12 research outputs found

    Human Inspired Behavioural Control for Robot-to-Human Object Handover

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    āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāļĻāļēāļŠāļ•āļĢāđŒāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ• (āļ§āļīāļĻāļ§āļāļĢāļĢāļĄāđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļāļĨāđāļĨāļ°āđ€āļĄāļ„āļēāļ—āļĢāļ­āļ™āļīāļāļŠāđŒ), 2564Currently, robots play an increasingly important role in human life, as the robots are capable of safely performing human-robot interactive tasks. As ageing and disability societies have become a challenge social problem in Thailand and all over the world, due to the shortage of care workers. Subsequently, to enhance the quality of life of elderly and disabled people, service robots have been taken into account to support household chores, particularly passing an object to a human. Therefore, this thesis focuses on the development of robotic human-like control by initially understanding how an equivalent human-human interaction can perform object handover naturally, reliably and safely. The preliminary human-human handover (HHH) tests were carried out to acknowledge the dynamic behavioural characteristics of the human participants in HHH. The experimental findings intensively explained human handover strategies, the interactive force profiles, object handover times, transfer locations, and the mathematical model of the giver’s arm while regulating the exerted force. The understanding of HHH behavioural responses leads to the proper design of a conceptual framework for a robot control system. The substantive tests were developed, in which a Toyota Human Support Robot (HSR) was implemented based on human-like behavioural control. Additionally, the robotic impedance control, which is suitable to control the HRS’s force-position relation while interacting with the human environment, was used. The optimized impedance parameters were experimentally identified. The main results show that the performance of the robot impedance control can be considered acceptable for HHH. This allowed the HSR to successfully pass the object to the human in a safe, reliable, and timely manner.āļ›āļąāļˆāļˆāļļāļšāļąāļ™āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāđ€āļĢāļīāđˆāļĄāļĄāļĩāļšāļ—āļšāļēāļ—āļ—āļĩāđˆāļŠāļģāļ„āļąāļāļĄāļēāļāļ‚āļķāđ‰āļ™āļ•āđˆāļ­āļāļēāļĢāļ”āļģāļĢāļ‡āļŠāļĩāļ§āļīāļ•āļ›āļĢāļ°āļˆāļģāļ§āļąāļ™āļ‚āļ­āļ‡āļĄāļ™āļļāļĐāļĒāđŒāļ­āļąāļ™ āđ€āļ™āļ·āđˆāļ­āļ‡āļĄāļēāļˆāļēāļāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļŠāļēāļĄāļēāļĢāļ–āļ—āļģāļ‡āļēāļ™āļĢāđˆāļ§āļĄāļāļąāļ™āļāļąāļšāļĄāļ™āļļāļĐāļĒāđŒāđƒāļ™āļŦāļĨāļēāļĒāļĢāļđāļ›āđāļšāļšāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āļ›āļĨāļ­āļ”āļ āļąāļĒ āļ­āļĩāļāļ—āļąāđ‰āļ‡āļžāļšāļ§āđˆāļē āļŠāļąāļ‡āļ„āļĄāļœāļđāđ‰āļŠāļđāļ‡āļ­āļēāļĒāļļāđāļĨāļ°āļ„āļ™āļžāļīāļāļēāļĢāļāļĨāļēāļĒāđ€āļ›āđ‡āļ™āļ›āļąāļāļŦāļēāđƒāļŦāļāđˆāļ—āļĩāđˆāļŠāđˆāļ‡āļœāļĨāļ•āđˆāļ­āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđāļĨāļ°āļ—āļąāđˆāļ§āđ‚āļĨāļāđ€āļ™āļ·āđˆāļ­āļ‡āļˆāļēāļāļ‚āļēāļ” āđāļ„āļĨāļ™āļ„āļ™āļ”āļđāđāļĨ āđ€āļžāļ·āđˆāļ­āļĒāļāļĢāļ°āļ”āļąāļšāļ„āļļāļ“āļ āļēāļžāļŠāļĩāļ§āļīāļ•āļ‚āļ­āļ‡āļœāļđāđ‰āļŠāļđāļ‡āļ­āļēāļĒāļļāđāļĨāļ°āļœāļđāđ‰āļžāļīāļāļēāļĢ āļˆāļķāļ‡āđ€āļĢāļīāđˆāļĄāļĄāļĩāļāļēāļĢāļžāļīāļˆāļēāļĢāļ“āļēāļ™āļģāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒ āļšāļĢāļīāļāļēāļĢāđ€āļžāļ·āđˆāļ­āļŠāļ™āļąāļšāļŠāļ™āļļāļ™āļ‡āļēāļ™āļšāđ‰āļēāļ™ āđ‚āļ”āļĒāđ€āļ‰āļžāļēāļ°āļ­āļĒāđˆāļēāļ‡āļĒāļīāđˆāļ‡āļāļēāļĢāļŠāđˆāļ‡āļŠāļīāđˆāļ‡āļ‚āļ­āļ‡āđƒāļŦāđ‰āđāļāđˆāļĄāļ™āļļāļĐāļĒāđŒāļ”āļąāļ‡āļ™āļąāđ‰āļ™āļ§āļīāļ—āļĒāļēāļ™āļīāļžāļ™āļ˜āđŒāļ™āļĩāđ‰āļˆāļķāļ‡ āļĄāļļāđˆāļ‡āđ€āļ™āđ‰āļ™āđ„āļ›āļ—āļĩāđˆāļāļēāļĢāļžāļąāļ’āļ™āļēāļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒ āđ‚āļ”āļĒāđ€āļĢāļīāđˆāļĄāļ•āđ‰āļ™āļĻāļķāļāļĐāļēāļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāđ€āļŠāļīāļ‡āļžāļĪāļ•āļīāļāļĢāļĢāļĄāđƒāļ™āļāļēāļĢ āļ›āļāļīāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒāļĢāļ°āļŦāļ§āđˆāļēāļ‡āļĄāļ™āļļāļĐāļĒāđŒāļāļąāļšāļĄāļ™āļļāļĐāļĒāđŒāļ—āļĩāđˆāļŠāļēāļĄāļēāļĢāļ–āļŠāđˆāļ‡āļ§āļąāļ•āļ–āļļāļĢāļ°āļŦāļ§āđˆāļēāļ‡āļāļąāļ™āđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āđ€āļ›āđ‡āļ™āļ˜āļĢāļĢāļĄāļŠāļēāļ•āļīāđāļĨāļ°āļ›āļĨāļ­āļ”āļ āļąāļĒ āđ‚āļ”āļĒāļāļēāļĢāļ—āļ”āļŠāļ­āļšāļāļēāļĢāļŠāđˆāļ‡āļ§āļąāļ•āļ–āļļāļĢāļ°āļŦāļ§āđˆāļēāļ‡āļĄāļ™āļļāļĐāļĒāđŒāļāļąāļšāļĄāļ™āļļāļĐāļĒāđŒāđ€āļšāļ·āđ‰āļ­āļ‡āļ•āđ‰āļ™ (Human-Human Handover : HHH) āđ€āļĢāļīāđˆāļĄāļˆāļēāļāļāļēāļĢāļĻāļķāļāļĐāļēāļĨāļąāļāļĐāļ“āļ°āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļāļēāļĢāļŠāđˆāļ‡āđāļšāļšāđ„āļ”āļ™āļēāļĄāļīāļāļ‚āļ­āļ‡āļœāļđāđ‰āđ€āļ‚āđ‰āļēāļĢāđˆāļ§āļĄāļāļēāļĢāļ—āļ”āļĨāļ­āļ‡āđƒāļ™ HHH āļœāļĨāļ—āļĩāđˆāđ„āļ”āđ‰ āļˆāļēāļāļāļēāļĢāļ—āļ”āļĨāļ­āļ‡āļŠāļēāļĄāļēāļĢāļ–āļ­āļ˜āļīāļšāļēāļĒāļžāļĪāļ•āļīāļāļĢāļĢāļĄāļāļēāļĢāļŠāđˆāļ‡āļ§āļąāļ•āļ–āļļāļ‚āļ­āļ‡āļĄāļ™āļļāļĐāļĒāđŒāļ­āļĒāđˆāļēāļ‡āļĨāļ°āđ€āļ­āļĩāļĒāļ”, āļĢāļđāļ›āđāļšāļšāđāļĢāļ‡āļ›āļŽāļīāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒ, āđ€āļ§āļĨāļēāđƒāļ™āļāļēāļĢāļŠāđˆāļ‡āļĄāļ­āļšāļ§āļąāļ•āļ–āļļ, āļ•āļģāđāļŦāļ™āđˆāļ‡āļāļēāļĢāļ–āđˆāļēāļĒāđ‚āļ­āļ™, āđāļĨāļ°āđāļšāļšāļˆāļģāļĨāļ­āļ‡āļ—āļēāļ‡āļ„āļ“āļīāļ•āļĻāļēāļŠāļ•āļĢāđŒāļ‚āļ­āļ‡āđāļ‚āļ™āļ‚āļ­āļ‡āļœāļđāđ‰āļŠāđˆāļ‡āļ‚āļ“āļ° āļŠāđˆāļ‡āļ§āļąāļ•āļ–āļļ āđ‚āļ”āļĒāļœāļĨāļˆāļēāļāļāļēāļĢāļĻāļķāļāļĐāļēāļāļēāļĢāļ•āļ­āļšāļŠāļ™āļ­āļ‡āļ•āđˆāļ­āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ‚āļ­āļ‡ HHH āļˆāļ°āļ™āļģāđ„āļ›āļŠāļđāđˆāļāļēāļĢāļ­āļ­āļāđāļšāļšāļāļĢāļ­āļš āđāļ™āļ§āļ„āļīāļ”āļ—āļĩāđˆāđ€āļŦāļĄāļēāļ°āļŠāļĄāļŠāļģāļŦāļĢāļąāļšāļĢāļ°āļšāļšāļ„āļ§āļšāļ„āļļāļĄāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļŠāļģāļŦāļĢāļąāļšāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļŠāđˆāļ‡āļ‚āļ­āļ‡āđƒāļŦāđ‰āļĄāļ™āļļāļĐāļĒāđŒ (Human-Robot Handover : HRH) āļ‡āļēāļ™āļ§āļīāļˆāļąāļĒāļ™āļĩāđ‰āļ™āļģāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļšāļĢāļīāļāļēāļĢāļ—āļĩāđˆāļĄāļĩāļŠāļ·āđˆāļ­āļ§āđˆāļē Human Support Robot (HSR) āđƒāļ™āļāļēāļĢ āļ—āļ”āļĨāļ­āļ‡ āđ‚āļ”āļĒāļĄāļĩāļˆāļļāļ”āļ›āļĢāļ°āļŠāļ‡āļ„āđŒāļ„āļ·āļ­āļ•āđ‰āļ­āļ‡āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāļžāļĪāļ•āļīāļāļĢāļĢāļĄāļāļēāļĢāļŠāđˆāļ‡āļ§āļąāļ•āļ–āļļāļ‚āļ­āļ‡āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāđƒāļŦāđ‰āļĄāļĩāļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ—āļĩāđˆ āđƒāļāļĨāđ‰āđ€āļ„āļĩāļĒāļ‡āļāļąāļšāļĄāļ™āļļāļĐāļĒāđŒ āļ”āđ‰āļ§āļĒāļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāđāļšāļšāļ­āļīāļĄāļžāļīāđāļ”āļ™āļ‹āđŒāļ—āļĩāđˆāđ€āļŦāļĄāļēāļ°āļŠāļģāļŦāļĢāļąāļšāļ„āļ§āļšāļ„āļļāļĄāļ•āļģāđāļŦāļ™āđˆāļ‡āļ‚āļ­āļ‡ HSR āļ—āļĩāđˆāļ‚āļķāđ‰āļ™āļ­āļĒāļđāđˆ āļāļąāļšāđāļĢāļ‡āļ›āļāļīāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒāļ‚āļ“āļ°āļ—āļĩāđˆāļ›āļāļīāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒāļāļąāļšāļĄāļ™āļļāļĐāļĒāđŒ āļ„āđˆāļēāļžāļēāļĢāļēāļĄāļīāđ€āļ•āļ­āļĢāđŒāļ­āļīāļĄāļžāļīāđāļ”āļ™āļ‹āđŒāļ—āļĩāđˆāđ€āļŦāļĄāļēāļ°āļŠāļĄāļ•āđˆāļ­āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄ āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļāļēāļĢāļŠāđˆāļ‡āļ§āļąāļ•āļ–āļļāļ‚āļ­āļ‡āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒ HSR āļ–āļđāļāļĢāļ°āļšāļļāđƒāļ™āļāļēāļĢāļ—āļ”āļĨāļ­āļ‡ āđ‚āļ”āļĒāļœāļĨāļˆāļēāļāļāļēāļĢāļ—āļ”āļĨāļ­āļ‡āđāļĨāļ°āļāļēāļĢāļĒāļ­āļĄāļĢāļąāļš āļˆāļēāļāļœāļđāđ‰āđ€āļ‚āđ‰āļēāļĢāđˆāļ§āļĄāļāļēāļĢāļ—āļ”āļĨāļ­āļ‡āļžāļšāļ§āđˆāļē āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāđāļšāļšāļ­āļīāļĄāļžāļīāđāļ”āļ™āļ‹āđŒāļŠāļēāļĄāļēāļĢāļ–āļ„āļ§āļšāļ„āļļāļĄāđƒāļŦāđ‰āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļĄāļĩāļžāļĪāļ•āļīāļāļĢāļĢāļĄāļāļēāļĢ āļŠāđˆāļ‡āļ§āļąāļ•āļ–āļļāļ—āļĩāđˆāđƒāļāļĨāđ‰āđ€āļ„āļĩāļĒāļ‡āļāļąāļšāļĄāļ™āļļāļĐāļĒāđŒāđ„āļ”āđ‰āļ”āļąāļ‡āļ™āļąāđ‰āļ™āļ‡āļēāļ™āļ§āļīāļˆāļąāļĒāļ™āļĩāđ‰āļāļĨāđˆāļēāļ§āđ„āļ”āđ‰āļ§āđˆāļēāļŠāļēāļĄāļēāļĢāļ–āļ—āļģāđƒāļŦāđ‰āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒHSR āļŠāļēāļĄāļēāļĢāļ–āļŠāđˆāļ‡āļ§āļąāļ•āļ–āļļ āđƒāļŦāđ‰āđāļāđˆāļĄāļ™āļļāļĐāļĒāđŒāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āđ€āļ›āđ‡āļ™āļ˜āļĢāļĢāļĄāļŠāļēāļ•āļī āđāļĨāļ°āļ›āļĨāļ­āļ”āļ āļą

