Risk Map of Dengue Case in the Southernmost Provinces of Thailand Using a Machine Learning

Total Page:16

File Type:pdf, Size:1020Kb

Risk Map of Dengue Case in the Southernmost Provinces of Thailand Using a Machine Learning Turkish Journal of Physiotherapy and Rehabilitation; 32(3) ISSN 2651-4451 | e-ISSN 2651-446X RISK MAP OF DENGUE CASE IN THE SOUTHERNMOST PROVINCES OF THAILAND USING A MACHINE LEARNING Teerawad Sriklin 1, Supattra Puttinaovarat 2, Siriwan Kajornkasirat 3 1,2,3 Faculty of Science and Industrial Technology, Prince of Songkla University, Surat Thani Campus,Surat Thani 84000, Thailand Email:1 16240320501@psu.ac.th, 2supattra.p@psu.ac.th, 3siriwan.wo@psu.ac.th ABSTRACT This study aimed to compare a machine learning model suitable for spatial data on dengue cases in the three southernmost provinces of Thailand including Pattani, Yala, and Narathiwat provinces. Data on the dengue cases and weather data including rainfall, rainy day, temperature, relative humidity, and air pressure for the period of 2015 to 2019 were obtained from the Bureau of Epidemiology, and the Meteorological Department of Southern Thailand, respectively. The machine learning models used for testing to compare the accuracy of predictions were ANN, Random Forest, SVM, and J48. The results showed that the ANN model at the number of iterations 2500 rounds gives the highest accuracy (98.89%) with lowest root mean square error and mean absolute error. Narathiwat (Russo, Si Sakhon, and Chanae District) and Pattani (Yarang and Mayo District) provinces are defined to the high-risk areas. Yala province was the low-risk area corresponding to the information obtained from the Public Health Office and the risk map created from the patient information. Keywords:dengue, ANN, Random Forest, SVM, J48. I. INTRODUCTION The World Health Organization [1] revealed the rapid increase in the number of Dengue Hemorrhagic Fever (DHF) cases are caused by the dengue virus, which contagious disease caused by mosquitoes that reached 30 times during the last 50 year. The disease also threatens the health of more than 40 percent of the world's population (2,500 million people), especially in tropical and temperate countries [2], [3]. The southern region of Thailand is different from other regions. Since the area is adjacent to the sea, high mountains and closer to the equator than the rest of the country. Therefore, the area is classified as a tropical area, resulting in high temperatures and rainfall throughout the year. The average number of rainy day is 148.7 days per year with the amount of rainfall 1,781.7 millimeters per year [4]. The reported of dengue cases and deaths in Thailand in 2019 was 42,185 cases and 29 deaths [5]. In the southern region, 6,859 cases and 3 deaths were reported [5]. There was a higher dengue incidence rate in the three southernmost provinces including Pattani, Yala, and Narathiwat provinces and higher than in the neighboring areas in the lower South region of Thailand [5]. From the previous studies, it was found that rainfall, temperature, humidity, relative humidity [6]-[8] and the application of Geographic Information Systems (GIS) tools were used to predict or determine risk areas by linking, analyzing, processing, and correlating data [9]-[11]. In this study investigated the appropriate models for dengue case prediction was done using the model of ANN, Random Forest, SVM, and J48 in the southernmost province in Thailand. The prediction is performed using WEKA software. The objectives of this study are: 1) to explore the major factors of dengue fever, 2) to study models suitable for predicting dengue severity in the three southernmost provinces, and 3) to map outbreaks of dengue fever. This will be used in planning and prevent the spread of dengue fever in the area. II. THEORY AND RELATED MATERIALS The learning and testing process is performed using WEKA software. We choose the Decision Tree algorithm as this algorithm is widely known and suitable for solving complex problems. It is an easy-to-understand model www.turkjphysiotherrehabil.org 10884 Turkish Journal of Physiotherapy and Rehabilitation; 32(3) ISSN 2651-4451 | e-ISSN 2651-446X consisting of Random Forest, J48, and two other models, ANN and SVM. The reason for choosing four algorithms is that ANN has excellent performance and high accuracy in characterizing data which like a human brain [12]. Random Forest is a popular method with its excellent performance and accuracy in classifying tasks. It also outperforms its counterparts such as neural network, discriminant analysis and Support Vector Machines (SVM) [13]. SVM is a powerful supervised learning algorithm that has many applications in biophotonics, pattern recognition, and classification [14]-[16]. For J48, it can apply can to other fields unrelated to health. It is used in credit analysis where research is compared with other algorithms. A. Artificial Neural Networks (ANN) The field of artificial neural networks tries to simulate and to fabricate networks and devices in the spirit of neurobiology, to solve the useful computational problems of the kind that biology does effortlessly [17] and can be