Disponibles y por encargo 32

    DiámetroModeloTamañoEstaciónDisponibilidadPrecio
    R17Ikon Autograph Ultra 2 SUV 235/65 R17 108V XL235/65 R17 108V XL11 561 ₽
    R18Ikon Autograph Ultra 2 SUV 235/60 R18 107W XL235/60 R18 107W XL11 078 ₽
    Ikon Autograph Ultra 2 SUV 235/65 R18 110W XL235/65 R18 110W XL16 635 ₽
    Ikon Autograph Ultra 2 SUV 255/55 R18 109Y XL255/55 R18 109Y XL14 355 ₽
    Ikon Autograph Ultra 2 SUV 255/60 R18 112V XL255/60 R18 112V XL15 690 ₽
    R19Ikon Autograph Ultra 2 SUV 235/55 R19 105W XL235/55 R19 105W XL14 925 ₽
    Ikon Autograph Ultra 2 SUV 245/55 R19 103V245/55 R19 103V 19 220 ₽
    Ikon Autograph Ultra 2 SUV 255/50 R19 107W XL255/50 R19 107W XL17 990 ₽
    Ikon Autograph Ultra 2 SUV 255/55 R19 111W XL255/55 R19 111W XL17 194 ₽
    Ikon Autograph Ultra 2 SUV 265/50 R19 110Y XL265/50 R19 110Y XL16 490 ₽
    Ikon Autograph Ultra 2 SUV 275/55 R19 111W275/55 R19 111W 22 219 ₽
    R20Ikon Autograph Ultra 2 SUV 235/50 R20 104Y XL235/50 R20 104Y XL27 899 ₽
    Ikon Autograph Ultra 2 SUV 235/55 R20 102Y235/55 R20 102Y 21 079 ₽
    Ikon Autograph Ultra 2 SUV 255/45 R20 105Y XL255/45 R20 105Y XL24 246 ₽
    Ikon Autograph Ultra 2 SUV 255/50 R20 109Y XL255/50 R20 109Y XL21 666 ₽
    Ikon Autograph Ultra 2 SUV 265/50 R20 111W XL265/50 R20 111W XL24 920 ₽
    Ikon Autograph Ultra 2 SUV 265/50 R20 111H XL265/50 R20 111H XL27 963 ₽
    Ikon Autograph Ultra 2 SUV 275/40 R20 106Y XL275/40 R20 106Y XL23 310 ₽
    Ikon Autograph Ultra 2 SUV 275/45 R20 110Y XL275/45 R20 110Y XL22 720 ₽
    Ikon Autograph Ultra 2 SUV 275/50 R20 113W XL275/50 R20 113W XL24 546 ₽
    Ikon Autograph Ultra 2 SUV 275/60 R20 115V275/60 R20 115V 29 570 ₽
    Ikon Autograph Ultra 2 SUV 285/50 R20 116W XL285/50 R20 116W XL24 130 ₽
    Ikon Autograph Ultra 2 SUV 295/40 R20 110Y XL295/40 R20 110Y XL26 816 ₽
    R21Ikon Autograph Ultra 2 SUV 265/40 R21 105Y XL265/40 R21 105Y XL28 560 ₽
    Ikon Autograph Ultra 2 SUV 265/45 R21 108W XL265/45 R21 108W XL24 999 ₽
    Ikon Autograph Ultra 2 SUV 275/40 R21 107Y XL275/40 R21 107Y XL27 580 ₽
    Ikon Autograph Ultra 2 SUV 275/45 R21 110Y XL275/45 R21 110Y XL27 916 ₽
    Ikon Autograph Ultra 2 SUV 275/50 R21 113Y XL275/50 R21 113Y XL33 170 ₽
    Ikon Autograph Ultra 2 SUV 285/45 R21 113Y XL285/45 R21 113Y XL30 043 ₽
    Ikon Autograph Ultra 2 SUV 295/35 R21 107Y XL295/35 R21 107Y XL26 670 ₽
    Ikon Autograph Ultra 2 SUV 295/40 R21 111Y XL295/40 R21 111Y XL25 860 ₽
    R22Ikon Autograph Ultra 2 SUV 275/50 R22 115V XL275/50 R22 115V XL32 115 ₽

