Sam & Max Season One for Nintendo Wii will be published by Dreamcatcher/The Adventure Company in North America, and by JoWooD in Europe. In addition to English language, the game will be fully localized in French and German, and subtitled in Italian and Spanish. All versions are expected to ship during the fall 2008 season.
After LucasArts' license with Steve Purcell expired in 2005, the Sam & Max franchise moved to Telltale Games, a company of former LucasArts employees who had worked on a number of LucasArts adventure games, including on the development of Freelance Police. Under Telltale Games, a new episodic series of Sam & Max video games was made. Like both Sam & Max Hit the Road and Freelance Police, Sam & Max Save the World was in a point-and-click graphic adventure game format, although it lacked the original voice actors for the characters. The first season ran for six episodes, each with a self-contained storyline but with an overall story arc running through the series. The first episode was released on GameTap in October 2006, with episodes following regularly until April 2007, and a special compilation on the Wii released in October 2008. A second season, Sam & Max Beyond Time and Space, began in November 2007 and ended in April 2008. This was also released as a compilation on the Wii. Originally expected to be released in 2009,[44] a third season, Sam & Max: The Devil's Playhouse, began in April 2010.[45]
sam and max season 1 cracks
While it may seem kind of petty given all the death and the potential Upside Down-ification of the world, season 4 also shook up the love lives of many of the characters. Joyce and Hopper are back together, which is nice. And, it appears that Robin and her bandmate/crush Vickie (Amybeth Mcnulty) might be playing for the same team after all.
The NFL season is over, the Senior Bowl and NFL Scouting Combine are in the books, the wheels are already moving on free agency and pro days are in full swing as well. Put differently: all the mock drafts we've done up to this moment are about to be rendered moot as teams begin the process of reshaping their 2022 rosters.
(Confession: Back in November, we re-watched UNC's lackluster season-opening effort vs. Virginia Tech and had some serious doubts about Howell's game without much help around him. But last week, we finally got around to studying three more of his games and now feel much better about what he was able to do and how that might translate to the next level.)
Leonard finally cracks, and tells you that he hid the meatball sandwich inside the One-Armed Bandit at the casino. You take the BANDIT ARM that Leonard removed from the One-Armed Bandit machine, then automatically leave the office..
In situ 4D (three spatial dimensions plus time) observation of crack formation and subsequent filling of the crack by a load bearing reaction product is crucial for understanding the self-healing behavior. Furthermore, quantification of the spatial and temporal dependence is needed to validate and develop new micromechanical models for crack healing currently under development. While the challenge of in situ observation and (low level) quantification of closing and healing of cracks were already extremely demanding for (polymeric) materials that fail and heal at room temperature23, the experimental challenges become orders of magnitude more complex for (ceramic) materials that operate and heal at high temperatures. Until now, it has not been possible to directly observe the crack filling in high temperature ceramics. Thus it has also not been possible to monitor the crack repair or to establish the integrity of the repair. This is true not only for cracks formed in the pristine material, but also for cracks passing through a previously healed region. 4D X-ray tomographic microscopy using the high flux and brilliance of synchrotron X-rays is now a powerful tool for imaging the spatial and temporal evolution of microstructures from macroscopic to submicroscopic scales within a variety of materials24,25,26,27,28,29,30,31.
(a) Image of the mechanical testing rig incorporating the laser-based heating system mounted at the TOMCAT beamline; the sample stage and wedge setup are also visible. (b) Sample and wedge configuration; the arrow indicates the chevron where the cracks are generated and healed.
Abstract:Cracking in concrete structures affects performance and is a major durability problem. Cracks must be detected and repaired in time in order to maintain the reliability and performance of the structure. This study focuses on vision-based crack detection algorithms, based on deep convolutional neural networks that detect and classify cracks with higher classification rates by using transfer learning. The image dataset, consisting of two subsequent image classes (no-cracks and cracks), was trained by the AlexNet model. Transfer learning was applied to the AlexNet, including fine-tuning the weights of the architecture, replacing the classification layer for two output classes (no-cracks and cracks), and augmenting image datasets with random rotation angles. The fine-tuned AlexNet model was trained by stochastic gradient descent with momentum optimizer. The precision, recall, accuracy, and F1 metrics were used to evaluate the performance of the trained AlexNet model. The accuracy and loss obtained through the training process were 99.9% and 0.1% at the learning rate of 0.0001 and 6 epochs. The trained AlexNet model accurately predicted 1998/2000 and 3998/4000 validation and test images, which demonstrated the prediction accuracy of 99.9%. The trained model also achieved precision, recall, accuracy, and F1 scores of 0.99, respectively.Keywords: crack detection; deep learning; convolutional neural networks; image processing; AlexNet network 2ff7e9595c
Comments