Hannanta-Anan, Pimkhuan

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Hannanta-Anan, Pimkhuan
Alternative Name
Hannanta-anan, Pimkhuan
Hannanta-Anan, P.
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Email
pimkhuan.ha@kmitl.ac.th

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Now showing 1 - 7 of 7
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    An ultra-violet sterilization robot for disinfection
    (2019-07-01)
    Chanprakon, Pacharawan
    ;
    Sae-Oung, Tapparat
    ;
    Treebupachatsakul, Treesukon
    ;
    Hannanta-Anan, Pimkhuan
    ;
    Piyawattanametha, Wibool
    Ultraviolet (UV) sterilization technology is used to aid in reduction of microorganisms that may remain on the surfaces after a standard cleaning to the minimum number. Our research team developed a UV robot or UV bot for sterilization in an operating or a patient room. Our UV bot has three 19.3-watt of UV lamps mounted on top of the UV bot platform covering 360° direction. Our UV bot employed an embedded system based on a Raspberry Pi to aid in navigation to avoid obstacles. In addition, we tested the effectiveness of eliminating Staphylococcus Aureus bacteria sample plates located 35 cm away from our UV bot to be within 8 seconds after UV light exposure.
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    Multi-Agent Q-Leaming for Power Allocation in Interference Channel
    (2022-01-01)
    Wongphatcharatham, Tanutsorn
    ;
    Phakphisut, Watid
    ;
    Wijitpornchai, Thongchai
    ;
    Areeprayoonkij, Poonlarp
    ;
    Jaruvitayakovit, Tanun
    Signal transmission in wireless networks suffers from unwanted interference. To maximize signal to interference plus noise ratio, transmit power of each transmitter needs to be optimally allocated. Here, we propose to use multi-agent Q-learning to optimize such transmit power within interference channel. Our simulation indicated that multi-agent Q-Iearning resulted in better sum-rate than the traditional methods such as the maximum power allocation and the random power allocation. Our work offers a novel and practical computational approach to optimizing signal transmission in wireless networks.
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    Effect of extrusion conditions on the physical properties of coconut rice-based extrudates
    (2019-09-09)
    Dumchaiyapoom, K.
    ;
    Hannanta-Anan, P.
    ;
    Phongpipatpong, M.
    Coconut meal is a by-product of coconut oil and coconut milk production. It is a rich source of dietary fiber which shows to have an important role in lowing the risk of various chronic diseases. Therefore, it is interesting to convert the coconut meal, previously recognized as a valueless by-product, into a nutritious food product. The aim of this work is to investigate the possibility of such conversion using a widely known extrusion method. The effect of extrusion variables, including the coconut meal content (0, 6, and 12 %), glutinous rice content (5, 10 and 15%) and screw speed of extruder (380, 400 and 420 rpm) were investigated on the properties of extruded products. Physical properties of the extrudates such as expansion ratio, density, water absorption index (WAI), water solubility index (WSI), crispness and moisture content were evaluated. Our study showed that the extrudates had expansion ratio of 2.30-2.78%, density of 0.55-0.76 g/cm<sup>3</sup>, WAI of 4.24-5.50 g/g, WSI of 21.51-33.37%, crispness of 16.87-27.73 kg.sec and moisture content of 6.76-8.27%. The regression models for true density, expansion ratio, crispness, WAI and WSI were derived and statistically significant (p<0.05).
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    Fabrications of Low-Cost Poly(methyl methacrylate) Microfluidic Devices for Precise Passive Flow Control
    (2024-01-01)
    Kaewtae, Wattana
    ;
    Tanasapsakul, Warinthorn
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    Pattamang, Pattaraluck
    ;
    Ranron, Norabadee
    ;
    Sripumkhai, Witsaroot
    Microfluidics serve as effective platforms for conducting point-of-care diagnostics and biochemical assays which require precise control over flow rates and incubation times. To enable their uses in resource-limited settings, a pump-free approach is essential for driving fluid flow within the microfluidics. In this study, we introduced cost-effective methodologies for fabricating poly(methyl methacrylate) (PMMA)-based microfluidic devices driven passively by capillary pressure. We explored three fabrication techniques including two-layer CNC micro-milling, two-layer laser engraving, and three-layer laser cutting. Among these methods, three-layer laser cutting proved to be the most reproducible method, yielding devices with consistent channel dimensions and contact angles. Consequently, this fabrication technique enables better control over flow rates within microfluidic systems. Our findings demonstrate the feasibility of fabricating low-cost, pump-free microfluidic devices for precise flow control, with potential applications in disease detection and biomedical research.