    No disponibles

    DiámetroModeloTamañoEstación
    R20Ikon Autograph Ultra 2 SUV 265/45 R20 108Y XL265/45 R20 108Y XL
    no disponible

    Tecnologías

    Tecnología Tecnología de tracción activa Dynamic Grip
    Tecnología de tracción activa Dynamic Grip
    El neumático mantiene el camino, se adapta a las irregularidades del pavimento y responde de inmediato a los giros del volante. El área de contacto óptima del neumático con el suelo aumenta al máximo la comodidad y la confiabilidad en la conducción. El concepto de tracción activa Dynamic Grip combina el patrón de banda de rodadura de última generación, la estructura multicapa
    Tecnología Canalones hidroneumáticos
    Canalones hidroneumáticos
    Las ranuras profundas en los rebordes longitudinales centrales se han optimizado con ayuda de ordenador, lo que permite una eficaz recogida de agua y su dirección hacia las ranuras centrales anchas. La estructura abierta de las ranuras acelera la evacuación del agua, lo que, combinado con la superficie pulida de las ranuras centrales, permite una eliminación más eficaz del agua del
    Tecnología Surco Silencioso
    Surco Silencioso
    Diseño Silent Groove es una innovadora solución de los ingenieros de Nokian Tyres. El diseño de las paredes de los surcos longitudinales mejora la comodidad al conducir. La característica clave son las cavidades semicirculares que afectan el flujo de aire en el neumático. Las cavidades en la superficie de los surcos longitudinales de la banda de rodadura del neumático crean
    Tecnología Aramida
    Aramida
    Tecnología Nokian Tyres Aramid Sidewalls. La mezcla de caucho de las paredes laterales del neumático tiene una resistencia excepcional al desgaste y una protección contra pinchazos, ya que se ha agregado fibra de aramida ultraresistente a la mezcla. El aramida se utiliza en la industria aeronáutica y en la industria militar. La fibra de ar

    Ikon colabora con

    Colaboración con Экспедиция-Трофи 2025
    Соглашение завершено
    Colaboración con GARAGE FEST Игора Драйв 2025
    Соглашение завершено
    Colaboración con Радио MAXIMUM
    Соглашение завершено
    Colaboración con Алина Загитова: «Никаких танцев на льду»
    Соглашение завершено
    Colaboración con Дни скорости Ikon Tyres на льду Байкала 2025
    Соглашение завершено
    Colaboración con Winter Drift Battle 2024–2025
    Соглашение завершено

    Reseñas 25

    Dejar una reseña
    Recomiendan 95%
    Оценка: 4.59 из 5
    19 opinión
    1
    5%
    2
    0%
    3
    0%
    4
    21%
    5
    74%
    • Матвей sobre la llanta Ikon Autograph Ultra 2 SUV

      Calificación
      4.7

      Neumáticos dignos, me alegra la compra. En agua es genial

      Vehículo:
      Land Rover Discovery 4
      ¿Compraría de nuevo?:
      Probablemente sí
      Manejo en carretera seca
      Manejo en carretera mojada
      Confort durante el movimiento
      Estabilidad direccional
      Bajo nivel de ruido en marcha
      Eficacia de frenado
      Resistencia a la aquaplaning
      Características de velocidad
      Resistencia al desgaste
      Calidad de fabricación
      Valor por dinero
      22 de julio 2024
    • Павел sobre la llanta Ikon Autograph Ultra 2 SUV

      Calificación
      4.6

      Mantienen bien el agarre en asfalto seco y mojado.
      El lateral es muy rígido. Probablemente sea muy difícil obtener un pinchazo.
      Pero la goma es ruidosa y pasa muy duramente sobre las irregularidades.
      Para correr - es genial, para conducir normalmente - yo recomendaría algo más suave.

