RULES FOR SAFE OPERATION

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3

 

3

 

 

 

 

 

 

13

2

 

4

11

 

 

 

 

 

 

 

 

7

 

 

5

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8

 

 

 

15

6

12

9

 

6

10

216

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9

1

19

17 18

21

20

CHAIN COMPONENTS

1.Saw Chain 2.Guide Bar 3.Front Handle 4.Handle Bracket 5.Pole Locking Nut 6.Power Cord 7.Height Adjuster Knob 8.Outer Pole 9.Lock-off Switch 10.Trigger Start/ Stop Switch 11.Rear Handle

12.Hand Guard 13.Oil Tank Cap 14.Electric Motor 15.Rear Hand Guard 16.Guide Bar Nose 17.Sprocket Cover 18.Chain Catcher 19.Bar Retaining Nuts 20.Spikes

21.Tension Adjustment Screw

SAFETY FEATURES

Numbers preceding the descriptions correspond with the numbers on preceding page to help you locate the safety feature.

1.LOW-KICKBACK CHAIN helps significantly reduce kickback, or the intensity of kickback, due to spe- cially designed depth gauges and Guard links.

9.LOCK / OFF BUTTON prevents accidental acceler- ation of the saw motor. The trigger cannot be squeezed unless lock/off button is depressed.

10.TRIGGER START / STOP SWITCH stops saw

motor when released.

12.HAND GUARD protects the operator’s left hand in the event it slips off the front handle while saw is running.

14.ELECTRIC MOTOR is double insulated for added safety.

18.CHAIN CATCHER reduces the danger of injury in the event saw chain breaks or derails during opera- tion. The catcher is designed to intercept a whipping chain.

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MTD PS manual Chain Components

PS specifications

MTD PS, or Machine Translation Deep Post-Editing System, is an innovative solution designed to improve the accuracy and quality of machine-generated translations. This system is particularly instrumental for businesses and organizations that rely on multilingual communication and require high-quality translations for documents, websites, and other materials.

One of the main features of MTD PS is its deep learning architecture, which employs neural networks to analyze and refine machine-generated translations. This technology allows the system to understand linguistic nuances, context, and semantics, resulting in translations that are not only grammatically correct but also culturally relevant. The adaptability of deep learning means that the system can continuously improve over time by learning from user feedback and various language data.

Another significant characteristic of MTD PS is its user-friendly interface. Designed with usability in mind, the system allows post-editors to review and enhance translations with ease. Suggestions for improvements are generated in real-time, enabling human translators to make quick decisions and apply necessary changes. This collaboration between humans and machines amplifies productivity while maintaining high standards of quality.

MTD PS integrates advanced natural language processing (NLP) technologies, which are crucial for understanding and generating human-like text. With features such as context-aware formatting and terminology management, the system ensures consistency across different translations, streamlining the localization process. NLP capabilities also facilitate the handling of idiomatic expressions and jargon specific to certain fields, enabling the system to cater to various industries.

Additionally, MTD PS is equipped with extensive data analytics features. It allows users to track performance metrics such as translation accuracy and editor efficiency. This data-driven approach helps organizations evaluate the effectiveness of their translation processes and make informed decisions about future localization strategies.

In summary, MTD PS is a powerful tool that leverages deep learning, NLP technologies, and user-centric design to enhance the quality of machine translations. Its ability to adapt, learn, and provide actionable insights makes it an invaluable asset for a wide range of applications in the global marketplace. As businesses continue to expand their reach across borders, systems like MTD PS will play a pivotal role in ensuring effective communication and fostering collaboration across cultures.