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Design Public Park Project : Saint Chon College Campus Park

Design Public Park Project : Saint Chon College Campus Park

Abstract

Expanding from a public park design project to a campus design on an area of ​​over 50 rai in Ang Sila Subdistrict, Mueang District, Chonburi Province, to serve as both an educational institution and a place for relaxation and learning for the surrounding people.

Objective

การพัฒนาพื้นที่แห่งนี้ให้กลายเป็นCampus Park เพื่อเป็นพื้นที่พักผ่อนและแลกเปลี่ยนความรู้เกี่ยวกับระบบนิเวศชายหาดของจังหวัดชลบุรี

Other Innovations

Artificial intelligence of things system for monitoring and controlling irrigation using weather information

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Artificial intelligence of things system for monitoring and controlling irrigation using weather information

This research focuses on the design and development of a prototype Artificial Intelligence of Things (AIoT) system for monitoring and controlling irrigation using weather information. The system consists of four main components: 1) Weather Station – This component includes various sensors such as air temperature, relative humidity, wind speed, and sunlight duration, among others, to collect real-time weather data. 2) Controller Unit – This unit is equipped with machine learning algorithms or models to estimate the reference evapotranspiration (ETo) and calculate the plant’s water requirement by integrating the crop coefficient (Kc) with other plant-related data. This enables the system to determine the optimal irrigation amount based on plant needs automatically. 3) User Interface (UI) and Display – This section allows farmers or users to input relevant information, such as plant type, soil type, irrigation system type, number of water emitters, planting distance, and growth stages. It also provides a display for monitoring and interaction with the system. 4) Irrigation Unit – This component is responsible for controlling the water supply and managing the irrigation emitters to ensure efficient water distribution based on the calculated requirements.

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Penetration Testing Learning Platform (SecurionSphere)

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Penetration Testing Learning Platform (SecurionSphere)

SecurionSphere is the penetration testing learning platform that focuses on web application exploitation. This platform is intended to address concerns seen in existing penetration testing platforms, such as resource sharing that may affect other users and the constant environment configuration the permits the same response leading to copy the answer from others. Supervisors can use templates to address various forms of web application vulnerability threats. Users can generate the instance of supervisor's templates machine. The platform also randomly generates the environment configuration for each machine has the difference environment and the answer. This allows the users get more realistic learning experiences without affecting the resources of others.

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Detection of salivary biomarker  for migraine diagnosis

คณะแพทยศาสตร์

Detection of salivary biomarker for migraine diagnosis

Migraine, a prevalent neurological disorder, is the third most common disease globally, causing significant health and financial burdens. It has four stages: prodrome, aura, headache, and postdrome. The prodrome (also known as premonitory) stage is crucial as it precedes the headache by up to 72 hours. Taking medication during the premonitory peroid has shown to prevent the headache phase . However, the symptoms of premonitory period lack specificity, making it difficult for patients to know if they’re experiencing premonitory symptoms. Calcitonin-gene related peptide (cGRP),is a protein that plays a key role in migraine pathogenesis and studies found that salivary cGRP levels increase during the premonitory stage. This study aims to develop and evaluate a lateral flow immunoassay kit for detecting salivary cGRP levels in migraine patients during the prodrome stage. It can serve as a confirmation tool for premonitory symptoms.

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