    āļ­āļīāļ—āļ˜āļīāļžāļĨāļ‚āļ­āļ‡āļ„āļ§āļēāļĄāļ„āļĨāđ‰āļēāļĒāļ„āļĨāļķāļ‡āđ€āļŠāļīāļ‡āļĢāļđāļ›āļĨāļąāļāļĐāļ“āđŒāđāļĨāļ°āļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāđ„āļ”āđ‰āļ—āļĩāđˆāļĄāļĩāļœāļĨāļ•āđˆāļ­āļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļ„āļ§āļēāļĄāđ€āļŦāļĄāļ·āļ­āļ™āļĄāļ™āļļāļĐāļĒāđŒ āļ„āļ§āļēāļĄāđ€āļŠāļ·āđˆāļ­āđƒāļˆ āđāļĨāļ°āļāļēāļĢāļĒāļ­āļĄāļĢāļąāļšāļ•āđˆāļ­āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒ

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    āļ‡āļēāļ™āļ§āļīāļˆāļąāļĒāļ™āļĩāđ‰āļĄāļĩāļˆāļļāļ”āļ›āļĢāļ°āļŠāļ‡āļ„āđŒāđ€āļžāļ·āđˆāļ­āļĻāļķāļāļĐāļēāļ­āļīāļ—āļ˜āļīāļžāļĨāļ‚āļ­āļ‡āļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļ„āļ§āļēāļĄāđ€āļŦāļĄāļ·āļ­āļ™āļĄāļ™āļļāļĐāļĒāđŒāļ—āļĩāđˆāļĄāļĩāļ•āđˆāļ­āļ„āļ§āļēāļĄāđ„āļ§āđ‰āļ§āļēāļ‡āđƒāļˆāđāļĨāļ°āļāļēāļĢāļĒāļ­āļĄāļĢāļąāļšāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļ•āļēāļĄāđāļ™āļ§āļ„āļīāļ”āļ—āļĪāļĐāļŽāļĩ S-E-E-K āļ—āļĩāđˆāļ™āļģāļĄāļēāđƒāļŠāđ‰āļŠāļĢāđ‰āļēāļ‡āļāļĢāļ­āļšāđāļ™āļ§āļ„āļīāļ”āļŦāļĨāļąāļāđƒāļ™āļāļēāļĢāļ§āļīāļˆāļąāļĒāļ™āļĩāđ‰ āđ‚āļ”āļĒāļĄāļĩāļ›āļąāļˆāļˆāļąāļĒāļ—āļēāļ‡āļ”āđ‰āļēāļ™āļ„āļ§āļēāļĄāļ„āļĨāđ‰āļēāļĒāļ„āļĨāļķāļ‡āđ€āļŠāļīāļ‡āļĢāļđāļ›āļĨāļąāļāļĐāļ“āđŒāđ€āļ›āđ‡āļ™āļ•āļąāļ§āđāļ›āļĢāļ•āđ‰āļ™ āļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāđ„āļ”āđ‰āđ€āļ›āđ‡āļ™āļ•āļąāļ§āđāļ›āļĢāļāļģāļāļąāļš āđāļĨāļ°āđāļĢāļ‡āļˆāļđāļ‡āđƒāļˆāļ—āļēāļ‡āļŠāļąāļ‡āļ„āļĄāđ€āļ›āđ‡āļ™āļ•āļąāļ§āđāļ›āļĢāļ„āļ§āļšāļ„āļļāļĄ āļāļĨāļļāđˆāļĄāļ•āļąāļ§āļ­āļĒāđˆāļēāļ‡ āļ„āļ·āļ­ āļ™āļīāļŠāļīāļ• āļˆāļģāļ™āļ§āļ™ 200 āļ„āļ™ āļ­āļēāļĒāļļāļĢāļ°āļŦāļ§āđˆāļēāļ‡ 18-25 āļ›āļĩ āđƒāļŠāđ‰āļāļēāļĢāļŠāļļāđˆāļĄāļ­āļĒāđˆāļēāļ‡āđ€āļ›āđ‡āļ™āļĢāļ°āļšāļšāļĢāđˆāļ§āļĄāļāļąāļšāļāļēāļĢāļŠāļļāđˆāļĄāļ­āļĒāđˆāļēāļ‡āļ‡āđˆāļēāļĒāđ€āļ‚āđ‰āļēāļŦāļ™āļķāđˆāļ‡āđƒāļ™ 4 āđ€āļ‡āļ·āđˆāļ­āļ™āđ„āļ‚ āđ‚āļ”āļĒāđƒāļŦāđ‰āļœāļđāđ‰āđ€āļ‚āđ‰āļēāļĢāđˆāļ§āļĄāļāļēāļĢāļ§āļīāļˆāļąāļĒāļ”āļđāļĢāļđāļ›āļ āļēāļžāđāļĨāļ°āļ­āđˆāļēāļ™āļ‚āđ‰āļ­āļ„āļ§āļēāļĄāļ„āļļāļ“āļŠāļĄāļšāļąāļ•āļīāļ‚āļ­āļ‡āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļ—āļĩāđˆāļĄāļĩāļāļēāļĢāļˆāļąāļ”āļāļĢāļ°āļ—āļģāđƒāļŦāđ‰āļĄāļĩāļ„āļ§āļēāļĄāļ„āļĨāđ‰āļēāļĒāļ„āļĨāļķāļ‡āļĄāļ™āļļāļĐāļĒāđŒāđāļĨāļ°āļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ—āļĩāđˆāļ„āļēāļ”āđ€āļ”āļē/āļ„āļ§āļšāļ„āļļāļĄāđ„āļ”āđ‰āļ‚āļ­āļ‡āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļ—āļĩāđˆāđāļ•āļāļ•āđˆāļēāļ‡āļāļąāļ™āđƒāļ™āđāļ•āđˆāļĨāļ°āđ€āļ‡āļ·āđˆāļ­āļ™āđ„āļ‚ āļˆāļēāļāļ™āļąāđ‰āļ™āļ•āļ­āļšāđāļšāļšāļŠāļ­āļšāļ–āļēāļĄāļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļ„āļ§āļēāļĄāđ€āļŦāļĄāļ·āļ­āļ™āļĄāļ™āļļāļĐāļĒāđŒ āļ„āļ§āļēāļĄāđ„āļ§āđ‰āļ§āļēāļ‡āđƒāļˆāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļāļēāļĢāļĒāļ­āļĄāļĢāļąāļšāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒ āļœāļĨāļˆāļēāļāļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāđ€āļŠāđ‰āļ™āļ—āļēāļ‡āļžāļšāļ§āđˆāļē āļ„āļ§āļēāļĄāļ„āļĨāđ‰āļēāļĒāļ„āļĨāļķāļ‡āđ€āļŠāļīāļ‡āļĢāļđāļ›āļĨāļąāļāļĐāļ“āđŒāļĄāļĩāļœāļĨāļ•āđˆāļ­āļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļ„āļ§āļēāļĄāđ€āļŦāļĄāļ·āļ­āļ™āļĄāļ™āļļāļĐāļĒāđŒāļ—āļĩāđˆāļĄāļĩāļ•āđˆāļ­āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļ­āļĒāđˆāļēāļ‡āļĄāļĩāļ™āļąāļĒāļŠāļģāļ„āļąāļāļ—āļēāļ‡āļŠāļ–āļīāļ•āļī āđ‚āļ”āļĒāđƒāļ™āđ€āļ‡āļ·āđˆāļ­āļ™āđ„āļ‚āļ—āļĩāđˆāļĄāļĩāļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāđāļĨāļ°āļ„āļēāļ”āđ€āļ”āļēāđ„āļĄāđˆāđ„āļ”āđ‰āļ—āļģāđƒāļŦāđ‰āļ­āļīāļ—āļ˜āļīāļžāļĨāļ‚āļ­āļ‡āļ„āļ§āļēāļĄāļ„āļĨāđ‰āļēāļĒāļ„āļĨāļķāļ‡āđ€āļŠāļīāļ‡āļĢāļđāļ›āļĨāļąāļāļĐāļ“āđŒāļ—āļĩāđˆāļĄāļĩāļ•āđˆāļ­āļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļ„āļ§āļēāļĄāđ€āļŦāļĄāļ·āļ­āļ™āļĄāļ™āļļāļĐāļĒāđŒāđ€āļžāļīāđˆāļĄāļĄāļēāļāļ‚āļķāđ‰āļ™ āļĒāļīāđˆāļ‡āđ„āļ›āļāļ§āđˆāļēāļ™āļąāđ‰āļ™āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļ—āļĩāđˆāļĄāļĩāļ„āļ§āļēāļĄāļ„āļĨāđ‰āļēāļĒāļ„āļĨāļķāļ‡āļĄāļ™āļļāļĐāļĒāđŒāļŠāļđāļ‡ āđāļĨāļ°āļšāļļāļ„āļ„āļĨāđ„āļĄāđˆāļŠāļēāļĄāļēāļĢāļ–āļ„āļ§āļšāļ„āļļāļĄāļŦāļĢāļ·āļ­āļ„āļēāļ”āđ€āļ”āļēāļžāļĪāļ•āļīāļāļĢāļĢāļĄāļ‚āļ­āļ‡āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāđ„āļ”āđ‰ āļ—āļģāđƒāļŦāđ‰āļšāļļāļ„āļ„āļĨāļĢāļđāđ‰āļŠāļķāļāļ§āđˆāļēāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļĄāļĩāļ„āļ§āļēāļĄāđ€āļŦāļĄāļ·āļ­āļ™āļĄāļ™āļļāļĐāļĒāđŒāļĄāļēāļāļ‚āļķāđ‰āļ™ āļ‹āļķāđˆāļ‡āļŠāđˆāļ‡āļœāļĨāļ•āđˆāļ­āļ„āļ§āļēāļĄāđ„āļ§āđ‰āļ§āļēāļ‡āđƒāļˆāļĢāļ§āļĄāļ–āļķāļ‡āļāļēāļĢāļĒāļ­āļĄāļĢāļąāļšāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļ„āļģāļŠāļģāļ„āļąāļ: āļ—āļĪāļĐāļŽāļĩ S-E-E-K  āļ„āļ§āļēāļĄāļ„āļĨāđ‰āļēāļĒāļ„āļĨāļķāļ‡āđ€āļŠāļīāļ‡āļĢāļđāļ›āļĨāļąāļāļĐāļ“āđŒ  āļāļēāļĢāļĢāļąāļšāļĢāļđāđ‰āļāļēāļĢāļ„āļ§āļšāļ„āļļāļĄāđ„āļ”āđ‰  āļ„āļ§āļēāļĄāđ€āļŦāļĄāļ·āļ­āļ™āļĄāļ™āļļāļĐāļĒāđŒÂ  āļ„āļ§āļēāļĄāđ„āļ§āđ‰āļ§āļēāļ‡āđƒāļˆ  āļāļēāļĢāļĒāļ­āļĄāļĢāļąāļš  āļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒThis research aimed to investigate the effect of perceived anthropomorphism toward trust and acceptance in robots based on S-E-E-K theory; physical appearance similarity as independent variable, perceived of controllability as moderator and social motivation as controlled variable. Sample of 200 undergraduate and postgraduate students, aged between 18-25 years old were systematic and simple randomly assigned to one out of four conditions which were manipulated by a picture and a short description of the robot. The robots of each condition were designed to have different appearance (humanlike and not humanlike) and also behavior (predicted/controlled and not predicted/controlled). Afterward, participants completed the perceived anthropomorphism, trust in robot, acceptance in robot questionnaires. Results from Paths analysis showed that physical appearance similarity had relationship with a statistically significant on anthropomorphism. The effect of physical appearance similarity increased in the condition of unpredicted and uncontrollable robot. Furthermore, robot with highly humanlike appearance with unpredicted and uncontrolled behavior had the effect on participants’ feeling and it also increased trust and acceptance toward robots.Keywords: S-E-E-K Theory, Physical Appearance Similarity, Controllability, Anthropomorphism, Trust, Acceptance, Robot

