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This study aimed to show maps and analyses that display dengue cases and weather-related factors on dengue transmission in the three southernmost provinces of Thailand, namely Pattani, Yala, and Narathiwat provinces. Data on the number of dengue cases and weather variables including rainfall, rainy day, mean temperature, min temperature, max temperature, relative humidity, and air pressure for the period from January 2015 to December 2019 were obtained from the Bureau of Epidemiology, Ministry of Public Health and the Meteorological Department of Southern Thailand, respectively. Spearman rank correlation test was performed at lags from zero to two months and the predictive modeling used time series Poisson regression analysis. The distribution of dengue cases showed that in Pattani and Yala provinces the most dengue cases occurred in June. Narathiwat province had the most dengue cases occurring in August. The air pressure, relative humidity, rainfall, rainy day, and min temperature are the main predictors in Pattani province, while air pressure, rainy day, and max/mean temperature seem to play important roles in the number of dengue cases in Yala and Narathiwat provinces. The goodness-of-fit analyses reveal that the model fits the data reasonably well. The results provide scientific information for creating effective dengue control programs in the community, and the predictive model can support decision making in public health organizations and for management of the environmental risk area.
Teerawad Sriklin; Siriwan Kajornkasirat; Supattra Puttinaovarat. Dengue Transmission Mapping with Weather-Based Predictive Model in Three Southernmost Provinces of Thailand. Sustainability 2021, 13, 6754 .
AMA StyleTeerawad Sriklin, Siriwan Kajornkasirat, Supattra Puttinaovarat. Dengue Transmission Mapping with Weather-Based Predictive Model in Three Southernmost Provinces of Thailand. Sustainability. 2021; 13 (12):6754.
Chicago/Turabian StyleTeerawad Sriklin; Siriwan Kajornkasirat; Supattra Puttinaovarat. 2021. "Dengue Transmission Mapping with Weather-Based Predictive Model in Three Southernmost Provinces of Thailand." Sustainability 13, no. 12: 6754.
An online analytic service system was designed as a web and a mobile application for shrimp farmers and shrimp farm managers to manage the growth performance of shrimp. The MySQL database management system was used to manage the shrimp data. The Apache Web Server was used for contacting the shrimp database, and the web content displays were implemented with PHP script, JavaScript, and HTML5. Additionally, the program was linked with Google Charts to display data in various graphs, such as bar graphs and scatter diagrams, and Google Maps API was used to display water quality factors that are related to shrimp growth as spatial data. To test the system, field survey data from a shrimp farm in southern Thailand were used. Growth performance of shrimp and water quality data were collected from 13 earthen ponds in southern peninsular Thailand, located in the Surat Thani, Krabi, Phuket, and Satun provinces. The results show that the system allowed administrators to manage shrimp and farm data from the field sites. Both mobile and web applications were accessed by the users to manage the water quality factors and shrimp data. The system also provided the data analysis tool required to select a parameter from a list box and shows the association between water quality factors and shrimp data with a scatter diagram. Furthermore, the system generated a report of shrimp growth for the different farms with a line graph overlay on Google Maps™ in the data entry suite via mobile application. Online analytics for the growth performance of shrimp as provided by this system could be useful as decision support tools for effective shrimp farming.
Siriwan Kajornkasirat; Jareeporn Ruangsri; Charuwan Sumat; Pete Intaramontri. Online Analytics for Shrimp Farm Management to Control Water Quality Parameters and Growth Performance. Sustainability 2021, 13, 5839 .
AMA StyleSiriwan Kajornkasirat, Jareeporn Ruangsri, Charuwan Sumat, Pete Intaramontri. Online Analytics for Shrimp Farm Management to Control Water Quality Parameters and Growth Performance. Sustainability. 2021; 13 (11):5839.
Chicago/Turabian StyleSiriwan Kajornkasirat; Jareeporn Ruangsri; Charuwan Sumat; Pete Intaramontri. 2021. "Online Analytics for Shrimp Farm Management to Control Water Quality Parameters and Growth Performance." Sustainability 13, no. 11: 5839.