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    Effects of extrusion variables on extrudate characteristics from corn-based enriched with soybean residue
    (2019-09-09)
    Unsaeng, K.
    ;
    Hannanta-Anan, P.
    ;
    Phongpipatpong, M.
    Soybean residue is a food processing by-product of soya milk or tofu production process. It consists of rich protein and fiber. As a result, reprocessing soybean residue as human food can be a worthwhile alternative. This research focuses on studying the effects of extrusion process and the extrudate characteristics. The mixture of corn grit and soybean residue flour was extruded by single-screw extruder to produce high protein snack. Experimental design was performed by Box-Behnken design and Response surface methodology (RSM) was used to assess the effects on extrusion variables, including screw speed (370-430 RPM), soybean residue flour content (20-40%) and feed moisture (14-18%) on the properties of the extrudates including, expansion ratio (ER), density (D), water absorption index (WAI), water solubility index (WSI) and hardness (H). Analysis of variance showed that the most significant variables are soybean residue, which has negative effect on ER and positive effect on H, and screw speed, which has positive effect on ER and H, while feed moisture is non-significant in most characteristics.
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    A Cost-Effective Digital Microfluidic System for CRISPR Diagnostic Automation
    (2024-01-01)
    Vunkong, Jirachaya
    ;
    Hannanta-Anan, Pimkhuan
    CRISPR diagnostics offer precise detection of genetic material with high specificity and accuracy while adaptable for field deployment. However, the labor-intensive steps required can reduce usability and increase the risk of human error. To overcome these limitations, we developed a low-cost digital microfluidic (DMF) platform integrated with a custom fluorescence imaging module for the automation of CRISPR diagnostics. Our DMF platform was built from a basic PCB array coated with a layer of parafilm and silicone oil. The fluorescence module was custom designed and fabricated through 3D printing. Our integrated platform effectively facilitated movement, mixing, and fluorescence imaging of water and CRISPR-Cas reagents. This affordable DMF system demonstrates its initial feasibility for automating CRISPR diagnostics, enhancing accessibility and user- friendliness.
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    Computer Vision-aided CRISPR Diagnostics for the Detection of COVID-19
    (2021-04-01)
    Nimsamer, Pattaraporn
    ;
    Mayuramart, Oraphan
    ;
    Samacoits, Aubin
    ;
    Chantaravisoot, Naphat
    ;
    Nakhakes, Chajchawan
    Surveillance testing is a key strategy to control the spread of COVID-19. Unlike the gold standard testing method, quantitative reverse transcription polymerase chain reaction (RT-qPCR), CRISPR diagnostics have recently become a more appealing alternative as they are proven to be faster, simpler, and more affordable. However, the current CRISPR diagnostic readouts are typically non-quantitative, making them error-prone and lacking crucial information of viral load. To further improve the CRISPR diagnostic method, we have developed a custom computer vision algorithm that works in complement to common transilluminators to process fluorescence images of the diagnostic samples, quantify their fluorescence signals, and assign the test results. Our analysis showed that the quantified fluorescence intensity was directly correlated to the sample viral load, useful information for transmissibility and disease severity. Verified through laboratory and clinical samples, our algorithm accurately discriminated the samples with the viral RNA as low as 6.25 copies/uL, and correctly classified nasopharyngeal swab (NP swab) samples with 100% accuracy. Our work serves as a potential technique to improve the accuracy of CRISPR diagnostics of COVID-19 and promote rapid testing vital to the containment of the ongoing pandemic.