trained to perform a particular task based on available empirical data. When the relationships between data are unknown [12]. There exist many ANN variants, this study focuses particularly on Multi-Layer Perceptron (MLP). In our implementation, the MLP has defined as per equations (1) and (2). ( ) = ( ) ( ) + ( ) ( ) (1) =1 �1 ( ) = 1+ ( ) (2) − When this equationⅇ = The total number of input nodes ( ) = A sampled data present at the node ℎ ( ) = The weight assigned to the link between the and the nodes ℎ ℎ ( ), ( ) = The bias and weight linking between bias and the node ℎ ( ) = The response at the node the node. ℎ B. Random Forest The Random Forest is an aggregation method used for classification and regression. This supervised learning method allows the construction of multiple decision trees with observations and random variables [18]. For example, one such rule might differ some dengue case locations from others by a rainfall threshold, while another rule might further split the data based on the population density within a specific range. The input data is categorized repeatedly according to different classification structures, and the final forecast/classification is done by taking the average of each tree [19]. C. SVM SVM is define the boundary between data groups and maximize the boundary distance (or extract a hyperplane in case of multiple dimensions) from the nearest data point. These closest data points, located on both sides of a line or hyperplane are called support vectors. This has led to a good generalization ability of the classifier that might produce better results with invisible samples. In the case of linear inseparable data, mathematical functions (also known as kernel functions) are used to transform data to a higher-dimensional space, which can be linearly separated in the new region [20]. D. J48 J48 is classification is the process of modeling a class from set of records labeled classes Decision Tree algorithm looks for how an attribute-vector works for number of instances. A class was also found for the newly created instance based on the training instance. This algorithm generates rules for the prediction of target variables with the help of tree classification algorithms, the key distributions can be easily understanding [21]. www.turkjphysiotherrehabil.org 10885 Turkish Journal of Physiotherapy and Rehabilitation; 32(3) ISSN 2651-4451 | e-ISSN 2651-446X III. METHODOLOGY A. Study areas In this study, we selected the three southernmost provinces of Thailand for the study areas including Pattani, Yala, and Narathiwat provinces. Southern region Thailand is on the Malay Peninsula with an area of around 70,714 km2. The study areas are located near the seaside and mountainous areas, closer to the equator than in other parts of Thailand. Therefore, it is tropical, causing high temperatures and rainfall throughout the year. It is influenced by the northeast monsoon that occurs from October to February. Topographic characteristics of the central and southern study areas, the region has the Sankalakiri Mountain Range. Yala and Narathiwat provinces resting in the east-west direction and a border between Thailand and Malaysia. On the east is a river basin stretching to the coast of the Gulf of Thailand in Pattani and Narathiwat provinces. B. Data collection The data set used in this study is monthly dengue fever cases from January 2015 to December 2019 in the three southernmost provinces of Thailand. The data were obtained from the Bureau of Epidemiology, Ministry of Public Health. Weather data in the same period were collected from the Meteorological Department of Southern Thailand consisting of mean temperature, minimum temperature, and maximum temperature, air pressure, relative humidity rainfall, and rainy days. The location of data in this study are randomly from Google Earth with a total of 180 points separated by province. C. Data Preprocessing The number of dengue cases was divided into three intervals of severity according to the principle of the class interval (Fig. 1). Severity rates are established to determine the outcome of the prediction. Severity rate data is used in conjunction with weather data (i.e. air pressure, relative humidity, temperature, rainfall, number of rainy days) D. Training and Dengue Fever Predicting Processes All data reformatted into ARFF to be able to set MLP configured ANN, and training Random Forest, SVM, and J48. The learning process is performed using WEKA software [22]. During the training and predicting, the ANN learning was set to the number of iterations given by 500, 1500, 2000, 2500, and 3000 rounds. Another parameter is learning rate is 0.3 and the hidden layer is automatic. The reason for these to find the balance between accuracy and time. Fig. 1 Dangue rate points www.turkjphysiotherrehabil.org 10886 Turkish Journal of Physiotherapy and Rehabilitation; 32(3) ISSN 2651-4451 | e-ISSN 2651-446X IV. RESULTS The results of comparisons between different accuracy were shown in Table 1. The results indicated that ANN and Random Forest gives the highest accuracy with 98.89 percent with the lowest of RMSE and MAE are 0.085 and 0.0141, respectively.