    āļāļēāļĢāļ›āļĢāļ°āļĒāļļāļāļ•āđŒāđƒāļŠāđ‰āđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļ§āļąāļ”āļ„āļĨāļ·āđˆāļ™āđ„āļŸāļŸāđ‰āļēāļŠāļĄāļ­āļ‡āđāļšāļšāļžāļāļžāļēāđƒāļ™āļāļēāļĢāļ§āļąāļ”āļ„āļ§āļēāļĄāļ„āļīāļ”āļŠāļĢāđ‰āļēāļ‡āļŠāļĢāļĢāļ„āđŒāļ‚āļ­āļ‡āļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™āļ—āļĩāđˆāđ€āļĢāļĩāļĒāļ™āļĢāļđāđ‰āļ”āđ‰āļ§āļĒāļāļīāļˆāļāļĢāļĢāļĄāļŠāļ°āđ€āļ•āđ‡āļĄāđāļšāļšāđ€āļ›āļīāļ”āđāļĨāļ°āđāļšāļšāļĄāļĩāđ‚āļ„āļĢāļ‡āļŠāļĢāđ‰āļēāļ‡

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    The Application of Portable Electroencephalography Device to Measure Learners’ Creative Thinking when Learning with Structured and Open STEM Activities Suthida Chamrat āļĢāļąāļšāļšāļ—āļ„āļ§āļēāļĄ: 28 āļāļļāļĄāļ āļēāļžāļąāļ™āļ˜āđŒ 2563; āđāļāđ‰āđ„āļ‚āļšāļ—āļ„āļ§āļēāļĄ: 24 āļžāļĪāļĐāļ āļēāļ„āļĄ 2563; āļĒāļ­āļĄāļĢāļąāļšāļ•āļĩāļžāļīāļĄāļžāđŒ: 29 āļžāļĪāļĐāļ āļēāļ„āļĄ 2563DOI: http://doi.org/10.14456/jstel.2020.2 āļšāļ—āļ„āļąāļ”āļĒāđˆāļ­āļāļēāļĢāļ§āļīāļˆāļąāļĒāđƒāļ™āļ„āļĢāļąāđ‰āļ‡āļ™āļĩāđ‰āļĻāļķāļāļĐāļēāļāļēāļĢāļ™āļģāļ„āļ§āļēāļĄāļāđ‰āļēāļ§āļŦāļ™āđ‰āļēāļ‚āļ­āļ‡āļ§āļīāļ—āļĒāļēāļāļēāļĢāļ›āļĢāļ°āļŠāļēāļ—āļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāđŒ āđ‚āļ”āļĒāļāļēāļĢāđƒāļŠāđ‰āļ­āļļāļ›āļāļĢāļ“āđŒāļ§āļąāļ”āļ„āļĨāļ·āđˆāļ™āđ„āļŸāļŸāđ‰āļēāļŠāļĄāļ­āļ‡ (EEG) āđāļšāļšāļžāļāļžāļē āđ€āļžāļ·āđˆāļ­āļ™āļģāļĄāļēāļ§āļąāļ”āļŠāļ āļēāļ§āļ°āļāļēāļĢāļ„āļīāļ”āļŠāļĢāđ‰āļēāļ‡āļŠāļĢāļĢāļ„āđŒāļ‚āļ­āļ‡āļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™āđƒāļ™āļ‚āļ“āļ°āļ”āļģāđ€āļ™āļīāļ™āļāļīāļˆāļāļĢāļĢāļĄāļāļēāļĢāđ€āļĢāļĩāļĒāļ™āļĢāļđāđ‰āļ•āļēāļĄāđāļ™āļ§āļŠāļ°āđ€āļ•āđ‡āļĄāļĻāļķāļāļĐāļēāđāļšāļšāđ€āļ›āļīāļ”āđāļĨāļ°āđāļšāļšāļĄāļĩāđ‚āļ„āļĢāļ‡āļŠāļĢāđ‰āļēāļ‡ āđ‚āļ”āļĒāđ€āļāđ‡āļšāļ‚āđ‰āļ­āļĄāļđāļĨāļ§āļīāļˆāļąāļĒāļˆāļēāļāļžāļĨāļ§āļīāļˆāļąāļĒāļ‹āļķāđˆāļ‡āđ€āļ›āđ‡āļ™āļ­āļēāļŠāļēāļŠāļĄāļąāļ„āļĢāļˆāļģāļ™āļ§āļ™ 12 āļ„āļ™ āļŦāļĨāļąāļ‡āļˆāļēāļāļ—āļĩāđˆāđ„āļ”āđ‰āļĢāļąāļšāļāļēāļĢāļ­āļ™āļļāļĄāļąāļ•āļīāļˆāļēāļāļ„āļ“āļ°āļāļĢāļĢāļĄāļāļēāļĢāļˆāļĢāļīāļĒāļ˜āļĢāļĢāļĄāļāļēāļĢāļ§āļīāļˆāļąāļĒāđƒāļ™āļ„āļ™ āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāđ€āļŠāļĩāļĒāļ‡āđƒāļŦāļĄāđˆ āļžāļĨāļ§āļīāļˆāļąāļĒāđ„āļ”āđ‰āđ€āļ‚āđ‰āļēāļĢāđˆāļ§āļĄāļāļīāļˆāļāļĢāļĢāļĄāļŠāļ°āđ€āļ•āđ‡āļĄāļ—āļąāđ‰āļ‡āļŠāļ­āļ‡āļāļīāļˆāļāļĢāļĢāļĄ āļ—āļĩāđˆāļ›āļĢāļ°āļāļ­āļšāļ”āđ‰āļ§āļĒāļāļīāļˆāļāļĢāļĢāļĄāļāļēāļĢāļŸāļąāļ‡āļšāļĢāļĢāļĒāļēāļĒāļˆāļēāļāļœāļđāđ‰āļŠāļ­āļ™ āļāļēāļĢāļ”āļđāļ§āļīāļ”āļīāļ—āļąāļĻāļ™āđŒāļˆāļēāļāļĒāļđāļ—āļđāļ› āđāļĨāļ°āļāļēāļĢāļĨāļ‡āļĄāļ·āļ­āļ›āļāļīāļšāļąāļ•āļī āļ„āļĨāļ·āđˆāļ™āđ„āļŸāļŸāđ‰āļēāļŠāļĄāļ­āļ‡āļˆāļ°āļ–āļđāļāļ§āļąāļ”āđ‚āļ”āļĒāđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļŠāļ§āļĄāļĻāļĩāļĢāļĐāļ° Muse āļ—āļĩāđˆāļĄāļĩ 4 āļ­āļīāđ€āļĨāđ‡āļāđ‚āļ—āļĢāļ” āđ„āļ”āđ‰āđāļāđˆ AF7  AF8  TP9 āđāļĨāļ° TP10 āđ‚āļ”āļĒāļĻāļķāļāļĐāļēāļ§āļīāļ˜āļĩāļāļēāļĢāđƒāļŠāđ‰āļ‡āļēāļ™āđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļ§āļąāļ”āļ„āļĨāļ·āđˆāļ™āđ„āļŸāļŸāđ‰āļēāļŠāļĄāļ­āļ‡āđāļšāļšāđ€āļ„āļĨāļ·āđˆāļ­āļ™āļ—āļĩāđˆāļ—āļĩāđˆāļ§āļąāļ”āđāļĨāļ°āļŠāđˆāļ‡āļ„āļĨāļ·āđˆāļ™āļŠāļąāļāļāļēāļ™āđ„āļ›āļĒāļąāļ‡āļ­āļļāļ›āļāļĢāļ“āđŒāļĢāļąāļšāļŠāļąāļāļāļēāļ“ Bluetooth 2 āļĢāļđāļ›āđāļšāļš āļ„āļ·āļ­ 1) āļāļēāļĢāļŠāļ•āļĢāļĩāļĄāļ‚āđ‰āļ­āļĄāļđāļĨāđ„āļ›āļĒāļąāļ‡āđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļ„āļ­āļĄāļžāļīāļ§āđ€āļ•āļ­āļĢāđŒāļœāđˆāļēāļ™āđāļ­āļ›āļžāļĨāļīāđ€āļ„āļŠāļąāļ™ Muse Direct āđƒāļ™āļĢāļđāļ›āđāļšāļšāđ„āļŸāļĨāđŒāļ™āļēāļĄāļŠāļāļļāļĨ .Muse āļ‹āļķāđˆāļ‡āđāļŠāļ”āļ‡āļœāļĨāđāļšāļš real–time āļœāđˆāļēāļ™āđ‚āļ›āļĢāđāļāļĢāļĄ Neuro visual āđāļĨāļ° 2) āļāļēāļĢāļŠāļ•āļĢāļĩāļĄāļ‚āđ‰āļ­āļĄāļđāļĨāđ„āļ›āļĒāļąāļ‡āđ‚āļ—āļĢāļĻāļąāļžāļ—āđŒāļĄāļ·āļ­āļ–āļ·āļ­āļœāđˆāļēāļ™āđāļ­āļ›āļžāļĨāļīāđ€āļ„āļŠāļąāļ™ Mind Monitor āļ‹āļķāđˆāļ‡āđ€āļŠāļ·āđˆāļ­āļĄāļ•āđˆāļ­āđāļĨāļ°āđ€āļāđ‡āļšāļ‚āđ‰āļ­āļĄāļđāļĨāđ€āļ‚āđ‰āļēāļĢāļ°āļšāļšāļ„āļĨāļēāļ§āļ”āđŒāļ‚āļ­āļ‡ Dropbox āđ‚āļ”āļĒāļ­āļąāļ•āđ‚āļ™āļĄāļąāļ•āļī āđƒāļ™āļĢāļđāļ›āđāļšāļš CVS āļœāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāļžāļšāļ§āđˆāļēāļ§āļīāļ˜āļĩāļāļēāļĢāļ—āļĩāđˆ 2 āļŠāļ°āļ”āļ§āļāđāļĨāļ°āđƒāļŦāđ‰āļ‚āđ‰āļ­āļĄāļđāļĨāļ—āļĩāđˆāđ€āļŠāļ–āļĩāļĒāļĢāļĄāļēāļāļāļ§āđˆāļē āļŠāļēāļĄāļēāļĢāļ–āļ™āļģāļ‚āđ‰āļ­āļĄāļđāļĨāđ„āļ›āđƒāļŠāđ‰āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļœāļĨāđ„āļ”āđ‰āđ€āļĨāļĒ āđƒāļ™āļ‚āļ“āļ°āļ—āļĩāđˆāđāļšāļšāļ—āļĩāđˆ 1 āļ‚āđ‰āļ­āļĄāļđāļĨāļ™āļēāļĄāļŠāļāļļāļĨ .Muse āļ•āđ‰āļ­āļ‡āļ™āļģāđ„āļ›āđāļ›āļĨāļ‡āđ„āļŸāļĨāđŒāđāļĨāļ°āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ”āđ‰āļ§āļĒāđ‚āļ›āļĢāđāļāļĢāļĄ Matlab āļ—āļĩāđˆāļ‹āļąāļšāļ‹āđ‰āļ­āļ™āđāļĨāļ°āļ•āđ‰āļ­āļ‡āđƒāļŠāđ‰āļ„āļ§āļēāļĄāđ€āļŠāļĩāđˆāļĒāļ§āļŠāļēāļāđƒāļ™āļāļēāļĢāđ€āļ‚āļĩāļĒāļ™āļ„āļģāļŠāļąāđˆāļ‡ āļœāļĨāļˆāļēāļāļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ‚āđ‰āļ­āļĄāļđāļĨāđ‚āļ”āļĒ Mind Monitor Graphing āđāļšāļšāļ­āļ­āļ™āđ„āļĨāļ™āđŒ āđāļŠāļ”āļ‡āđƒāļŦāđ‰āđ€āļŦāđ‡āļ™āļŠāļ āļēāļ§āļ°āļāļēāļĢāļ—āļģāļ‡āļēāļ™āļ‚āļ­āļ‡āļŠāļĄāļ­āļ‡āđāļ•āļāļ•āđˆāļēāļ‡āļāļąāļ™āđ„āļ›āļ•āļēāļĄāļāļīāļˆāļāļĢāļĢāļĄāļ—āļĩāđˆāļ—āļģ āđ‚āļ”āļĒāļāļēāļĢāļ—āļģāļāļīāļˆāļāļĢāļĢāļĄāļŠāļ°āđ€āļ•āđ‡āļĄāđāļšāļšāļĄāļĩāđ‚āļ„āļĢāļ‡āļŠāļĢāđ‰āļēāļ‡ āđƒāļ™āļŠāđˆāļ§āļ‡āļāļēāļĢāļ­āļ­āļāđāļšāļšāđƒāļŦāđ‰āļ„āļĨāļ·āđˆāļ™āđ„āļŸāļŸāđ‰āļēāļŠāļĄāļ­āļ‡āļŠāđˆāļ§āļ‡āđāļ­āļĨāļŸāļē (āļ„āļ§āļēāļĄāļ–āļĩāđˆ 8–12 Hz) āđ€āļ‰āļĨāļĩāđˆāļĒāļŠāļđāļ‡āļāļ§āđˆāļēāļāļīāļˆāļāļĢāļĢāļĄāļŠāļ°āđ€āļ•āđ‡āļĄāđāļšāļšāđ€āļ›āļīāļ” āđāļĨāļ°āļĨāļ”āļĨāļ‡āļ•āđˆāļģāļŠāļļāļ”āđƒāļ™āļŠāđˆāļ§āļ‡āļāļēāļĢāļŸāļąāļ‡āļšāļĢāļĢāļĒāļēāļĒ (71.637) āđ€āļĄāļ·āđˆāļ­āļžāļīāļˆāļēāļĢāļ“āļēāļ„āļ§āļēāļĄāļŠāļĄāļĄāļēāļ•āļĢāļ‚āļ­āļ‡āļ„āļĨāļ·āđˆāļ™āļ­āļąāļĨāļŸāļēāđƒāļ™āļŠāļĄāļ­āļ‡āļ‹āļĩāļāļ‚āļ§āļēāđāļĨāļ°āļ‹āļĩāļāļ‹āđ‰āļēāļĒ āļžāļšāļ§āđˆāļē āļāļīāļˆāļāļĢāļĢāļĄāļŠāļ°āđ€āļ•āđ‡āļĄāđāļšāļšāđ€āļ›āļīāļ”āđƒāļŦāđ‰āļ„āļĨāļ·āđˆāļ™āđāļ­āļĨāļŸāļēāđƒāļ™āļŠāļĄāļ­āļ‡āļ‹āļĩāļāļ‚āļ§āļēāļĄāļēāļāļāļ§āđˆāļēāļ‹āļĩāļāļ‹āđ‰āļēāļĒāļ­āļĒāđˆāļēāļ‡āļŠāļąāļ”āđ€āļˆāļ™ (āļŠāđˆāļ§āļ™āļ•āđˆāļēāļ‡āļŦāļĢāļ·āļ­āļ­āļŠāļĄāļĄāļēāļ•āļĢ = 11.160)āļ„āļģāļŠāļģāļ„āļąāļ: āļāļīāļˆāļāļĢāļĢāļĄāļŠāļ°āđ€āļ•āđ‡āļĄ  āļ§āļīāļ˜āļĩāļāļēāļĢāļšāļąāļ™āļ—āļķāļāļ„āļĨāļ·āđˆāļ™āđ„āļŸāļŸāđ‰āļēāđƒāļ™āļŠāļĄāļ­āļ‡  āļ›āļĢāļ°āļŠāļēāļ—āļ§āļīāļ—āļĒāļēāļĻāļēāļŠāļ•āļĢāđŒÂ AbstractThis research explored the utilization of neuroscience technology using portable electroencephalography (EEG) devices to measure the state of students’ creative thinking during their performance of STEM activities and structured and open STEM activities. After obtaining Institutional Review Board approval, 12 students who voluntarily participated in this study were assigned to engage in two STEM activities consisting of listening to lectures, watching YouTube videos, and engaging in hands–on activities. Participants were measured for their creative thinking using the EEG Muse Headband while they were performing the tasks. The Muse headband transmitted brain signals collected by four electrodes in areas of AF7, AF8, TP9 and TP10 to mobile equipment via Bluetooth in 2 methods: 1) streaming data to a computer via the Muse Direct application in the Muse file format, which is displayed in real–time by Neuro visual program, and 2) streaming data to mobile phones via the Mind Monitor application, which connects and stores data automatically in Cloud Storage with Dropbox in CVS format. The results indicated that the second method is more convenient and gives a stable, ready to analyze data. The first method, the file in *.Muse format must be converted before analyzed by Matlab, which is more complicated and requires expertise in writing commands. The results of the online data analysis by Mind Monitor Graphing show the brain wave conditions vary according to the activity. In the structured STEM activity, the alpha band (8–12 Hz) showed that creative thinking was higher than open STEM activity. The alpha brain wave was lowest during the lecture sessions. When considering the alpha wave’s symmetry in the right and left hemisphere, open STEM activity is giving the alpha waves in the right hemisphere than the left hemisphere (difference or asymmetry = 11.160).Keywords: STEM activity, Electroencephalography, Neuroscience

    āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļŦāļļāđˆāļ™āļĒāļ™āļ•āđŒāļ‚āļ™āļēāļ”āđ„āļĄāđ‚āļ„āļĢāđ€āļĄāļ•āļĢāļŦāļĢāļ·āļ­āļ™āļēāđ‚āļ™āđ€āļĄāļ•āļĢāđ€āļžāļ·āđˆāļ­āđƒāļŠāđ‰āļ—āļēāļ‡āļāļēāļĢāđāļžāļ—āļĒāđŒāđāļĨāļ°āđ€āļ āļŠāļąāļŠāļāļĢāļĢāļĄ Micro or Nano-robotic Technology for Medical and Pharmaceutical Applications