Southern Thailand has the highest Dengue Hemorrhagic Fever (DHF) incidence and fatality rate in Thailand. Geographic Information Systems (GIS) technology and spatial analysis techniques are powerful tools to describe epidemiological patterns. The aim of this study was to develop an Online Advanced Analytical Service: Profiles for Dengue Hemorrhagic Fever Transmission (OSD) in Southern Thailand. The system was developed using JavaServer Pages (JSP) and Database Management System (DBMS) with Structured Query Language (SQL) technology as the web database tool for data entry and data access, web Mathematica technology for data analysis and Google Maps™ API technology for online data display as the map service implementing GIS technology. The OSD system has been available online at URL http://www.s-cm.co/dengue . Users performed data entry using the web-service with login by social network (i.e. Facebook) account, used data analysis tools with online real-time statistical analysis and data display with transparent color circles overlaid on Google Maps™. The OSD system display represents the distribution of DHF cases with spatial information. This system enables health planners to provide interventions for DHF focusing on prevention, control, and strategic planning.
Siriwan Kajornkasirat; Jirapond Muangprathub; Nathaphon Boonnam. Online Advanced Analytical Service: Profiles for Dengue Hemorrhagic Fever Transmission in Southern Thailand. 2019, 48, 1979 -1987.
AMA StyleSiriwan Kajornkasirat, Jirapond Muangprathub, Nathaphon Boonnam. Online Advanced Analytical Service: Profiles for Dengue Hemorrhagic Fever Transmission in Southern Thailand. . 2019; 48 (11):1979-1987.
Chicago/Turabian StyleSiriwan Kajornkasirat; Jirapond Muangprathub; Nathaphon Boonnam. 2019. "Online Advanced Analytical Service: Profiles for Dengue Hemorrhagic Fever Transmission in Southern Thailand." 48, no. 11: 1979-1987.
In this paper, we propose developing a system optimally watering agricultural crops based on a wireless sensor network. This work aimed to design and develop a control system using node sensors in the crop field with data management via smartphone and a web application. The three components are hardware, web application, and mobile application. The first component was designed and implemented in control box hardware connected to collect data on the crops. Soil moisture sensors are used to monitor the field, connecting to the control box. The second component is a web-based application that was designed and implemented to manipulate the details of crop data and field information. This component applied data mining to analyze the data for predicting suitable temperature, humidity, and soil moisture for optimal future management of crops growth. The final component is mainly used to control crop watering through a mobile application in a smartphone. This allows either automatic or manual control by the user. The automatic control uses data from soil moisture sensors for watering. However, the user can opt for manual control of watering the crops in the functional control mode. The system can send notifications through LINE API for the LINE application. The system was implemented and tested in Makhamtia District, Suratthani Province, Thailand. The results showed the implementation to be useful in agriculture. The moisture content of the soil was maintained appropriately for vegetable growth, reducing costs and increasing agricultural productivity. Moreover, this work represents driving agriculture through digital innovation.
Jirapond Muangprathub; Nathaphon Boonnam; Siriwan Kajornkasirat; Narongsak Lekbangpong; Apirat Wanichsombat; Pichetwut Nillaor. IoT and agriculture data analysis for smart farm. Computers and Electronics in Agriculture 2018, 156, 467 -474.
AMA StyleJirapond Muangprathub, Nathaphon Boonnam, Siriwan Kajornkasirat, Narongsak Lekbangpong, Apirat Wanichsombat, Pichetwut Nillaor. IoT and agriculture data analysis for smart farm. Computers and Electronics in Agriculture. 2018; 156 ():467-474.
Chicago/Turabian StyleJirapond Muangprathub; Nathaphon Boonnam; Siriwan Kajornkasirat; Narongsak Lekbangpong; Apirat Wanichsombat; Pichetwut Nillaor. 2018. "IoT and agriculture data analysis for smart farm." Computers and Electronics in Agriculture 156, no. : 467-474.