Recommended publications
  • Additions to Annonaceae in the Flora of Thailand
    THAI FOREST BULL., BOT. 49(2): 163–172. 2021. DOI https://doi.org/10.20531/tfb.2021.49.2.02 Additions to Annonaceae in the Flora of Thailand DAVID M. JOHNSON1,*, PASAKORN BUNCHALEE2, PIYA CHALERMGLIN3, PRANOM CHANTARANOTHAI4, CHARAN LEERATIWONG5, NANCY A. MURRAY6, RICHARD M.K. SAUNDERS7, YOTSAWATE SIRICHAMORN8, YVONNE C.F. SU9 & PHANOM SUTTHISAKSOPON10 ABSTRACT Work toward completion of the Annonaceae treatment for the Flora of Thailand revealed 18 species previously unrecorded for the country, six of them in the genus Fissistigma. In addition, several species previously placed in synonymy are re-instated, for which we propose three new combinations in the genera Mitrella, Monoon, and Sphaerocoryne. KEYWORDS: Desmos, Maasia, Mezzettia, Phaeanthus, Popowia, Pseuduvaria, Xylopia Accepted for publication: 11 June 2021. Published online: 27 July 2021 INTRODUCTION volume for the Flora of Thailand currently in prepa- ration will treat 39 genera and about 300 species. The Annonaceae are a pantropical plant family The landmark publication of Volume 1 of Forest comprising approximately 2,500 species in 110 Trees of Southern Thailand (Gardner et al., 2015), genera. These taxa are about evenly divided among provided a major update to our knowledge of the Africa, Asia, and the Americas, with all but eight family in Thailand. Since then, new species have genera restricted to one of the three areas. Thailand, been described in Alphonsea Hook.f. & Thomson with its diverse tropical forest habitats, harbors over (Turner & Utteridge, 2017, Leeratiwong et al., one-fourth of the known Asian species diversity and 2020), Artabotrys R.Br. (Chen & Eiadthong, 2020; all but five of the 43 indigenous Asian genera.
    [Show full text]
  • By Suvapak Imsamut
    By Suvapak Imsamut Thai Working Group The 32nd MT-JGS Working Group Meeting 27th Apr. 2021 Activities as agreed during the 17th MT-JGSC Meeting 2nd December 2020, (Video Conference) Activities Year 2019 Year 2020(2563) Year 2021 (2564) Year 2022 (2565) Year 2023 (2562) (2566) Compilation of 1. Geology and geological sites Mineral visited by the Compilation of Malaysia –Thailand geoscientists of Resources the Malaysia- metallogenic maps including strategic along Malaysia- Thailand Border Joint Geological minerals Thailand border Survey 2. Geo- conservation Compilation of Geological sites Geoheritage mapping and Geo- potential for geotourism along Malaysia- and geopark Tourism Thailand border development in Malaysia Activities and Thailand 3. Cooperative Stratigraphic correlation study and Stratigraphic correlation and fossil and fossil assemblage geological assemblages between the Jentik research in term between the Chuping Formation and the Pa Samed Formation. of stratigraphy, Formation and the Khao paleontology, and Rub Chang Formation sedimentology. TOPIC • Definition • Geo-trails • Future works DEFINITION 3 Geo-tourism The National Geographic Society defines Geotourism as “tourism that sustains or enhances the geographical character of a place—its environment, culture, aesthetics, heritage, and the well-being of its residents.” 2 Geo-trail Geological Society of Australia:'A Geotrail delivers geotourism experiences through a journey linked by an area's geology and landscape as the basis for providing visitor engagement, learning and
    [Show full text]
  • 33 Pinsuda Siridhrungsri.Indd
    ว.มรม. ปที่ 12 ฉบับที่ 2 : พฤษภาคม - สิงหาคม 2561 RMU.J. 12(2) : May - August 2018 353 การจัดการเรียนรูแบบเครือขายการมีสวนรวมสูโรงเรียนสุขภาวะในสามจังหวัดชายแดนภาคใต Learning Management Modelof Participatory Networks for Healthy Schools in the Three SouthernmostProvinces of Thailand พิณสุดา สิริธรังศร Pinsuda Siridhrungsri วิทยาลัยครุศาสตร มหาวิทยาลัยธุรกิจบัณฑิตย College of Education Sciences, Dhurakij Pundit University Corresponding author, E-mail : ppinsuda@gmail.com บทคัดยอ การวิจัยนี้มีวัตถุประสงคเพื่อ 1) ศึกษารูปแบบการดําเนินโครงการการจัดการการเรียนรูแบบเครือขายการมีสวนรวมสูโรงเรียนสุข ภาวะในสามจังหวัดชายแดนภาคใต 2) เพื่อประเมินผลการดําเนินโครงการการจัดการการเรียนรูแบบเครือขายการมีสวนรวมสูโรงเรียน สุขภาวะในสามจังหวัดชายแดนภาคใต วิธีการวิจัยเชิงคุณภาพ ดวยวิธีการศึกษาเอกสาร การเขารวมกิจกรรม การสังเกต การสัมภาษณ และการสนทนากลุม กลุมตัวอยางในการวิจัย ไดแก คณะทํางานระดับสวนกลาง จํานวน 3 คน ประธานเครือขาย 15 เครือขาย/คน ผูบริหารโรงเรียน จํานวน 100 คน/โรง ซึ่งไมไดทําหนาที่ประธานเครือขาย และครูผูรับผิดชอบโครงการ จํานวน 115 คน/โรง ตัวแทน ผูปกครอง/ชุมชน จํานวน 15 คน/เครือขาย บุคคลแกนนําเครือขายๆละ 2 คน จํานวน 30 คน ตัวแทนนักเรียนแกนนํา เครือขายละ 4 คน จาก 15 เครือขาย รวม 60 คน รวมทั้งสิ้น 338 คน เครื่องมือการวิจัย ไดแก แบบสังเคราะหเอกสาร แบบสัมภาษณกึ่งโครงสราง การรวบรวมขอมูลโดยการสังเกต สัมภาษณ สังแคราะหเอกสาร วิเคราะหขอมูลดวยวิธีการวิเคราะหเนื้อหา ผลการวิจัยพบวา 1) รูปแบบการการจัดการแบบเครือขายการมีสวนรวมของโรงเรียนสุขภาวะ ประกอบดวย แนวคิดการรวมตัว กันเปนเครือขายดวยความสมัครใจของโรงเรียน เครือขายละ 5-10 โรง โดยยึดหลักการจัดการกระจายความรับผิดชอบแบบมีสวนรวม
    [Show full text]
  • 7Th RSEP International Social Sciences Conference 1-4 May 2018
    REVIEW OF SOCIO-ECONOMIC 7 th RSEP PERSPECTIVES-RSEP International Academic Conferences 7th RSEP International Social Sciences Internation Conference 2 - 009 al Social - 284 - CONFERENCE Sciences Conference, 605 - 978 PROCEEDINGS ISBN: ISBN: Abstracts & Full Papers 1 - 4 May, 2018,4 May, Amsterdam Editors Assoc. Prof. M. Veysel Kaya Dr. Patrycja Chodnicka Jaworska NOVOTEL Amsterdam Schipol 1-4 May 2018 www.rsepconferences.com info@rsepconferences.com submission@rsepconferences.com Amsterdam, NETHERLANDS 7th RSEP International Social Sciences Conference Book 1-4 May 2018, NOVOTEL Amsterdam Schipol, Amsterdam, Netherlands www.rsepconferences.com ISBN: 978-605-284-009-2 Review of Socio-Economic Perspectives RSEP International Academic Conferences 7th RSEP International Social Sciences Conference CONFERENCE PROCEEDINGS Abstracts & Full Papers Editors Assoc. Prof. M. Veysel Kaya Dr. Patrycja Chodnicka - Jaworska ISBN: : 978-605-284-009-2 NOVOTEL Amsterdam Schipol, Amsterdam 1-4 May 2018 Amsterdam, NETHERLANDS i 7th RSEP International Social Sciences Conference Book 1-4 May 2018, NOVOTEL Amsterdam Schipol, Amsterdam, Netherlands www.rsepconferences.com ISBN: 978-605-284-009-2 7th RSEP International Social Sciences Conference Proceedings ISBN: 978-605-284-009-2 Yargi Yayinevi/Yargi Publishing House Editörler/Editors M. Veysel Kaya Patrycja Chodnicka - Jaworska Copyright © All rights reserved. No part of the material protected by this copyright may be reproduced or utilized in any form or by any means, without the prior written permission of the copyright owners, unless the use is a fair dealing for the purpose of private study, research or review. The authors and editors reserve the right that their material can be used for purely educational, scientific and research purposes.
