AUTHORS: Kittipat Savetratanakaree, Kingkarn Sookhanaphibarn, Sarun Intakosum, Ruck Thawonmas, and Kuan-Ta Chen

ABSTRACT: Most business models of online game companies usually depend on sale of virtual items and the monthly subscription fees. The prediction of player departure could increase revenues by giving special promotions out to the players who are expected to unsubscribe or quit playing the game. This paper proposes a departure prediction approach by using a new feature called “SLKdays” and a game revisitation. The feature "SLKdays" is defined as "Staytime", which is the time each player spending in an online game, of the last k days, and a game revisitation is the playing frequency in the last month to predict the next month subscription. We explore our new feature "SLKdays" to determine the optimal number of k for the departure prediction. With our proposed feature, the accuracy of the departure prediction is high, 91.92%, and the precision and recall rate are 98.22% and 84.51%.

AUTHORS: Akekachai Sacfung, Kingkarn Sookhanaphibarn, and Worawat Choensawat

ABSTRACT: Virtual worlds are successfully used for training a personal skill in an emergency situation. In this paper, we present a serious game for fire evacuation training in any public places like office buildings, conventional centers, hotels, and universities. The goal of fire safety evacuation plan is to minimize the damage, i.e. the number of injured people and casualties. In this paper, we built a virtual environment where imitates a classroom building in Bangkok University. We described a design process and development approach for achieving the objectives of evacuation training. The user evaluation was also conducted, showing that the prototype can be used effectively for training a fire drill at other public places.

AUTHORS: Anastasios Ballas, Tossaporn Santad, Kingkarn Sookhanaphibarn, and Worawat Choensawat

ABSTRACT: This paper presents a serious game-based system for dance notation training named LabanDance. The system tracks the full body motion via Microsoft Kinect of the user while performing the movement according to the dancing score. The system provides two training modes which a practice mode and an examination mode. The practice mode is designed for users with less knowledge in the notation where movement of a virtual instructor is displayed according to the score for a user to follow. The second mode is the examination mode where users must perform the body movement according to the displayed Labanotation symbols within the provided time frame. The experiment showed that users without knowledge of Labanotation can enjoy the game while learning the fundamental of the Labanotation.

AUTHORS: Piyarat Silapasuphakornwong, Kingkarn Sookhanaphibarn

ABSTRACT: This paper describes a conceptual framework for smart home that supports elderly people. We describe and compare the principles and general techniques used in automatic human fall detection via a surveillance indoor camera, which are implemented in smart home applications. The comparisons illustrate the benefits and the weak points of each technique. In addition, the challenges and trends are discussed for improving the effective fall detection applications, which is a part in elderly smart care systems in near future.

AUTHORS: Worawat Choensawat, Minako Nakamura and Kozaburo Hachimura

ABSTRACT: This paper presents a computer-aided tool for automatically generating Labanotation scores from motion capture data named GenLaban. GenLaban can be implemented with a low-cost equipment but an efficient method that allows users converting body motions to scores. The key components of GenLaban are the analysis of body motions, the quantization of body postures and the determination of body parts carrying the body weight. All the processes are under supervision of a Labanotation expert to ensure the notation meaning correctly as the use for the dance composition. The experiments showed that for dancers,

AUTHORS: Kingkarn Sookhanaphibarn and Ekachai Kanyanucharat

ABSTRACT: This paper presents the use of wireless usage data as a research tool for analyzing the routine structure of people. The patterns of wireless usage can infer the routine of student life in campus. In our experiments, we discover the student routine structure from the volume and time of the wireless usage. Without following an individual trace for any particular person, we use the volume and time of the whole accesses for particular time and location in a university campus. The analysis is based on the large wireless LANs, one-year log data of the city campus of Bangkok University (August 2011 - July 2012), and the experiment is focused on the wireless

AUTHORS: Jirawat Chomputawat, Worawat Choensawat and Don Isarakorn

ABSTRACT: In Western dance communities, Labanotation is one of the most well known dance notations. Labanotation uses a symbolic description for describing the human body movement. This paper presents a tool for generating Labanotation score from motion capture data. A graphical user interface (GUI) for semiautomatically converting motion capture data to Labanotation scores is designed to reduce an ambiguous of key-frames selection and symbol definition. The GUI allows the user easily to define some of the symbols definition according to the dance motion. In addition, user can make

AUTHORS: Payon Krainuyachan, Worawat Choensawat, Don Isarakorn

ABSTRACT: Nowadays, distant-learning systems provide a wide range of learning techniques with flexibility that provide students with increased opportunities, convenience, and personalization. Students can choose their own studying style whether learning at home or the university. Students can learn at home without the physical presence of a teacher. Recently, Thailand has experienced the worst flooding in over 50 years. At that time, some students and teachers had difficulty in commuting. For that reason, Bangkok University adopted a “BU WebEx” system which designed for helping teachers and students for distant learning. So far, there is little research