Knowledge-based design of generate-and-patch problem solvers that solve global resource assignment problems

We present MENDER, a knowledge based system that implements software design techniques that are specialized to automatically compile generate-and-patch problem solvers that satisfy global resource assignments problems. We provide empirical evidence of the superior performance of generate-and-patch over generate-and-test: even with constrained generation, for a global constraint in the domain of '2D-floorplanning'. For a second constraint in '2D-floorplanning' we show that even when it is possible to incorporate the constraint into a constrained generator, a generate-and-patch problem solver may satisfy the constraint more rapidly. We also briefly summarize how an extended version of our system applies to a constraint in the domain of 'multiprocessor scheduling'

Towards a General Framework for Formal Reasoning about Java Bytecode Transformation

Program transformation has gained a wide interest since it is used for several purposes: altering semantics of a program, adding features to a program or performing optimizations. In this paper we focus on program transformations at the bytecode level. Because these transformations may introduce errors, our goal is to provide a formal way to verify the update and establish its correctness. The formal framework presented includes a definition of a formal semantics of updates which is the base of a static verification and a scheme based on Hoare triples and weakest precondition calculus to reason about behavioral aspects in bytecode transformationComment: In Proceedings SCSS 2012, arXiv:1307.802

Empiricism and stochastics in cellular automaton modeling of urban land use dynamics

An increasing number of models for predicting land use change in regions of rapidurbanization are being proposed and built using ideas from cellular automata (CA)theory. Calibrating such models to real situations is highly problematic and to date,serious attention has not been focused on the estimation problem. In this paper, wepropose a structure for simulating urban change based on estimating land usetransitions using elementary probabilistic methods which draw their inspiration fromBayes' theory and the related ?weights of evidence? approach. These land use changeprobabilities drive a CA model ? DINAMICA ? conceived at the Center for RemoteSensing of the Federal University of Minas Gerais (CSR-UFMG). This is based on aneight cell Moore neighborhood approach implemented through empirical land useallocation algorithms. The model framework has been applied to a medium-size townin the west of São Paulo State, Bauru. We show how various socio-economic andinfrastructural factors can be combined using the weights of evidence approach whichenables us to predict the probability of changes between land use types in differentcells of the system. Different predictions for the town during the period 1979-1988were generated, and statistical validation was then conducted using a multipleresolution fitting procedure. These modeling experiments support the essential logicof adopting Bayesian empirical methods which synthesize various information aboutspatial infrastructure as the driver of urban land use change. This indicates therelevance of the approach for generating forecasts of growth for Brazilian citiesparticularly and for world-wide cities in general

Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation

We present a new encoder-decoder Vision Transformer architecture, Patcher, for medical image segmentation. Unlike standard Vision Transformers, it employs Patcher blocks that segment an image into large patches, each of which is further divided into small patches. Transformers are applied to the small patches within a large patch, which constrains the receptive field of each pixel. We intentionally make the large patches overlap to enhance intra-patch communication. The encoder employs a cascade of Patcher blocks with increasing receptive fields to extract features from local to global levels. This design allows Patcher to benefit from both the coarse-to-fine feature extraction common in CNNs and the superior spatial relationship modeling of Transformers. We also propose a new mixture-of-experts (MoE) based decoder, which treats the feature maps from the encoder as experts and selects a suitable set of expert features to predict the label for each pixel. The use of MoE enables better specializations of the expert features and reduces interference between them during inference. Extensive experiments demonstrate that Patcher outperforms state-of-the-art Transformer- and CNN-based approaches significantly on stroke lesion segmentation and polyp segmentation. Code for Patcher is released with publication to facilitate future research.Comment: MICCAI 202

Assessing Rehabilitation Strategies Of Urban Drainage Systems Based On Future Scenarios Of Urbanization