This project aimed to develop a mobile application for visualization of the Dengue Hemorrhagic Fever (DHF) epidemic, by displaying the information and graph of the DHF epidemic in areas and to provide prediction of the DHF epidemic in Mueang District Surat Thani Province, Thailand. The weekly DHF cases were obtained from Surat Thani Provincial Public Health Office from January 2008 to April 2016. The application was developed by using Cordova platform, programming was completed with HTML5, JavaScripts, PHP, SQL, and JSON. The visualization of the DHF epidemic was completed with Augmented Reality (AR) technology. Google Map, Google Place, and Google Chart APIs were used for data representation of the DHF epidemic on Google Map™. Mathematica and WebMathematica technology were used to develop a Time Series model for DHF prediction. The results showed that this application can be used via mobile devices on both iOS and Android operating system. The system allowed the users to visualize the DHF epidemic with AR. The DHF cases are shown as a bar chart on Google Map™. The different colors (gray, green, yellow, orange and red colors) of a marker in Google Map™ indicated the level of the DHF epidemic in the area. Moreover, the Time Series model was prepared a prediction of DHF cases in the area. This application could be used for monitoring the DHF epidemic and preparing for a health prevention campaign to protect against the DHF epidemic in the area. The information is useful to support the related organization for efficient planning regarding policies on DHF protection.
Siriwan Kajornkasirat; Jirapond Muangprathub; Naphatsawat Rachpibool; Nitikorn Phomnui. Real-Time Analytics and Visualization: Dengue Hemorrhagic Fever Epidemic Applying Mobile Augmented Reality. Privacy Enhancing Technologies 2018, 735 -742.
AMA StyleSiriwan Kajornkasirat, Jirapond Muangprathub, Naphatsawat Rachpibool, Nitikorn Phomnui. Real-Time Analytics and Visualization: Dengue Hemorrhagic Fever Epidemic Applying Mobile Augmented Reality. Privacy Enhancing Technologies. 2018; ():735-742.
Chicago/Turabian StyleSiriwan Kajornkasirat; Jirapond Muangprathub; Naphatsawat Rachpibool; Nitikorn Phomnui. 2018. "Real-Time Analytics and Visualization: Dengue Hemorrhagic Fever Epidemic Applying Mobile Augmented Reality." Privacy Enhancing Technologies , no. : 735-742.
Risk assessment system to reduce the risk of personnel to staff were not aware that their work can also be a risk prevention and behavior change work habits to avoid the risk of working in the hospital. personnel Able to work properly so that the workplace / department that is likely threats in question would pose a danger not much to consider to take any action to solve the problem Such as radiation, heat, chemical accidents. lifting too heavy Sitting or standing too long exposure to various viruses. those risks appropriately developed a risk assessment system in the work of hospital personnel by keeping the risk of things at a critical level and the level of opportunity that will occur to the management at the risk department. To work the procedure of personnel steps to find a way to prevent and solve problems with the work of personnel to reduce the risk of personnel work.
Jumras Pitakphongmetha; Nathaphon Boonnam; Siriwan Kajornkasirat; Suchakree Limpasamanon; Pattarawat Rattanama; Watchara Jiamsawat. Analyze the system of opportunities that will affect the work of hospital personnel. 2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) 2017, 882 -885.
AMA StyleJumras Pitakphongmetha, Nathaphon Boonnam, Siriwan Kajornkasirat, Suchakree Limpasamanon, Pattarawat Rattanama, Watchara Jiamsawat. Analyze the system of opportunities that will affect the work of hospital personnel. 2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). 2017; ():882-885.
Chicago/Turabian StyleJumras Pitakphongmetha; Nathaphon Boonnam; Siriwan Kajornkasirat; Suchakree Limpasamanon; Pattarawat Rattanama; Watchara Jiamsawat. 2017. "Analyze the system of opportunities that will affect the work of hospital personnel." 2017 14th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON) , no. : 882-885.