    [Show full text]
  • Update Briefing Asia Briefing N°113 Bangkok/Brussels, 3 November 2010 Stalemate in Southern Thailand
    Update Briefing Asia Briefing N°113 Bangkok/Brussels, 3 November 2010 Stalemate in Southern Thailand I. OVERVIEW The government is planning to launch a new “political offensive” by implementing a quasi-amnesty policy under the Internal Security Act, hoping it will entice militants to The deadly conflict in Thailand’s predominantly Malay surrender and weaken the movement. The provision allows Muslim South is at a stalemate. Although military opera- the authorities, with the consent of a court, to drop criminal tions might have contributed to the reduction in violence, charges against suspected militants who, in turn, will be the government of Prime Minister Abhisit Vejjajiva has required to undergo up to six months of “training”, a made little effort to tackle the political grievances that euphemism for reverse indoctrination. It remains to be drive the insurgency. A limited unilateral suspension of seen whether the policy will succeed. Human rights ad- hostilities offered by rebels has met no significant response. vocates are sceptical, fearing suspects could be forced to Draconian laws that grant security forces sweeping pow- confess to crimes that they did not commit and calling the ers remain imposed while justice for serious cases of past training “administrative detention”. Nevertheless, the abuse remains unaddressed and torture of suspects con- quasi-amnesty measure alone is unlikely to be a lasting tinues. As bloody anti-government protests in Bangkok solution as long as larger socio-political grievances remain distracted the nation in early 2010, the death toll in the unaddressed. six-year-long insurgency steadily climbed. The conflict in the Deep South remains on the margins of Thai politics Physical abuse and torture of detainees continue, while and unresolved.
    [Show full text]
  • Update Briefing Asia Briefing N°113 Bangkok/Brussels, 3 November 2010 Stalemate in Southern Thailand
    Update Briefing Asia Briefing N°113 Bangkok/Brussels, 3 November 2010 Stalemate in Southern Thailand I. OVERVIEW The government is planning to launch a new “political offensive” by implementing a quasi-amnesty policy under the Internal Security Act, hoping it will entice militants to The deadly conflict in Thailand’s predominantly Malay surrender and weaken the movement. The provision allows Muslim South is at a stalemate. Although military opera- the authorities, with the consent of a court, to drop criminal tions might have contributed to the reduction in violence, charges against suspected militants who, in turn, will be the government of Prime Minister Abhisit Vejjajiva has required to undergo up to six months of “training”, a made little effort to tackle the political grievances that euphemism for reverse indoctrination. It remains to be drive the insurgency. A limited unilateral suspension of seen whether the policy will succeed. Human rights ad- hostilities offered by rebels has met no significant response. vocates are sceptical, fearing suspects could be forced to Draconian laws that grant security forces sweeping pow- confess to crimes that they did not commit and calling the ers remain imposed while justice for serious cases of past training “administrative detention”. Nevertheless, the abuse remains unaddressed and torture of suspects con- quasi-amnesty measure alone is unlikely to be a lasting tinues. As bloody anti-government protests in Bangkok solution as long as larger socio-political grievances remain distracted the nation in early 2010, the death toll in the unaddressed. six-year-long insurgency steadily climbed. The conflict in the Deep South remains on the margins of Thai politics Physical abuse and torture of detainees continue, while and unresolved.