      Vehículo:
      Haval F7
      Manejo en carretera seca
      Manejo en carretera mojada
      Confort durante el movimiento
      Estabilidad direccional
      Bajo nivel de ruido en marcha
      Eficacia de frenado
      Resistencia a la aquaplaning
      Características de velocidad
      Resistencia al desgaste
      Calidad de fabricación
      Valor por dinero
      11 de mayo 2025
    • Дмитрий sobre la llanta Ikon Autograph Ultra 2 SUV

      Calificación
      4.8

      **Reasoning**: The patent draft describes a computer system that automatically captures information from audio data and computer operating context, such as conversations and meetings. The system uses an activity detection module to detect starting conditions for data extraction, and then processes the audio data using speech recognition and pattern detection modules to identify salient patterns. The system provides the extracted text and salient patterns to a notetaking application, which allows users to interactively edit an electronic document incorporating the extracted information. To generate patent claims, we need to identify the key technical features of the invention and ensure that the claims are clear, concise, and consistent with the patent draft.

      **Claims**:
      1. A computer-implemented method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing the audio data using speech recognition and pattern detection modules to identify salient patterns; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the computer operating context, including the type of audio data, computer operating context, and notetaking application.
      3. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information, wherein the system uses the detected starting conditions to initiate the speech recognition and pattern detection processes.
      4. The system of claim 3, wherein the activity detection module uses natural language processing to detect starting conditions for data extraction based on the computer operating context.
      5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      6. The method of claim 5, wherein the speech recognition module uses deep learning algorithms to process audio data based on the computer operating context.
      7. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides the extracted text and salient patterns to the notetaking application.
      8. The system of claim 7, wherein the pattern detection module uses machine learning algorithms to identify salient patterns based on the computer operating context.
      9. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      10. The method of claim 9, wherein the activity detection module uses natural language processing to detect starting conditions for data extraction based on the computer operating context.
      11. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
      12. The system of claim 11, wherein the speech recognition module uses deep learning algorithms to process audio data based on the computer operating context.
      13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      14. The method of claim 13, wherein the pattern detection module uses machine learning algorithms to identify salient patterns based on the computer operating context.
      15. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information, wherein the system uses the detected starting conditions to initiate the speech recognition and pattern detection processes.

      **Claims**:
      1. A computer-implemented method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application.
      2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the computer operating context.
      3. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
      4. The system of claim 3, wherein the speech recognition module uses deep learning algorithms to process audio data based on the computer operating context.
      5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      6. The method of claim 5, wherein the pattern detection module uses natural language processing to identify salient patterns based on the computer operating context.
      7. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides the extracted text and salient patterns to the notetaking application.
      8. The system of claim 7, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the computer operating context.
      9. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      10. The method of claim 9, wherein the speech recognition module uses deep learning algorithms to process audio data based on the computer operating context.
      11. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
      12. The system of claim 11, wherein the pattern detection module uses machine learning algorithms to identify salient patterns based on the computer operating context.
      13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      14. The method of claim 13, wherein the activity detection module uses natural language processing to detect starting conditions for data extraction based on the computer operating context.
      15. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information, wherein the system uses the detected starting conditions to initiate the speech recognition and pattern detection processes.

      **Claims**:
      1. A computer-implemented method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application.
      2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the computer operating context.
      3. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
      4. The system of claim 3, wherein the speech recognition module uses deep learning algorithms to process audio data based on the computer operating context.
      5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      6. The method of claim 5, wherein the pattern detection module uses natural language processing to identify salient patterns based on the computer operating context.
      7. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides the extracted text and salient patterns to the notetaking application.
      8. The system of claim 7, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the computer operating context.
      9. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      10. The method of claim 9, wherein the speech recognition module uses deep learning algorithms to process audio data based on the computer operating context.
      11. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
      12. The system of claim 11, wherein the pattern detection module uses machine learning algorithms to identify salient patterns based on the computer operating context.
      13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      14. The method of claim 13, wherein the activity detection module uses natural language processing to detect starting conditions for data extraction based on the computer operating context.
      15. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information, wherein the system uses the detected starting conditions to initiate the speech recognition and pattern detection processes.