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    Abstract Nowadays the development of robots in medicine or pharmaceutical applications is important for disease diagnosis and drug delivery system. The goal of this study is to increase the efficiency of diagnosis or treatment to facilitate drug delivery and reduce the side effects of traditional treatment. Most designed robotic technology delivers the machine into an area where the disease or disorder occur which the tiny robots as micro and nano-scale are required using complex designs with different technologies including mechanical and chemical procedures. Keywords: robotic technology, micrometer, nanometer, medical, pharmaceutica

    āļāļēāļĢāļžāļąāļ’āļ™āļēāđ‚āļĄāļ”āļđāļĨāļāļēāļĢāļāļķāļ āđ€āļĢāļ·āđˆāļ­āļ‡āļĢāļ°āļšāļšāļ™āļīāļ§āđ€āļĄāļ•āļīāļāļžāļ·āđ‰āļ™āļāļēāļ™ āļŠāđāļēāļŦāļĢāļąāļšāđ‚āļĢāļ‡āđ€āļĢāļĩāļĒāļ™āļŠāđˆāļēāļ‡āļ™āļ­āļāļĢāļ°āļšāļš

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    The objectives of this research were to: 1) develop the training module on basic pneumatic system for non-formal vocational education and 2) conduct the follow-up study of the trainees in their workplaces. The samples in this study include 85 students from Phradabos School in the field of Industrial Technician of batch 42. The research procedures were as follows: (1) developing training module, (2) defining learning model, (3) implementing the training, (4) conducting the follow-up study of the trainees’ performance, (5) defining the trainer’s qualification, and (6) defining the trainees’ qualification. The Instruments used in the research consisted of (1) training module, (2) evaluation form for the suitability of the training module, and (3) evaluation form of training in the workplace. Data analysis using statistics (1) percentage, (2) mean, and (3) standard deviation. The results of the research revealed that: 1) The training module on basic pneumatic system for non-formal vocational education contains the summary of necessary contents for completing the exercises and practicing on the worksheets. The training module also contains clear description with illustrations, exercises for testing and worksheets for the trainers to follow and practice on pneumatic circuit connection. There are also experimental parts with experimental records to explain the operation of each circuit. At the end of each worksheet was equipped with quizzes. The appropriateness training module evaluated by 5 experts was at good level. The average training achievement was 71.78% with the knowledge aspect achievement of 66.70% and 76.86% on the skill achievement. 2) The results of the follow-up study on 4 trainees at their enterprises show that the average achievement is 86.21% with details of each aspect as follows: 90% on personal characteristics, 82.75% on knowledge and skills, 87.75% on duty responsibility, and work achievement at 84.37%

    āļāļēāļĢāļžāļąāļ’āļ™āļēāļŸāļēāļĢāđŒāļĄāđ„āļāđˆāđ„āļ‚āđˆāđāļšāļšāļŠāļĄāļēāļĢāđŒāļ•āļšāļ™āļžāļ·āđ‰āļ™āļāļēāļ™āļ•āļĢāļĢāļāļĻāļēāļŠāļ•āļĢāđŒāļ„āļĨāļļāļĄāđ€āļ„āļĢāļ·āļ­āđāļĨāļ°āļĢāļēāļŠāļžāđŒāđ€āļšāļ­āļĢāđŒāļĢāļĩāđˆāđ„āļž

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    The Development of a Laying Hen Smart Farm Based on Fuzzy Logic and Raspberry Pi Pitak Jitsamran, Sooksawaddee Nattawuttisit and Thepparit BanditwattanawongāļĢāļąāļšāļšāļ—āļ„āļ§āļēāļĄ: 17 āļĄāļāļĢāļēāļ„āļĄ 2560; āļĒāļ­āļĄāļĢāļąāļšāļ•āļĩāļžāļīāļĄāļžāđŒ: 18 āļžāļĪāļĻāļˆāļīāļāļēāļĒāļ™ 2560DOI: http://doi.org/10.14456/jstel.2017.23 āļšāļ—āļ„āļąāļ”āļĒāđˆāļ­āļšāļ—āļ„āļ§āļēāļĄāļ™āļĩāđ‰āļ™āļģāđ€āļŠāļ™āļ­āļāļēāļĢāļžāļąāļ’āļ™āļēāļĢāļ°āļšāļšāļŸāļēāļĢāđŒāļĄāđ„āļāđˆāđ„āļ‚āđˆāđāļšāļšāļŠāļĄāļēāļĢāđŒāļ•āđ€āļžāļ·āđˆāļ­āļŠāđˆāļ§āļĒāđ€āļŦāļĨāļ·āļ­āđ€āļāļĐāļ•āļĢāļāļĢāđ‚āļ”āļĒ āđ€āļ‰āļžāļēāļ°āļœāļđāđ‰āđ€āļĨāļĩāđ‰āļĒāļ‡āļ­āļīāļŠāļĢāļ°āļˆāļēāļāļ—āļąāđ‰āļ‡āļŸāļēāļĢāđŒāļĄāļ‚āļ™āļēāļ”āļāļĨāļēāļ‡āđāļĨāļ°āļ‚āļ™āļēāļ”āđ€āļĨāđ‡āļāļ—āļĩāđˆāļ›āļĢāļ°āļŠāļšāļ›āļąāļāļŦāļēāļŠāļ āļēāļ§āļ°āļāļēāļĢāļ‚āļēāļ”āļ—āļļāļ™āļ—āļĩāđˆāđ€āļāļīāļ”āļˆāļēāļāļœāļĨāļīāļ•āļ āļēāļžāļ•āļāļ•āđˆāļģāđ€āļžāļĢāļēāļ°āđ„āļĄāđˆāļŠāļēāļĄāļēāļĢāļ–āļ„āļ§āļšāļ„āļļāļĄāļŠāļ āļēāļžāđāļ§āļ”āļĨāđ‰āļ­āļĄāļ āļēāļĒāđƒāļ™āļŸāļēāļĢāđŒāļĄāļ•āļēāļĄāđāļ™āļ§āļ›āļāļīāļšāļąāļ•āļīāļ—āļĩāđˆāļ”āļĩāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āđāļĄāđˆāļ™āļĒāļģāđāļĨāļ°āđ€āļ›āđ‡āļ™āļ­āļąāļ•āđ‚āļ™āļĄāļąāļ•āļī āļŸāļēāļĢāđŒāļĄāđ„āļāđˆāđ„āļ‚āđˆāđāļšāļšāļŠāļĄāļēāļĢāđŒāļ•āļ—āļģāļ‡āļēāļ™āļšāļ™āļāļēāļ™āļ•āļĢāļĢāļāļĻāļēāļŠāļ•āļĢāđŒāļ„āļĨāļļāļĄāđ€āļ„āļĢāļ·āļ­āđ‚āļ”āļĒāđƒāļŠāđ‰āļĢāļēāļŠāļžāđŒāđ€āļšāļ­āļĢāđŒāļĢāļĩāđˆāđ„āļžāļ›āļĢāļ°āļĄāļ§āļĨāļœāļĨāļ‚āđ‰āļ­āļĄāļđāļĨāļ™āļģāđ€āļ‚āđ‰āļēāļ—āļĩāđˆāđ€āļāđ‡āļšāđ„āļ”āđ‰āļˆāļēāļāļ•āļąāļ§āļĢāļąāļšāļĢāļđāđ‰āļ—āļĩāđˆāļ•āļīāļ”āļ•āļąāđ‰āļ‡āļ­āļĒāļđāđˆāļ āļēāļĒāđƒāļ™āļŸāļēāļĢāđŒāļĄ āđ„āļ”āđ‰āđāļāđˆ āļ­āļļāļ“āļŦāļ āļđāļĄāļī āđāļĨāļ°āļ„āļ§āļēāļĄāļŠāļ·āđ‰āļ™ āđ€āļžāļ·āđˆāļ­āļŠāļĢāđ‰āļēāļ‡āļŠāļąāļāļāļēāļ“āļ„āļ§āļšāļ„āļļāļĄāļ­āļļāļ›āļāļĢāļ“āđŒāļ„āļ§āļšāļ„āļļāļĄāļ­āļļāļ“āļŦāļ āļđāļĄāļīāđāļĨāļ°āļ„āļ§āļēāļĄāļŠāļ·āđ‰āļ™āļ āļēāļĒāđƒāļ™āļŸāļēāļĢāđŒāļĄ āđ„āļ”āđ‰āđāļāđˆ āļžāļąāļ”āļĨāļĄāļ”āļđāļ”āļ­āļēāļāļēāļĻ āđāļœāļ‡āļĢāļąāļ‡āļœāļķāđ‰āļ‡ āđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļ—āļģāļ™āđ‰āļģāļ­āļļāđˆāļ™ āđāļĨāļ°āļ›āļąāđŠāļĄāļ™āđ‰āļģ āļ—āļĩāđˆāļ•āļīāļ”āļ•āļąāđ‰āļ‡āļ­āļĒāļđāđˆāļšāļĢāļīāđ€āļ§āļ“āđ‚āļĢāļ‡āđ€āļĢāļ·āļ­āļ™āđ€āļĨāļĩāđ‰āļĒāļ‡āđ„āļāđˆ āļāļēāļĢāļ—āļ”āļŠāļ­āļšāļĢāļ°āļšāļšāļ”āļģāđ€āļ™āļīāļ™āļāļēāļĢāļāļąāļšāļŸāļēāļĢāđŒāļĄāļˆāļĢāļīāļ‡āļ‚āļ™āļēāļ”āđ€āļĨāđ‡āļāđƒāļ™āļŠāļ āļēāļžāļ­āļēāļāļēāļĻāļˆāļĢāļīāļ‡āļ—āļĩāđˆāļĄāļĩāļ„āļ§āļēāļĄāļĢāđ‰āļ­āļ™āđāļĨāļ°āļ„āļ§āļēāļĄāļŠāļ·āđ‰āļ™āļˆāļēāļāļāļ™ āļœāļĨāļāļēāļĢāļ—āļ”āļŠāļ­āļš āļžāļšāļ§āđˆāļē āļĢāļ°āļšāļšāļŠāļēāļĄāļēāļĢāļ–āļ„āļ§āļšāļ„āļļāļĄāļ­āļļāļ“āļŦāļ āļđāļĄāļīāđāļĨāļ°āļ„āļ§āļēāļĄāļŠāļ·āđ‰āļ™āđƒāļ™āļŸāļēāļĢāđŒāļĄāđƒāļŦāđ‰āļ­āļĒāļđāđˆāđƒāļ™āļŠāđˆāļ§āļ‡āļ—āļĩāđˆāđ€āļŦāļĄāļēāļ°āļŠāļĄāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āļ­āļąāļ•āđ‚āļ™āļĄāļąāļ•āļīāđāļĨāļ°āļ–āļđāļāļ•āđ‰āļ­āļ‡āļŠāļ­āļ”āļ„āļĨāđ‰āļ­āļ‡āļāļąāļšāļāļēāļĢāđ€āļ›āļĨāļĩāđˆāļĒāļ™āđāļ›āļĨāļ‡āļ‚āļ­āļ‡āļŠāļ āļēāļžāļ āļđāļĄāļīāļ­āļēāļāļēāļĻāļ āļēāļĒāļ™āļ­āļāļŸāļēāļĢāđŒāļĄ āļ„āļģāļŠāļģāļ„āļąāļ: āļœāļĨāļīāļ•āļ āļēāļžāđ„āļ‚āđˆāđ„āļāđˆ  āļŸāļēāļĢāđŒāļĄāļ­āļąāļˆāļ‰āļĢāļīāļĒāļ°  āļ•āļĢāļĢāļāļĻāļēāļŠāļ•āļĢāđŒāļ„āļĨāļļāļĄāđ€āļ„āļĢāļ·āļ­Â  āļĢāļēāļŠāļžāđŒāđ€āļšāļ­āļĢāđŒāļĢāļĩāđˆāđ„āļž   Abstract This paper presented the development of a smart farm system of laying hens for farmers, especially independent herdsman from small to medium farms, who suffer loss as a result of declined productivity due to inability to control internal farm environment according to good practice in an accurate and automated manner. Our smart farm was operated based on fuzzy logic and Raspberry Pi to process data collected from temperature and humidity sensors installed inside the farm. In order to generate control signals for intra-farm temperature and humidity, controller devices, ventilators, cooling pad, heater, and water pump were installed in the area next to the farm. The experiment results showed that the system could adjust temperature and humidity inside the farm to appropriate levels automatically and accurately according to climate change outside the farm. Keywords: Egg productivity, Smart farm, Fuzzy logic, Raspberry P

