Current Issue : January - March Volume : 2013 Issue Number : 1 Articles : 4 Articles
This paper describes an empirical study where the focus was on discovering differences and similarities in students working\r\non development of social applications versus students working on development of games using the same Android development\r\nplatform. In 2010-2011, students attending the software architecture course at theNorwegian University of Science and Technology\r\n(NTNU) could choose between four types of projects. Independently of the chosen type of project, all students had to go through\r\nthe same phases, produce the same documents based on the same templates, and follow exactly the same process. This study\r\nfocuses on one of projectsââ?¬â?Android project, to see how much the application domain affects the course project independently\r\nof the chosen technology. Our results revealed some positive effects for the students doing game development compared to social\r\napplication development to learn software architecture, like motivated to work with games, a better focus on quality attributes\r\nsuch as modifiability and testability during the development, production of software architectures of higher complexity, and more\r\nproductive coding working for the project. However, we did not find significant differences in awarded grade between students\r\nchoosing the two different domains....
Cheating in chess can take many forms and has existed almost as long as the game itself. The advent of computers has introduced\r\na new form of cheating into the game. Thanks to the computational power of modern-day computers, a player can use a program\r\nto calculate thousands of moves for him or her, and determine the best possible scenario for each move and countermove. These\r\nprograms are often referred to as ââ?¬Å?bots,ââ?¬Â and can even play the game without any user interaction. In this paper, we describe\r\na methodology aimed at preventing bots from participating in online chess games. The proposed approach is based on the\r\nintegration of a CAPTCHA protocol into a game scenario, and the subsequent inability of bots to accurately track the game\r\nstates. This is achieved by rotating the images of the individual chess pieces and adjusting their resolution in an attempt to render\r\nthem unreadable by a bot. Feedback from users during testing shows that there is minimal impact on their ability to play the game.\r\nPlayers rated the difficulty of reading the pieces on a scale of one to ten, with an average rank of 6.5. However, the average number\r\nof moves to adjust to the distorted pieces was only 3.75. This tells us that, although it is difficult to read the pieces at first, it is easy\r\nto adjust quickly to the new image....
Dynamic balancing of game difficulty can help cater for different levels of ability in players. However, performance in some game\r\ntasks depends on not only the player�s ability but also their desire to take risk. Taking or avoiding risk can offer players its own\r\nreward in a game situation. Furthermore, a game designer may want to adjust the mechanics differently for a risky, high ability\r\nplayer, as opposed to a risky, low ability player. In this work, we describe a novel modelling technique known as particle filtering\r\nwhich can be used to model various levels of player ability while also considering the player�s risk profile. We demonstrate this\r\ntechnique by developing a game challenge where players are required to make a decision between a number of possible alternatives\r\nwhere only a single alternative is correct. Risky players respond faster but with more likelihood of failure. Cautious players wait\r\nlonger for more evidence, increasing their likelihood of success, but at the expense of game time. By gathering empirical data for\r\nthe player�s response time and accuracy, we develop particle filter models. These models can then be used in real-time to categorise\r\nplayers into different ability and risk-taking levels....
Example-based mesh deformation techniques produce natural and realistic shapes by learning the space of deformations from\r\nexamples. However, skeleton-based methods cannot manipulate a global mesh structure naturally, whereas the mesh-based\r\napproaches based on a translational control do not allow the user to edit a local mesh structure intuitively. This paper presents\r\nan example-driven mesh editing framework that achieves both global and local pose manipulations. The proposed system is built\r\nwith a surface deformation method based on a two-step linear optimization technique and achieves direct manipulations of a\r\nmodel surface using translational and rotational controls. With the translational control, the user can create a model in natural\r\nposes easily. The rotational control can adjust the local pose intuitively by bending and twisting.We encode example deformations\r\nwith a rotation-invariant mesh representation which handles large rotations in examples. To incorporate example deformations,\r\nwe infer a pose from the handle translations/rotations and perform pose space interpolation, thereby avoiding involved nonlinear\r\noptimization. With the two-step linear approach combined with the proposed multiresolution deformation method, we can edit\r\nmodels at interactive rates without losing important deformation effects such as muscle bulging....
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