Population growth and urbanisation are creating a big need to improve the planning processes and management of urban infrastructures. Urban drainage networks are one of the vital services needed for any urban area, modelling its growth and expansion is a challenge because of the dynamics of the system. This work describes the integration of a cellular automata model, to simulate urban land use changes, with algorithms to deduct the future layout of the drainage network and with SWMM 5.0 as the hydraulic engine to assess the performance of the drainage systems in the current condition and in the future. The model was built using Dinamica EGO to simulate the land use changes in the future. The model was setup using a set of two land use maps for the municipality of Birmingham in the UK, for the year 2000 and 2006. The model was connected with the NSGAII algorithm to handle the calibration process. Once the model is calibrated three scenarios of future population growth and urbanization are run for the year 2040. The future generated map is then used to classified and cluster the areas of new developments that are suitable to expand the drainage network. Two algorithms are used to predict the future layout of the network. Once the new layout of the network is defined, the system can be connected to the existing urban drainage network and the performance of the expanded network can be assessed. To upgrade the system several rehabilitation strategies are tested to improve the capacity of the system. The integration of these models allows the exploration of several planning scenarios, in this way is possible to help the decision makers with tools and methods to anticipate bottlenecks and solutions in the urban drainage system

Patches in a timeline with ossia score

Handling of time and scores in patchers such as PureData, Max/MSP has been an ongoing concern for composers and users of such software. We introduce an integration of PureData inside the ossia score interactive and intermedia sequencer, based on libpd. This integration allows to score precisely event that are being sent to a PureData patch, and process the result of the patch's computations afterwards in score. This paper describes the way this integration has been achieved, and how it enables composers to easily add a temporal dimension to a set of patches, by leveraging both the computational power of PureData and the temporal semantics of the ossia system, in order to create complex compositions

Patches in a timeline with ossia score

Handling of time and scores in patchers such as PureData, Max/MSP has been an ongoing concern for composers and users of such software. We introduce an integration of PureData inside the ossia score interactive and intermedia sequencer, based on libpd. This integration allows to score precisely event that are being sent to a PureData patch, and process the result of the patch’s computations afterwards in score. This paper describes the way this integration has been achieved, and how it enables composers to easily add a temporal dimension to a set of patches, by leveraging both the computational power of PureData and the temporal semantics of the ossia system, in order to create complex compositions

The Purple, March 1915

The Purple is a student publication offering news of the month, editorials, poetry, college news and alumni news. This issue contains the following: Death, the Lover Erin\u27s Apostle The Call of Traumerei Blow, Balmy Winds When Men Go Mad To Sleep His Latest Victim Precursor Thanatos Our Common Enemy Night Memories of Erin Communications Under the Rose Editorial Wheat and Tares College Chronicle Alumni Arroama Athletic

Beyond representations: towards an action-centric perspective on tangible interaction

In the light of theoretical as well as concrete technical development, we discuss a conceptual shift from an information-centric to an action-centric perspective on tangible interactive technology. We explicitly emphasise the qualities of shareable use, and the importance of designing tangibles that allow for meaningful manipulation and control of the digital material. This involves a broadened focus from studying properties of the interface, to instead aim for qualities of the activity of using a system, a general tendency towards designing for social and sharable use settings and an increased openness towards multiple and subjective interpretations. An effect of this is that tangibles are not designed as representations of data, but as resources for action. We discuss four ways that tangible artefacts work as resources for action: (1) for physical manipulation; (2) for referential, social and contextually oriented action; (3) for perception and sensory experience; (4) for digitally mediated action

Towards Runtime Verification of Programmable Switches

Is it possible to patch software bugs in P4 programs without human involvement? We show that this is partially possible in many cases due to advances in software testing and the structure of P4 programs. Our insight is that runtime verification can detect bugs, even those that are not detected at compile-time, with machine learning-guided fuzzing. This enables a more automated and real-time localization of bugs in P4 programs using software testing techniques like Tarantula. Once the bug in a P4 program is localized, the faulty code can be patched due to the programmable nature of P4. In addition, platform-dependent bugs can be detected. From P4_14 to P4_16 (latest version), our observation is that as the programmable blocks increase, the patchability of P4 programs increases accordingly. To this end, we design, develop, and evaluate P6 that (a) detects, (b) localizes, and (c) patches bugs in P4 programs with minimal human interaction. P6 tests P4 switch non-intrusively, i.e., requires no modification to the P4 program for detecting and localizing bugs. We used a P6 prototype to detect and patch seven existing bugs in eight publicly available P4 application programs deployed on two different switch platforms: behavioral model (bmv2) and Tofino. Our evaluation shows that P6 significantly outperforms bug detection baselines while generating fewer packets and patches bugs in P4 programs such as switch.p4 without triggering any regressions