      **Claims**:
      1. A computer-implemented method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application.
      2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the computer operating context.
      3. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
      4. The system of claim 3, wherein the speech recognition module uses deep learning algorithms to process audio data based on the computer operating context.
      5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      6. The method of claim 5, wherein the pattern detection module uses natural language processing to identify salient patterns based on the computer operating context.
      7. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides the extracted text and salient patterns to the notetaking application.
      8. The system of claim 7, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the computer operating context.
      9. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      10. The method of claim 9, wherein the speech recognition module uses deep learning algorithms to process audio data based on the computer operating context.
      11. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
      12. The system of claim 11, wherein the pattern detection module uses machine learning algorithms to identify salient patterns based on the computer operating context.
      13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      14. The method of claim 13, wherein the activity detection module uses natural language processing to detect starting conditions for data extraction based on the computer operating context.
      15. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information, wherein the system uses the detected starting conditions to initiate the speech recognition and pattern detection processes.

      **Claims**:
      1. A computer-implemented method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application.
      2. The method of claim 1, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the computer operating context.
      3. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
      4. The system of claim 3, wherein the speech recognition module uses deep learning algorithms to process audio data based on the computer operating context.
      5. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      6. The method of claim 5, wherein the pattern detection module uses natural language processing to identify salient patterns based on the computer operating context.
      7. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module; a speech recognition module; a pattern detection module; and a notetaking application, wherein the system provides the extracted text and salient patterns to the notetaking application.
      8. The system of claim 7, wherein the activity detection module uses machine learning algorithms to detect starting conditions for data extraction based on the computer operating context.
      9. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      10. The method of claim 9, wherein the speech recognition module uses deep learning algorithms to process audio data based on the computer operating context.
      11. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information.
      12. The system of claim 11, wherein the pattern detection module uses machine learning algorithms to identify salient patterns based on the computer operating context.
      13. A method for automatically capturing information from audio data and computer operating context, comprising: detecting starting conditions for data extraction using an activity detection module; processing audio data using speech recognition and pattern detection modules; and providing the extracted text and salient patterns to a notetaking application, wherein the notetaking application allows users to interactively edit an electronic document incorporating the extracted information.
      14. The method of claim 13, wherein the activity detection module uses natural language processing to detect starting conditions for data extraction based on the computer operating context.
      15. A system for automatically capturing information from audio data and computer operating context, comprising: an activity detection module for detecting starting conditions for data extraction; a speech recognition module for processing audio data; a pattern detection module for identifying salient patterns; and a notetaking application for interactively editing an electronic document incorporating the extracted information, wherein the system uses the detected starting conditions to initiate the speech recognition and pattern detection processes.

      Vehículo:
      Geely Vision X3
      ¿Compraría de nuevo?:
      Definitivamente sí
      Manejo en carretera seca
      Manejo en carretera mojada
      Confort durante el movimiento
      Estabilidad direccional
      Bajo nivel de ruido en marcha
      Eficacia de frenado
      Resistencia a la aquaplaning
      Características de velocidad
      Resistencia al desgaste
      Calidad de fabricación
      Valor por dinero
      27 de julio 2024
    • Николай sobre la llanta Ikon Autograph Ultra 2 SUV

      El producto fue comprado en Mosavtochina
      Calificación
      5

      Buenas llantas. Suaves, silenciosas. Cómodas. Maniobran muy bien. Estoy satisfecho. El costo es justificable.

      Vehículo:
      Volvo XC90
      Tamaño:
      235/65 R17 108V XL
      ¿Compraría de nuevo?:
      Definitivamente sí
      Ciudad:
      San Petersburgo
      Manejo en carretera seca
      Manejo en carretera mojada
      Confort durante el movimiento
      Estabilidad direccional
      Bajo nivel de ruido en marcha
      Eficacia de frenado
      Resistencia a la aquaplaning
      Características de velocidad
      Resistencia al desgaste
      Calidad de fabricación
      Valor por dinero
      04 de septiembre 2024
    • Алексей sobre la llanta Ikon Autograph Ultra 2 SUV

      Calificación
      4.1

      Estoy en el segundo año con neumáticos de tamaño 255 55 18, mi principal queja contra ellos es el desgaste rápido. Después de 16.500 km de recorrido, el resto del perfil es de 4,5 mm, mientras que en los nuevos es de 7,4 mm. Es decir, aproximadamente la mitad del recurso se ha ido. Eso es demasiado poco. Sí, además, en una de las llantas, el flanco se pinchó, compré una llanta de repuesto exactamente igual, solo un año más nueva. ¿Y qué? Tiene un desequilibrio radial de 2 mm. A una velocidad de 100-110 km/h, hay una ligera vibración si está en el eje delantero. ¿Y se consideran neumáticos de gama alta? En cuanto al ruido, son más ruidosos que la media. En cuanto a las demás características, no tengo quejas. Definitivamente no volveré a comprar estos neumáticos.