    āļāļēāļĢāļ•āļĢāļ°āļŦāļ™āļąāļāļĢāļđāđ‰āļ‚āļ­āļ‡āļšāļĢāļīāļŦāļēāļĢāļ˜āļļāļĢāļāļīāļˆāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ• āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĢāļēāļĄāļ„āļģāđāļŦāļ‡ āļ•āđˆāļ­āļĄāļēāļ•āļĢāļāļēāļ™āļāļēāļĢāļ­āļļāļ”āļĄāļĻāļķāļāļĐāļē āļž.āļĻ. 2561 āļ”āđ‰āļēāļ™āļœāļĨāļĨāļąāļžāļ˜āđŒāļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™

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    āļāļēāļĢāļ§āļīāļˆāļąāļĒāđ€āļĢāļ·āđˆāļ­āļ‡ āļāļēāļĢāļ•āļĢāļ°āļŦāļ™āļąāļāļĢāļđāđ‰āļ‚āļ­āļ‡āļšāļĢāļīāļŦāļēāļĢāļ˜āļļāļĢāļāļīāļˆāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ• āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĢāļēāļĄāļ„āļģāđāļŦāļ‡āļ•āđˆāļ­āļĄāļēāļ•āļĢāļāļēāļ™āļāļēāļĢāļ­āļļāļ”āļĄāļĻāļķāļāļĐāļē āļž.āļĻ. 2561 āļ”āđ‰āļēāļ™āļœāļĨāļĨāļąāļžāļ˜āđŒāļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™ āļĄāļĩāļ§āļąāļ•āļ–āļļāļ›āļĢāļ°āļŠāļ‡āļ„āđŒāđ€āļžāļ·āđˆāļ­ (1) āļĻāļķāļāļĐāļēāļĢāļ°āļ”āļąāļšāļ„āļ§āļēāļĄāļ„āļīāļ”āđ€āļŦāđ‡āļ™āđ€āļāļĩāđˆāļĒāļ§āļāļąāļšāļāļēāļĢāļ•āļĢāļ°āļŦāļ™āļąāļāļĢāļđāđ‰āļ‚āļ­āļ‡āļšāļĢāļīāļŦāļēāļĢāļ˜āļļāļĢāļāļīāļˆāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ• āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĢāļēāļĄāļ„āļģāđāļŦāļ‡āļ•āđˆāļ­āļĄāļēāļ•āļĢāļāļēāļ™āļāļēāļĢāļ­āļļāļ”āļĄāļĻāļķāļāļĐāļē āļž.āļĻ. 2561 āļ”āđ‰āļēāļ™āļœāļĨāļĨāļąāļžāļ˜āđŒāļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™ āđāļĨāļ° (2) āļĻāļķāļāļĐāļēāļ„āļ§āļēāļĄāđāļ•āļāļ•āđˆāļēāļ‡āļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ›āļąāļˆāļˆāļąāļĒāļŠāđˆāļ§āļ™āļšāļļāļ„āļ„āļĨāļāļąāļšāļ„āļ§āļēāļĄāļ„āļīāļ”āđ€āļŦāđ‡āļ™āđ€āļāļĩāđˆāļĒāļ§āļāļąāļš āļāļēāļĢāļ•āļĢāļ°āļŦāļ™āļąāļāļĢāļđāđ‰āļ‚āļ­āļ‡āļšāļĢāļīāļŦāļēāļĢāļ˜āļļāļĢāļāļīāļˆāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ• āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĢāļēāļĄāļ„āļģāđāļŦāļ‡āļ•āđˆāļ­āļĄāļēāļ•āļĢāļāļēāļ™āļāļēāļĢāļ­āļļāļ”āļĄāļĻāļķāļāļĐāļē āļž.āļĻ. 2561 āļ”āđ‰āļēāļ™āļœāļĨāļĨāļąāļžāļ˜āđŒāļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™ āļ›āļĢāļ°āļŠāļēāļāļĢāļ—āļĩāđˆāđƒāļŠāđ‰āđƒāļ™āļāļēāļĢāļĻāļķāļāļĐāļēāļ„āļĢāļąāđ‰āļ‡āļ™āļĩāđ‰ āļ„āļ·āļ­ āļšāļĢāļīāļŦāļēāļĢāļ˜āļļāļĢāļāļīāļˆāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ• āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĢāļēāļĄāļ„āļģāđāļŦāļ‡ āļāļĨāļļāđˆāļĄāļ•āļąāļ§āļ­āļĒāđˆāļēāļ‡āļˆāļģāļ™āļ§āļ™ 400 āļ„āļ™ āļāļēāļĢāļŠāļļāđˆāļĄāļ•āļąāļ§āļ­āļĒāđˆāļēāļ‡āđāļšāļšāđƒāļŠāđ‰āļ§āļīāļ˜āļĩāļāļēāļĢāļŠāļļāđˆāļĄāđāļšāļšāļšāļąāļ‡āđ€āļ­āļīāļ āđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļĄāļ·āļ­āđƒāļ™āļāļēāļĢāļ§āļīāļˆāļąāļĒāđƒāļŠāđ‰āđāļšāļšāļŠāļ­āļšāļ–āļēāļĄ āļŠāļ–āļīāļ•āļīāļ—āļĩāđˆāđƒāļŠāđ‰āđƒāļ™āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ‚āđ‰āļ­āļĄāļđāļĨ āđ„āļ”āđ‰āđāļāđˆ āļ„āđˆāļēāļ„āļ§āļēāļĄāļ–āļĩāđˆ āļ„āđˆāļēāļĢāđ‰āļ­āļĒāļĨāļ° āļ„āđˆāļēāđ€āļ‰āļĨāļĩāđˆāļĒ āļ„āđˆāļēāļŠāđˆāļ§āļ™āđ€āļšāļĩāđˆāļĒāļ‡āđ€āļšāļ™āļĄāļēāļ•āļĢāļāļēāļ™ āļ„āđˆāļēāļ„āļ§āļēāļĄāđāļˆāļāđāļˆāļ‡āļ„āļ§āļēāļĄāļ–āļĩāđˆ āđāļĨāļ°āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ„āđˆāļēāļ„āļ§āļēāļĄāđāļ›āļĢāļ›āļĢāļ§āļ™āđāļšāļšāļ—āļēāļ‡āđ€āļ”āļĩāļĒāļ§ āļœāļđāđ‰āļ•āļ­āļšāđāļšāļšāļŠāļ­āļšāļ–āļēāļĄ āļŠāđˆāļ§āļ™āđƒāļŦāļāđˆāđ€āļ›āđ‡āļ™āđ€āļžāļĻāļŦāļāļīāļ‡ āļ­āļēāļĒāļļāļĢāļ°āļŦāļ§āđˆāļēāļ‡ 26-35 āļ›āļĩ āļ›āļĢāļ°āđ€āļ āļ—āļ‚āļ­āļ‡āļŦāļ™āđˆāļ§āļĒāļ‡āļēāļ™āđ€āļ­āļāļŠāļ™ āļŊ āļ›āļĢāļ°āđ€āļ āļ—āļ•āļģāđāļŦāļ™āđˆāļ‡āļ‡āļēāļ™āļĢāļ°āļ”āļąāļšāļœāļđāđ‰āļ›āļāļīāļšāļąāļ•āļī āđāļĨāļ°āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒāļ—āļģāļ‡āļēāļ™ āđ„āļĄāđˆāđ€āļāļīāļ™ 5 āļ›āļĩ āđ‚āļ”āļĒāļžāļšāļ§āđˆāļē (1) āļœāļĨāļāļēāļĢāļĻāļķāļāļĐāļēāļĢāļ°āļ”āļąāļšāļ„āļ§āļēāļĄāļ„āļīāļ”āđ€āļŦāđ‡āļ™āđ€āļāļĩāđˆāļĒāļ§āļāļąāļšāļāļēāļĢāļ•āļĢāļ°āļŦāļ™āļąāļāļĢāļđāđ‰āļ‚āļ­āļ‡āļšāļĢāļīāļŦāļēāļĢāļ˜āļļāļĢāļāļīāļˆāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ• āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĢāļēāļĄāļ„āļģāđāļŦāļ‡ āļ•āđˆāļ­āļĄāļēāļ•āļĢāļāļēāļ™āļāļēāļĢāļ­āļļāļ”āļĄāļĻāļķāļāļĐāļē āļž.āļĻ. 2561 āļ”āđ‰āļēāļ™āļœāļĨāļĨāļąāļžāļ˜āđŒāļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™ āđƒāļ™āļ āļēāļžāļĢāļ§āļĄāļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļĄāļēāļ āđ€āļĄāļ·āđˆāļ­āļžāļīāļˆāļēāļĢāļ“āļēāđ€āļ›āđ‡āļ™āļĢāļēāļĒāļ”āđ‰āļēāļ™ āļžāļšāļ§āđˆāļē āļāļēāļĢāđ€āļ›āđ‡āļ™āļžāļĨāđ€āļĄāļ·āļ­āļ‡āļ—āļĩāđˆāđ€āļ‚āđ‰āļĄāđāļ‚āđ‡āļ‡āļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļĄāļēāļāđ€āļ›āđ‡āļ™āļ­āļąāļ™āļ”āļąāļšāđāļĢāļ āļĢāļ­āļ‡āļĨāļ‡āļĄāļē āļ„āļ·āļ­ āļāļēāļĢāđ€āļ›āđ‡āļ™āļšāļļāļ„āļ„āļĨāļ—āļĩāđˆāļĄāļĩāļ„āļ§āļēāļĄāļĢāļđāđ‰āļ„āļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļ–āļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļĄāļēāļ āđāļĨāļ° āļāļēāļĢāđ€āļ›āđ‡āļ™āļœāļđāđ‰āļĢāđˆāļ§āļĄāļŠāļĢāđ‰āļēāļ‡āļŠāļĢāļĢāļ„āđŒāļ™āļ§āļąāļ•āļāļĢāļĢāļĄāļ­āļĒāļđāđˆāđƒāļ™āļĢāļ°āļ”āļąāļšāļĄāļēāļ āļ•āļēāļĄāļĨāļģāļ”āļąāļš āđāļĨāļ° (2) āļœāļĨāļāļēāļĢāļĻāļķāļāļĐāļēāļ›āļąāļˆāļˆāļąāļĒāļŠāđˆāļ§āļ™āļšāļļāļ„āļ„āļĨ āļ”āđ‰āļēāļ™āļ›āļĢāļ°āļŠāļšāļāļēāļĢāļ“āđŒ āļ—āļĩāđˆāļĄāļĩāļ„āļ§āļēāļĄāđāļ•āļāļ•āđˆāļēāļ‡āļŠāđˆāļ‡āļœāļĨāļ•āđˆāļ­āļ„āļ§āļēāļĄāļ„āļīāļ”āđ€āļŦāđ‡āļ™āļ‚āļ­āļ‡āļāļēāļĢāļ•āļĢāļ°āļŦāļ™āļąāļāļĢāļđāđ‰āļ‚āļ­āļ‡āļšāļĢāļīāļŦāļēāļĢāļ˜āļļāļĢāļāļīāļˆāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ• āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāļĢāļēāļĄāļ„āļģāđāļŦāļ‡ āļ•āđˆāļ­āļĄāļēāļ•āļĢāļāļēāļ™āļāļēāļĢāļ­āļļāļ”āļĄāļĻāļķāļāļĐāļē āļž.āļĻ. 2561 āļ”āđ‰āļēāļ™āļœāļĨāļĨāļąāļžāļ˜āđŒāļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™āļ—āļĩāđˆāđāļ•āļāļ•āđˆāļēāļ‡āļ­āļĒāđˆāļēāļ‡āļĄāļĩāļ™āļąāļĒāļŠāļģāļ„āļąāļāļ—āļēāļ‡āļŠāļ–āļīāļ•āļīāļ—āļĩāđˆāļĢāļ°āļ”āļąāļš 0.05The research objectives are (1) to study the perceptions and awareness of students of the Master of Business Administration (MBA) program, Ramkhamhaeng University towards national Higher Education Standards B.E. 2561 (2018) in desired learning outcomes, and (2) to explore individual differences in demographic characteristics and opinion levels on the perceptions of aforesaid framework. The study sample, being drawn from convenience sampling included 400 MBA students of Ramkhamhaeng University. A questionnaire set served as the instrument for collecting data. The statistics for data analysis were frequency, percentage, mean, standard deviation, frequency distribution and one-way ANOVA. The majority of respondents represented female, aged between 26-35 years, business owners, office employees, possessing less than five years’ experience. As results, respondents’ perception of Higher Education Standards Framework 2018 on learning outcomes was overall at a high level. Substantial aspects could be prioritized in this manner: Smart Citizenship, Having vital competencies and skills; and Possessing characteristics of creative and innovative individuals. Differences in perceptions towards the 2018 framework were found among respondents with different types and levels of work experience (p<0.05)