    [Show full text]
  • Stalemate in Southern Thailand
    Update Briefing Asia Briefing N°113 Bangkok/Brussels, 3 November 2010 Stalemate in Southern Thailand I. OVERVIEW The government is planning to launch a new “political offensive” by implementing a quasi-amnesty policy under the Internal Security Act, hoping it will entice militants to The deadly conflict in Thailand’s predominantly Malay surrender and weaken the movement. The provision allows Muslim South is at a stalemate. Although military opera- the authorities, with the consent of a court, to drop criminal tions might have contributed to the reduction in violence, charges against suspected militants who, in turn, will be the government of Prime Minister Abhisit Vejjajiva has required to undergo up to six months of “training”, a made little effort to tackle the political grievances that euphemism for reverse indoctrination. It remains to be drive the insurgency. A limited unilateral suspension of seen whether the policy will succeed. Human rights ad- hostilities offered by rebels has met no significant response. vocates are sceptical, fearing suspects could be forced to Draconian laws that grant security forces sweeping pow- confess to crimes that they did not commit and calling the ers remain imposed while justice for serious cases of past training “administrative detention”. Nevertheless, the abuse remains unaddressed and torture of suspects con- quasi-amnesty measure alone is unlikely to be a lasting tinues. As bloody anti-government protests in Bangkok solution as long as larger socio-political grievances remain distracted the nation in early 2010, the death toll in the unaddressed. six-year-long insurgency steadily climbed. The conflict in the Deep South remains on the margins of Thai politics Physical abuse and torture of detainees continue, while and unresolved.
    [Show full text]
  • New Eco-Tourist Site in the Southern Border Province of Yala (17/2/2014)
    New Eco-Tourist Site in the Southern Border Province of Yala (17/2/2014) Yala, one of the southern border provinces, has launched a campaign to make its principal eco-tourist site, "Unseen Hala-Bala, better known. The campaign, which was launched on 14 February 2014, is a joint effort by the province and the Tourism Authority of Thailand, Yala Office. Dubbed the Amazon of ASEAN, Hala-Bala is part of the most fertile forest in the deep South of Thailand. This tropical rainforest covers an area of 433.6 square kilometers and has been designated a wildlife sanctuary. Located near the Thai-Malaysian border, Hala-Bala is actually representative of two different sectors. Hala, on the western side, is in Betong district, Yala province, and Chanae district, Narathiwat province. Bala, on the eastern side, is in Waeng and Sukhirin districts, Narathiwat province. Yala Governor Dejrat Simsiri said that the Hala-Bala Wildlife Sanctuary is rich in flora and fauna, especially numerous species of birds. It is also the settlement of the Sakai ethnic group. Nature lovers wishing to visit this reserve, he said, may start their journey in Betong district, where the weather is cool all year round. Known as "the town in the fog, Betong boasts several tourist attractions, such as Piyamit Tunnel, Winter Flower Garden, and Betong Hot Spring. The Governor suggested that visitors to this town travel along Highway 410, which offers beautiful scenery. Then they should take a boat trip in Than To district to the Hala-Bala forest, which is expected to attract eco- adventurers, especially those who enjoy hiking, jungle treks, and bird-watching.
    [Show full text]
  • Education Under Attack, 2010
    Education under Attack 2010 Education under Attack 2010 Published by the United Nations Educational, Scientific and Cultural Organization 7, place de Fontenoy, 75352 Paris 07 SP, France © UNESCO 2010 All rights reserved ISBN 978-92-3-104155-6 The ideas and opinions expressed in this publication are those of the author and not necessarily those of UNESCO and do not commit the Organization. The designations employed and the presentation of material throughout this publication do not imply the expression of any opinion whatsoever on the part of UNESCO concerning the legal status of any country, territory, city or area or of its authorities or concerning the delimitation of its frontiers or boundaries. Cover photo: Tyre, Lebanon – A boy searches for books in the rubble of a destroyed building. © Jeroen Oerlemans/Panos photos/2006 Printed by UNESCO Printed in France Foreword to the series In situations of armed conflict and insecurity, deliberate attacks on and threats against learners, academics, teachers and education facilities are both a barrier to the right to education and a serious protection issue. These violent incidents involve the use of force in ways that disrupt and deter educational provision, putting educators and learners at risk in environments that should be safe, secure and protective. The international community has made a commitment to achieving the Education for All (EFA) goals by 2015; wherever they occur, attacks on education threaten the realization of those goals. UNESCO, tasked with the global coordination of EFA, has a mandate to promote full and equal opportunities for education for all, and this includes those whose access to education is threatened or prevented by targeted violence.
    [Show full text]
  • Southern Thailand: Moving Towards Political Solutions?