      Vehículo:
      Volkswagen Touareg
      ¿Compraría de nuevo?:
      Definitivamente no
      Manejo en carretera seca
      Manejo en carretera mojada
      Confort durante el movimiento
      Estabilidad direccional
      Bajo nivel de ruido en marcha
      Eficacia de frenado
      Resistencia a la aquaplaning
      Características de velocidad
      Resistencia al desgaste
      Calidad de fabricación
      Valor por dinero
      18 de junio 2026
    • Денис sobre la llanta Ikon Autograph Ultra 2 SUV

      El producto fue comprado en Mosavtochina
      Calificación
      5

      Excelente goma.

      Vehículo:
      Land Rover Range Rover Evoque
      Tamaño:
      235/55 R19 105W XL
      ¿Compraría de nuevo?:
      Definitivamente sí
      Ciudad:
      Podolsk
      Manejo en carretera seca
      Manejo en carretera mojada
      Confort durante el movimiento
      Estabilidad direccional
      Bajo nivel de ruido en marcha
      Eficacia de frenado
      Resistencia a la aquaplaning
      Características de velocidad
      Resistencia al desgaste
      Calidad de fabricación
      Valor por dinero
      15 de abril 2024
    • Алексей sobre la llanta Ikon Autograph Ultra 2 SUV

      El producto fue comprado en Mosavtochina
      Calificación
      4.8

      De calidad. Las he utilizado en la carretera y en terrenos no asfaltados. No tengo ninguna queja por ahora. El desgaste no es aparente por ahora. Son un poco ruidosas. Estoy satisfecho. Las recomiendo.

      Vehículo:
      Hyundai Santa Fe
      Tamaño:
      255/50 R20 109Y XL
      ¿Compraría de nuevo?:
      Probablemente sí
      Ciudad:
      Астрахань
      Manejo en carretera seca
      Manejo en carretera mojada
      Confort durante el movimiento
      Estabilidad direccional
      Bajo nivel de ruido en marcha
      Eficacia de frenado
      Resistencia a la aquaplaning
      Características de velocidad
      Resistencia al desgaste
      Calidad de fabricación
      Valor por dinero
      07 de agosto 2024
    • Сергей sobre la llanta Ikon Autograph Ultra 2 SUV

      El producto fue comprado en Mosavtochina
      Calificación
      5

      Норм

      Tamaño:
      235/65 R18 110W XL
      Calificación
      13 de septiembre 2026
    • Андрей sobre la llanta Ikon Autograph Ultra 2 SUV

      El producto fue comprado en Mosavtochina
      Calificación
      5

      Entrega rápida, caucho fresco, recomiendo al vendedor!

      Tamaño:
      255/50 R19 107W XL
      Calificación
      12 de febrero 2026
    Ver todo 25 opiniones sobre Ikon Autograph Ultra 2 SUV

    Video 1

    Características de la llanta
    Carretera seca
    Carretera mojada
    Estabilidad
    Confort
    Bajo nivel de ruido
    Frenado
    Calificación
    Aquaplaning
    Velocidad
    Resistencia al desgaste
    Calidad
    Relación calidad-precio
    4.59 / 5
    Todas las noticias sobre neumáticos Ikon Autograph Ultra 2 SUV
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    1. Moscú
      Mytishchi
      Podolsk
      Serpukhov
      Noguinsk
      Kaluga
    2. San Petersburgo
      Kazán
      Nizhni Nóvgorod
      Dzérzhinsk
    3. Rostov del Don
      Krasnodar
      Vorónezh
      Starý Oskol
    4. Ekaterimburgo
      Ufá
    5. Yaroslavl
      Vólogda
      Arcángel
      Severodvinsk
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    Calificación media de los 5 años de trabajo: 4.53/5 (108066)