    The Relationship between Research and Development Disclosure and Share Price of Listed Companies in the Stock Exchange of Thailand (New S-curve)

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    āļšāļąāļāļŠāļĩāļĄāļŦāļēāļšāļąāļ“āļ‘āļīāļ• (āļāļēāļĢāļšāļąāļāļŠāļĩ), 2566The purpose of this research were to study the level of research and development disclosure of listed companies on the Stock Exchange of Thailand in the New S-curve group and to test the differences in research and development disclosure between industries of the New S-curve group as well as to test the relationship between the research and development disclosure and the share price of listed companies in the New S-curve group by collecting data from the annual report between 2016 and 2021, totaling 76 companies, consisting of research and development disclosure, size of business, age of business, industry type, risk, profit, audit committee and Covid-19 by analyzing descriptive data, ANOVA, correlation analysis, and multiple regression analysis. Results from 2016 to 2021, it was found that in 2020, the overall research and development disclosure score was the highest. As for the number words of research and development disclosure, it was found that 2021 had the most disclosure of research and development and decrease until 2016.Based on the data analysis, the difference in research and development disclosure scores and research and development disclosure word count between industries It was found that the industry group had a significant effect on research and development disclosure at 0.05, and from the correlation test, it was found that research and development disclosure scores do not correlate with share price. Research and development disclosure word counts were positively correlated with share price. at a significance level of 0.10, size and age of business had a positive correlation with the share price at a significance level of 0.05 and 0.01.āļāļēāļĢāļ§āļīāļˆāļąāļĒāļ™āļĩāđ‰āļĄāļĩāļ§āļąāļ•āļ–āļļāļ›āļĢāļ°āļŠāļ‡āļ„āđŒāđ€āļžāļ·āđˆāļ­āļĻāļķāļāļĐāļēāļĢāļ°āļ”āļąāļšāļ‚āļ­āļ‡āļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļēāļ‚āļ­āļ‡ āļšāļĢāļīāļĐāļąāļ—āļ—āļĩāđˆāļˆāļ”āļ—āļ°āđ€āļšāļĩāļĒāļ™āđƒāļ™āļ•āļĨāļēāļ”āļŦāļĨāļąāļāļ—āļĢāļąāļžāļĒāđŒāđāļŦāđˆāļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđƒāļ™āļāļĨāļļāđˆāļĄ New S-curve āļ—āļ”āļŠāļ­āļšāļ„āļ§āļēāļĄāđāļ•āļāļ•āđˆāļēāļ‡ āļ‚āļ­āļ‡āļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļēāđāļ•āđˆāļĨāļ°āļ­āļļāļ•āļŠāļēāļŦāļāļĢāļĢāļĄāļ‚āļ­āļ‡āļšāļĢāļīāļĐāļąāļ—āļ—āļĩāđˆāļˆāļ”āļ—āļ°āđ€āļšāļĩāļĒāļ™āđƒāļ™āļ•āļĨāļēāļ”āļŦāļĨāļąāļāļ—āļĢāļąāļžāļĒāđŒ āđāļŦāđˆāļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđƒāļ™āļāļĨāļļāđˆāļĄ New S-curve āđāļĨāļ°āļ—āļ”āļŠāļ­āļšāļ„āļ§āļēāļĄāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒāļĢāļ°āļŦāļ§āđˆāļēāļ‡āļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ° āļžāļąāļ’āļ™āļēāđāļĨāļ°āļĢāļēāļ„āļēāļŦāļļāđ‰āļ™āļ‚āļ­āļ‡āļšāļĢāļīāļĐāļąāļ—āļ—āļĩāđˆāļˆāļ”āļ—āļ°āđ€āļšāļĩāļĒāļ™āđƒāļ™āļ•āļĨāļēāļ”āļŦāļĨāļąāļāļ—āļĢāļąāļžāļĒāđŒāđāļŦāđˆāļ‡āļ›āļĢāļ°āđ€āļ—āļĻāđ„āļ—āļĒāđƒāļ™āļāļĨāļļāđˆāļĄ New S-curve āđ‚āļ”āļĒāđ€āļāđ‡āļšāļ‚āđ‰āļ­āļĄāļđāļĨāļˆāļēāļāļĢāļēāļĒāļ‡āļēāļ™āļ›āļĢāļ°āļˆ āļēāļ›āļĩāļĢāļ°āļŦāļ§āđˆāļēāļ‡ āļž.āļĻ. 2559 āļ–āļķāļ‡āļž.āļĻ. 2564 āļˆ āļēāļ™āļ§āļ™ 76 āļšāļĢāļīāļĐāļąāļ— āļ›āļĢāļ°āļāļ­āļšāļ”āđ‰āļ§āļĒ āļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļē āļ‚āļ™āļēāļ”āļ‚āļ­āļ‡āļāļīāļˆāļāļēāļĢ āļ­āļēāļĒāļļāļ‚āļ­āļ‡āļāļīāļˆāļāļēāļĢ āļ›āļĢāļ°āđ€āļ āļ—āļ­āļļāļ•āļŠāļēāļŦāļāļĢāļĢāļĄ āļ„āļ“āļ°āļāļĢāļĢāļĄāļāļēāļĢāļ•āļĢāļ§āļˆāļŠāļ­āļš āļ„āļ§āļēāļĄāđ€āļŠāļĩāđˆāļĒāļ‡ āļ āļēāđ„āļĢ āđāļĨāļ°āļŠāļ–āļēāļ™āļāļēāļĢāļ“āđŒ Covid-19 āļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ‚āđ‰āļ­āļĄāļđāļĨāđ‚āļ”āļĒāđƒāļŠāđ‰āļŠāļ–āļīāļ•āļīāđ€āļŠāļīāļ‡ āļžāļĢāļĢāļ“āļ™āļē āļ—āļ”āļŠāļ­āļšāļŠāļĄāļĄāļļāļ•āļīāļāļēāļ™āđ‚āļ”āļĒāđƒāļŠāđ‰ ANOVA āđāļĨāļ°āļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ„āļ§āļēāļĄāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒāđ€āļŠāļīāļ‡āļžāļŦāļļāļ„āļđāļ“ āļœāļĨāļāļēāļĢāļĻāļķāļāļĐāļē āļĢāļ°āļ”āļąāļšāļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļēāļĢāļēāļĒāļ›āļĩāļ•āļąāđ‰āļ‡āđāļ•āđˆāļž.āļĻ. 2559 āļ–āļķāļ‡ āļž.āļĻ. 2564 āļžāļšāļ§āđˆāļēāđƒāļ™ āļž.āļĻ. 2563 āļ„āļ°āđāļ™āļ™āļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļēāđ‚āļ”āļĒāļĢāļ§āļĄāļĄāļēāļāļ—āļĩāđˆāļŠāļļāļ” āļŠāđˆāļ§āļ™āļˆ āļēāļ™āļ§āļ™āļ„ āļēāļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒ āđāļĨāļ°āļžāļąāļ’āļ™āļē āļžāļšāļ§āđˆāļē āļž.āļĻ. 2564 āļĄāļĩāļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļēāļĄāļēāļāļ—āļĩāđˆāļŠāļļāļ” āđāļĨāļ°āļĨāļ”āļĨāļ‡āļĄāļēāļ•āļēāļĄāļĨ āļēāļ”āļąāļš āļˆāļ™āļ–āļķāļ‡āļž.āļĻ. 2559 āļˆāļēāļāļāļēāļĢāļ§āļīāđ€āļ„āļĢāļēāļ°āļŦāđŒāļ‚āđ‰āļ­āļĄāļđāļĨāļ„āļ§āļēāļĄāđāļ•āļāļ•āđˆāļēāļ‡āļ‚āļ­āļ‡āļ„āļ°āđāļ™āļ™āļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļē āđāļĨāļ°āļˆ āļēāļ™āļ§āļ™āļ„ āļēāļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļēāļĢāļ°āļŦāļ§āđˆāļēāļ‡āļ­āļļāļ•āļŠāļēāļŦāļāļĢāļĢāļĄ āļžāļšāļ§āđˆāļēāļāļĨāļļāđˆāļĄāļ­āļļāļ•āļŠāļēāļŦāļāļĢāļĢāļĄāļŠāđˆāļ‡āļœāļĨ āļ•āđˆāļ­āļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļēāļ­āļĒāđˆāļēāļ‡āļĄāļĩāļ™āļąāļĒāļŠ āļēāļ„āļąāļāļ—āļĩāđˆ 0.05 āđāļĨāļ°āļˆāļēāļāļāļēāļĢāļ—āļ”āļŠāļ­āļšāļ„āļ§āļēāļĄāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒ āļžāļšāļ§āđˆāļē āļ„āļ°āđāļ™āļ™āļāļēāļĢāđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļēāđ„āļĄāđˆāļĄāļĩāļ„āļ§āļēāļĄāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒāļāļąāļšāļĢāļēāļ„āļēāļŦāļļāđ‰āļ™ āļŠāđˆāļ§āļ™āļˆ āļēāļ™āļ§āļ™āļ„ āļēāļāļēāļĢ āđ€āļ›āļīāļ”āđ€āļœāļĒāļ‚āđ‰āļ­āļĄāļđāļĨāļāļēāļĢāļ§āļīāļˆāļąāļĒāđāļĨāļ°āļžāļąāļ’āļ™āļēāļĄāļĩāļ„āļ§āļēāļĄāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒāđ€āļŠāļīāļ‡āļšāļ§āļāļāļąāļšāļĢāļēāļ„āļēāļŦāļļāđ‰āļ™ āļ—āļĩāđˆāļĢāļ°āļ”āļąāļšāļ™āļąāļĒāļŠ āļēāļ„āļąāļ 0.10 āļ™āļ­āļāļˆāļēāļāļ™āļĩāđ‰ āļ‚āļ™āļēāļ”āļāļīāļˆāļāļēāļĢ āđāļĨāļ°āļ­āļēāļĒāļļāļāļīāļˆāļāļēāļĢāļĄāļĩāļ„āļ§āļēāļĄāļŠāļąāļĄāļžāļąāļ™āļ˜āđŒāđ€āļŠāļīāļ‡āļšāļ§āļāļāļąāļšāļĢāļēāļ„āļēāļŦāļļāđ‰āļ™āļ—āļĩāđˆāļĢāļ°āļ”āļąāļšāļ™āļąāļĒāļŠ āļēāļ„āļąāļ 0.05 āđāļĨāļ° 0.01 āļ•āļēāļĄāļĨ āļēāļ”āļą