    SOUTHERN THAILAND: MOVING TOWARDS POLITICAL SOLUTIONS? Asia Report N°181 – 8 December 2009 TABLE OF CONTENTS EXECUTIVE SUMMARY AND RECOMMENDATIONS................................................. i I. INTRODUCTION ............................................................................................................. 1 II. DEVELOPMENTS IN THE SOUTH IN 2009 ............................................................... 2 A. VIOLENCE INTENSIFIED................................................................................................................2 B. COMMUNAL VIOLENCE AND THE RISKS OF ARMING CIVILIANS ...................................................4 1. Al-Furqan mosque attack.............................................................................................................4 2. Paramilitary and civilian forces ...................................................................................................5 3. An industry of insecurity?............................................................................................................6 III. BOOSTING DEVELOPMENT ....................................................................................... 7 A. EMPOWERING THE SBPAC ..........................................................................................................7 B. DEVELOPMENT AS REMEDY FOR INSURGENCY ............................................................................8 C. DEVELOPING THE “RED ZONE”....................................................................................................9
    [Show full text]
  • Phuket Votes
    Volume 14 Issue 34 News Desk - Tel: 076-236555August 25 - 31, 2007 Daily news at www.phuketgazette.net 25 Baht The Gazette is published in association with Phuket votes ‘yes’ Murray released IN THIS ISSUE to new constitution on bail NEWS: Garbage mountain By Sompratch Saowakhon PHUKET: Six weeks after En- summit; AOT cuts number of glishman David Murray was airport limos; Rugby returns. PHUKET: In the August 19 na- charged with the murder without Pages 2 & 3 tional referendum of the draft intent in the death of his eight- year-old stepson, Narid “Curry” INSIDE STORY: Rajabhat dis- constitution, Phuket residents Budtharai, he is out on bail with grace: Toilets and other facili- overwhelmingly accepted the a court date yet to be set. ties failing. Pages 4 & 5 new charter with 88.9% of all those voting in favor compared Angered by the slow re- AROUND THE NATION: Gay with just 9.6% opposed. sponse, Curry’s natural father rights; Boxing jailbird; The remaining ballots, just Pissanu Badtharai asked for sup- Wombs for rent. Page 7 under 1.5% of the total cast, were port from the Bangkok-based Pavena Foundation for abused AROUND THE REGION: Expats deemed as spoiled. bemoan flip-side of tourism; The official results were women and children. The foun- Flooding dangers. Page 8 posted by the Phuket Election dation has sent a letter support- Commission (PEC) on a board ing K. Pissanu to the Provincial AROUND THE SOUTH: Bravery outside the PEC counting center Police Region 8 Commander Lt turns fatal; Military crack- Gen Thanee Thawichsee.
    [Show full text]
  • Predictive Models for Classifying the Outcomes of Violence: Case Study for Thailand’S Deep South*
    ISSN 2090-3359 (Print) ISSN 2090-3367 (Online) ΑΔΣ Advances in Decision Sciences Volume 23 Issue 3 September 2019 Michael McAleer Editor-in-Chief University Chair Professor Asia University, Taiwan Published by Asia University, Taiwan ADS@ASIAUNIVERSITY Predictive Models for Classifying the Outcomes of Violence: Case Study for Thailand’s Deep South* Bunjira Makond** Faculty of Commerce and Management Prince of Songkla University Trang, Thailand and Centre of Excellence in Mathematics Commission on Higher Education (CHE) Ministry of Education, Bangkok, Thailand Mayuening Eso Faculty of Science and Technology Prince of Songkla University Pattani, Thailand and Centre of Excellence in Mathematics Commission on Higher Education (CHE) Ministry of Education, Bangkok, Thailand Revised: August 2019 * The authors gratefully appreciate the assistance of Metta Kuning, former Director of DSCC, Prince of Songkla University, Pattani, Thailand, and a reviewer for helpful comments and suggestions. This research received much appreciated financial support from the Centre of Excellence in Mathematics, Commission on Higher Education, Thailand. ** Corresponding author: bunjira.m@psu.ac.th 1 Abstract Violence is now widely recognized as a public health problem because of its significant consequences on the health and wellness of people and it remains a growing problem in many countries including Thailand. Elucidating the factors related to violence can provide information that can help to prevent violence and decrease the number of injuries. This study explored predictive data mining models which have high interpretability and prediction accuracy in classifying the outcomes of violence. After data preprocessing, a set of 21,424 incidents occurring from 2004 to 2016 were obtained from the Deep South Coordination Centre database.
    [Show full text]