    āļ­āļīāļ™āđ€āļ—āļ­āļĢāđŒāđ€āļ™āđ‡āļ•āđ€āļžāļ·āđˆāļ­āļŠāļĢāļĢāļžāļŠāļīāđˆāļ‡ (Internet of Things) āļāļąāļšāļāļēāļĢāļĻāļķāļāļĐāļē Internet of Things on Education

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    āđāļ™āļ§āļ„āļīāļ”āļŠāļģāļ„āļąāļāļ‚āļ­āļ‡ āļ­āļīāļ™āđ€āļ—āļ­āļĢāđŒāđ€āļ™āđ‡āļ•āđ€āļžāļ·āđˆāļ­āļŠāļĢāļĢāļžāļŠāļīāđˆāļ‡ (Internet of Things) āđ€āļ›āđ‡āļ™āļāļēāļĢāđƒāļŠāđ‰āļ›āļĢāļ°āđ‚āļĒāļŠāļ™āđŒāļˆāļēāļāļ„āļ§āļēāļĄāļāđ‰āļēāļ§āļŦāļ™āđ‰āļēāļ‚āļ­āļ‡āđ€āļ„āļĢāļ·āļ­āļ‚āđˆāļēāļĒāļ­āļīāļ™āđ€āļ—āļ­āļĢāđŒāđ€āļ™āđ‡āļ• āđāļĨāļ°āļāļēāļĢāđ€āļžāļīāđˆāļĄāļ‚āļķāđ‰āļ™āļ‚āļ­āļ‡āļ‚āđ‰āļ­āļĄāļđāļĨāļŠāļēāļĢāļŠāļ™āđ€āļ—āļĻāļˆāļģāļ™āļ§āļ™āļĄāļēāļ (Big Data) āļˆāļēāļāļ­āļļāļ›āļāļĢāļ“āđŒāļŦāļĢāļ·āļ­āļŠāļĢāļĢāļžāļŠāļīāđˆāļ‡āļ•āđˆāļēāļ‡ āđ† āļ—āļĩāđˆāļ­āļĒāļđāđˆāļĢāļ­āļšāļ•āļąāļ§ āđƒāļŦāđ‰āļŠāļēāļĄāļēāļĢāļ–āļ™āļģāļĄāļēāđƒāļŠāđ‰āļ›āļĢāļ°āđ‚āļĒāļŠāļ™āđŒāđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āđ€āļŦāļĄāļēāļ°āļŠāļĄ āđƒāļ™āļ”āđ‰āļēāļ™āļāļēāļĢāļĻāļķāļāļĐāļē āļ­āļīāļ™āđ€āļ—āļ­āļĢāđŒāđ€āļ™āđ‡āļ•āđ€āļžāļ·āđˆāļ­āļŠāļĢāļĢāļžāļŠāļīāđˆāļ‡āđ€āļ›āđ‡āļ™āđ€āļ„āļĢāļ·āđˆāļ­āļ‡āļĄāļ·āļ­āļ—āļĩāđˆāļˆāļ°āļŠāđˆāļ§āļĒāļ­āļģāļ™āļ§āļĒāļ„āļ§āļēāļĄāļŠāļ°āļ”āļ§āļāđƒāļ™āļāļēāļĢāļˆāļąāļ”āļāļēāļĢāđ€āļĢāļĩāļĒāļ™āļāļēāļĢāļŠāļ­āļ™āļ—āļĩāđˆāļ•āļ­āļšāļŠāļ™āļ­āļ‡āļ„āļ§āļēāļĄāđāļ•āļāļ•āđˆāļēāļ‡āļ‚āļ­āļ‡āļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™āđāļ•āđˆāļĨāļ°āļ„āļ™ āđƒāļŦāđ‰āļŠāļēāļĄāļēāļĢāļ–āđ€āļĢāļĩāļĒāļ™āļĢāļđāđ‰āđ„āļ”āđ‰āļ­āļĒāđˆāļēāļ‡āļĄāļĩāļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļ āļēāļžāđāļĨāļ°āļ›āļĢāļ°āļŠāļīāļ—āļ˜āļīāļœāļĨ āļœāļđāđ‰āđ€āļĢāļĩāļĒāļ™āļĄāļĩāļŠāđˆāļ§āļ™āļĢāđˆāļ§āļĄāđƒāļ™āļāļēāļĢāđ€āļĢāļĩāļĒāļ™āļĢāļđāđ‰āđ€āļžāļīāđˆāļĄāļĄāļēāļāļ‚āļķāđ‰āļ™ āđ€āļ›āđ‡āļ™āļāļēāļĢāđ€āļŠāļĢāļīāļĄāļŠāļĢāđ‰āļēāļ‡āļāļēāļĢāđƒāļŠāđ‰āļ›āļĢāļ°āđ‚āļĒāļŠāļ™āđŒāļˆāļēāļāļ—āļĢāļąāļžāļĒāļēāļāļĢāđāļŦāļĨāđˆāļ‡āļŠāļēāļĢāļŠāļ™āđ€āļ—āļĻāđƒāļŦāđ‰āđ€āļāļīāļ”āļ„āļ§āļēāļĄāļ„āļļāđ‰āļĄāļ„āđˆāļēāļŠāļđāļ‡āļŠāļļāļ” āļ„āļģāļŠāļģāļ„āļąāļ āļ­āļīāļ™āđ€āļ—āļ­āļĢāđŒāđ€āļ™āđ‡āļ•āđ€āļžāļ·āđˆāļ­āļŠāļĢāļĢāļžāļŠāļīāđˆāļ‡ / āļāļēāļĢāļĻāļķāļāļĐāļē / āđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļāļēāļĢāļĻāļķāļāļĐāļēThe concept of the Internet of Things is to take advantage of advances in networking for the Internet and an increase in the amount of data (Big Data) or from things that are around them. It can be used appropriately.  Internet of Things in education is a tool to help facilitate the teaching and learning for the different of characteristic learners and more effectively for students collaborating theirs in learning the Internet of Things. Strengthens the utilization of information resources to achieve higher performance. Keyword Internet of Things / Education / Educational Technology

    āļĢāļđāļ›āđāļšāļšāļāļēāļĢāļžāļąāļ’āļ™āļēāļ„āļ§āļēāļĄāļŠāļēāļĄāļēāļĢāļ–āđƒāļ™āļāļēāļĢāļ›āļāļīāļšāļąāļ•āļīāļāļēāļĢāļŠāļ–āļēāļ™āļĩāđ‚āļ—āļĢāļ—āļąāļĻāļ™āđŒāļšāļ™āļĢāļ°āļšāļšāđ€āļ„āļĢāļ·āļ­āļ‚āđˆāļēāļĒāļ”āđ‰āļ§āļĒāļ§āļīāļ˜āļĩāļāļēāļĢāđ€āļĢāļĩāļĒāļ™āļāļēāļĢāļŠāļ­āļ™āđāļšāļšāļœāļŠāļĄāļœāļŠāļēāļ™āļ‚āļ­āļ‡āļŠāļēāļ‚āļēāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļāļēāļĢāđ‚āļ—āļĢāļ—āļąāļĻāļ™āđŒāđāļĨāļ°āļ§āļīāļ—āļĒāļļāļāļĢāļ°āļˆāļēāļĒāđ€āļŠāļĩāļĒāļ‡ āļĄāļŦāļēāļ§āļīāļ—āļĒāļēāļĨāļąāļĒāđ€āļ—āļ„āđ‚āļ™āđ‚āļĨāļĒāļĩāļĢāļēāļŠāļĄāļ‡āļ„āļĨāļāļĢāļļāļ‡āđ€āļ—āļž

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    The research study has objectives to is to 1) Develop the model of ability development practice perform with Television Station webcasting by Blended learning of Bachelor Television and Radio Broadcasting Technology Rajamangala University of Technology Krungthep. 2) Evaluate the model of ability development practice perform with Television station webcasting by Blended learning of Bachelor Television and Radio Broadcasting Technology Rajamangala University of Technology Krungthep. The result found that the developed model include with 5 Element 1) Man 2) Money 3) Material 4) Place 5) Time and 5 method of teching 1) Introduction 2) Teaching 3) Production 4) Broadcast 5) Evaluation. Evaluation model developed including 1) Element 2) Method 3) Using Model of ability development practice perform with Television Station webcasting by Blended learning by the experts in an overview that was most advantage
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